WO2013157307A1 - Pedometer - Google Patents

Pedometer Download PDF

Info

Publication number
WO2013157307A1
WO2013157307A1 PCT/JP2013/055313 JP2013055313W WO2013157307A1 WO 2013157307 A1 WO2013157307 A1 WO 2013157307A1 JP 2013055313 W JP2013055313 W JP 2013055313W WO 2013157307 A1 WO2013157307 A1 WO 2013157307A1
Authority
WO
WIPO (PCT)
Prior art keywords
walking
function
section
linear function
pedometer
Prior art date
Application number
PCT/JP2013/055313
Other languages
French (fr)
Japanese (ja)
Inventor
徳男 江村
Original Assignee
Emura Tokuo
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from JP2012110021A external-priority patent/JP5237482B1/en
Priority claimed from JP2012158085A external-priority patent/JP5180396B1/en
Priority claimed from JP2013021976A external-priority patent/JP5249476B1/en
Priority claimed from JP2013030647A external-priority patent/JP5291261B1/en
Application filed by Emura Tokuo filed Critical Emura Tokuo
Publication of WO2013157307A1 publication Critical patent/WO2013157307A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
    • G01C22/006—Pedometers
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118—Determining activity level

Definitions

  • the present invention relates to a pedometer that measures the number of steps during walking and provides walking-related information such as walking speed, walking distance, exercise intensity, calorie consumption, or fat burning amount together with the number of steps.
  • the principle of the step count measurement of the pedometer is a pendulum type or an acceleration sensor type.
  • functions there are pedometers that only measure the basic number of steps, or pedometers that calculate walking related information together with the measurement of steps.
  • pedometers that with additional functions are commercially available.
  • the calorie consumption or the amount of fat burning is useful information for users who use the pedometer for health management.
  • no standard is defined for the walking related information like the number of steps.
  • the accuracy cannot be predicted at present.
  • the inventor of the present application has been walking (hereinafter, walking is used as a synonym) for daily health improvement.
  • Carry your pedometer with basic data on walking distance and walking time (hereinafter these two quantities are called primitive data), walking-related information such as the number of steps, calories burned, and fat burning provided by the pedometer.
  • primitive data walking-related information such as the number of steps, calories burned, and fat burning provided by the pedometer.
  • “life activity” performed in daily life is also regarded as physical activity.
  • the intensity of physical activity ie, exercise intensity, is expressed in units of mets, and this value corresponds to a multiple of rest (1 mets). For example, normal walking is 3 mets.
  • the exercise (Ex) is a unit representing the amount of physical activity, and is obtained by multiplying the exercise intensity (Mets) of the physical activity by the execution time (hour) of the physical activity. Exercise for 3 minutes of physical activity at 3Mets is 1.5Ex.
  • the portion of 1.05 ⁇ weight corresponds to the basal metabolic rate per hour. In some cases, 1.05 is roughly 1.
  • exercise intensity ⁇ execution time is directly multiplied by weight.
  • required by the well-known calculation formula from height, weight, sex, and age may be used. Below, it demonstrates using Numerical formula 1 multiplied by 1.05.
  • the unit of energy consumption is kcal, and is expressed as calorie consumption below.
  • the calorie consumption necessary for burning 1 g of fat is 7.2 kcal (may be approximately 7 kcal), and the fat burning amount can be calculated from the calorie consumption.
  • pedometers are broadly divided into pendulum type and acceleration sensor type, and provided walking related information is limited to walking distance and calorie consumption, walking distance, walking time, walking speed, exercise intensity, exercise, calorie consumption, Or abundant fat burning amount, etc. Furthermore, as an additional function, memory of walking data (for example, for one week) is possible, walking data display is diverse with numerical display or graph display, with many types of data communication functions, etc. Is commercially available. The more walking-related information or additional functions, the more complicated the structure and the higher the price. A simple structure pedometer with no additional functions and limited walking-related information is inexpensive. In addition, activity meters for daily activities based on pedometer functions (deskwork and other household tasks) and mobile devices such as mobile phones with built-in pedometer functions are beginning to become popular. .
  • an error is defined by JIS for the step count measurement value of the pedometer. Because it is a low-priced product, there are no errors and lack of accuracy. However, there is no compliant standard for walking-related information, and the accuracy of the calorie consumption that is of particular interest is completely unpredictable.
  • the main function of the pedometer is to measure the number of steps more accurately, and it does not directly detect the walking speed. It can be easily understood that the walking speed increases as the number of steps measured per unit time increases, and decreases as the number of steps measured decreases. However, it seems that it is not easy to find the walking speed accurately. In fact, as the survey progressed, it turned out that how to accurately determine the walking speed, which is the basis for calculating calories burned, was an important technique. Further, as a result of the investigation, it has been found that the techniques disclosed in Patent Documents 1 to 3 described below have some problems.
  • Japanese Patent Application Laid-Open No. 2004-133826 calculates a step length during walking from a set height and a walking pitch that is a step count measurement value per unit time, and uses this step length to calculate a walking speed by a step length ⁇ walking pitch. It is disclosed.
  • the calorie consumption calculation is based on a kinetic energy formula known in physics, and a technique is disclosed in which walking speed is applied to the speed term of this formula.
  • Patent Document 2 there is a method of calculating the walking speed from the walking pitch and height (equation (3) of the same document), and a method of calculating the exercise load from the walking speed and weight (equation (4) of the same document). It is disclosed.
  • the former walking speed calculation method does not take into account the pitch range in which the change in the stride is small with respect to the change in the walking pitch, which will be described later. As a result, there is a problem that an accurate walking speed is not required.
  • the reason for not being considered is that the calculation formula of walking speed is given by the same calculation formula throughout the walking pitch range, and that the correction coefficient is also changed and calculated in the walking pitch range. None of them.
  • the amount of exercise load based on the latter kinetic energy is considered to be an amount corresponding to calorie consumption. Since it is an amount calculated from the walking speed lacking the accuracy described above, the exercise load also has a problem of lacking accuracy.
  • Japanese Patent No. 3734429 (Claim 1, Claim 2)
  • Japanese Patent No. 3916228 (Formula (3), Formula (4)) JP 2009-279239 A (paragraphs 0023 and 0024)
  • the present invention has been made in view of the conventional problems described above.
  • the subject of the present invention is the walking speed, walking distance, exercise intensity calculated from the measured number of steps and the height or weight of the set pedometer user regardless of the principle of the pendulum type or acceleration sensor type pedometer Or to provide pedometer technology with accurate walking-related information such as calories burned, or pedometer with practical accuracy and simple structure and economically cheap. is there. The practical accuracy will be described later.
  • the pedometer according to the present invention adopts the following characteristic configuration for the calculation of walking speed and exercise intensity, and the walking distance and consumption based on the calculated walking speed or exercise intensity. Calories and the like are calculated and displayed together with the number of steps.
  • the walking speed calculation configuration according to claim 1 is measured by the setting means for setting the height of the pedometer user, the step count measuring means for measuring the number of steps when the pedometer user walks, and the step count measuring means.
  • a characteristic piecewise linear function relating to the walking pitch that defines the walking characteristics and a function obtained by multiplying the characteristic piecewise linear function by the walking pitch is a characteristic piecewise quadratic function, and the correction function includes a plurality of sections of the characteristic piecewise linear function.
  • the characteristic segmentation linear function that defines the walking characteristics and the characteristic segmentation quadratic function based on this it is possible to simplify the calculation formula of the walking speed most easily, or to calculate the walking speed most easily, or The walking speed can be calculated more easily, or can be used as it is without simplifying the arithmetic expression.
  • the section function is 3, and the walking speed can be calculated relatively easily.
  • the error due to simplification of the arithmetic expression can be reduced according to the degree of simplification.
  • the setting means for setting the height of the pedometer user, the step count measuring means for measuring the number of steps when the pedometer user walks, and the step count measuring means The number of steps per unit time is calculated as the walking pitch, and the walking speed is calculated based on the result obtained by substituting the walking pitch into the correction function formula for the walking pitch and the height set in the setting means. And an arithmetic means. And the parameter which determines the characteristic of the said correction function can be set to the said setting means.
  • a characteristic piecewise linear function relating to the walking pitch that determines the walking characteristics of the pedometer user and a function obtained by multiplying the characteristic piecewise linear function by the walking pitch is a characteristic piecewise quadratic function, and the parameter is such that the correction function is a straight line If determined, the slope and intercept of one regression line obtained by performing regression analysis on the characteristic segmented quadratic function in an interval including at least one of the plurality of intervals of the characteristic segmented linear function, or When the correction function is defined as a piecewise linear function, regression analysis is performed on the characteristic piecewise quadratic function for each subdivision section obtained by dividing a section including at least one of the plurality of sections of the characteristic piecewise linear function into a plurality of sections.
  • the characteristic piecewise linear function is any one of the slope and intercept of the straight line for each section, and the sectioning point with the adjacent section, and the characteristic piecewise linear function uses the pedometer
  • a change in the ratio of the stride height to the person's walking pitch is a piecewise linear function expressed by a linear function related to the walking pitch for each section divided into a plurality according to the change
  • the correction function is the characteristic classification quadratic In the case of a function, the number of sections divided into a plurality according to the change of the characteristic piecewise linear function is three.
  • the walking characteristic value of the pedometer user can be set as a parameter. Furthermore, when the correction function for calculating the walking speed is the simplest straight line, the walking speed can be calculated most easily, or when the correction function is a simpler piecewise linear function, the walking speed is more easily calculated. When it can be calculated or becomes a quadratic function of characteristic division without being simplified, the division function is 3, and the walking speed can be calculated relatively easily. Since the walking characteristic value of the pedometer user can be set as a parameter, there is no error due to the deviation of the walking characteristic, and the walking speed can be accurately obtained within the error due to simplification of the arithmetic expression. This will be described later together with a method of setting a pedometer user's walking characteristic value as a parameter.
  • the calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed as an exercise intensity.
  • the exercise intensity function is a function obtained by performing the first operation or the second operation on the current piecewise linear function in which the relationship of the exercise intensity to the walking speed is expressed, and the first operation is: An operation of replacing the current piecewise linear function section with a new new piecewise linear function comprising a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function for each section divided into a plurality of sections including at least one.
  • the second operation includes a continuous section of the current piecewise linear function or the new piecewise linear function, and when the slope of the linear function in the continuous section is gradually non-decreasing, the continuous section of the linear function is Replaced with a new one section as the maximum value function for selecting the maximum value of the function value, and replaced with a new single section as the minimum value function for selecting the minimum value of the function value when gradually increasing, But Time, wherein the subtracting from the continuous sections one section is an operation of repeating the second operation to become impossible replacement.
  • the calculation formula for the exercise intensity representing the relationship between the walking speed and the exercise intensity is simplified according to the request for accuracy, or the calculation process by the second operation is simplified. Can be made. If accuracy is required, it is desirable to limit the first operation. Further, no error occurs in the second operation.
  • the exercise intensity is calculated by applying the obtained walking speed to the exercise intensity function obtained by replacing the first or second operation. Since the calculation result of exercise intensity includes a calculation error of walking speed, it is necessary to verify the total error. Details will be described later.
  • the walking speed calculation configuration according to Item 2 further includes the following characteristic configuration. That is, the calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, and multiplies the walking speed and the exercise intensity by a walking time to calculate a walking distance.
  • the exercise intensity function is a function obtained by performing the first operation or the second operation on the current piecewise linear function in which the relationship of the exercise intensity to the walking speed is expressed, and the first operation is: An operation of replacing the current piecewise linear function section with a new new piecewise linear function comprising a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function for each section divided into a plurality of sections including at least one.
  • the second operation includes a continuous section of the current piecewise linear function or the new piecewise linear function, and when the slope of the linear function in the continuous section is gradually non-decreasing, the continuous section of the linear function is Replaced with a new one section as the maximum value function for selecting the maximum value of the function value, and replaced with a new single section as the minimum value function for selecting the minimum value of the function value when gradually increasing, But Time, wherein the subtracting from the continuous sections one section is an operation of repeating the second operation to become impossible replacement.
  • the basal metabolic rate is set in addition to the height set in the setting means, the weight value set in the setting means, or a value obtained by multiplying the weight by a factor of 1.05, or further set in the setting means. It is one of a value calculated from sex, age, and height and weight.
  • the exercise intensity according to the required accuracy can be calculated from the obtained walking speed.
  • the walking distance, calorie consumption, and the like are calculated from these two quantities, and walking related information such as walking speed, walking distance, exercise intensity, or calorie consumption can be displayed together with the number of steps.
  • the accuracy of these two quantities is directly reflected in the value of the walking related information.
  • walking speed, exercise intensity, and other walking related information can be obtained with desired accuracy as follows.
  • the walking characteristics in the intermediate pitch interval, the lower pitch interval and the upper pitch interval in which the step change is reduced can be expressed by a piecewise linear function.
  • the walking speed can be obtained more easily by calculating the walking speed calculated based on the piecewise linear function with a regression analysis while maintaining practical accuracy.
  • the relationship of exercise intensity to walking speed is expressed as a piecewise linear function based on known numerical values, and this is simplified by maintaining the practical accuracy by regression analysis. I can do it.
  • Simplification can be made depending on the degree of accuracy required.
  • the original piecewise linear function can be used as it is without simplification.
  • there is no error due to simplification of the arithmetic expression and naturally the accuracy is superior to the simplified arithmetic expression.
  • the configuration in which the walking characteristics can be set has a greater accuracy because the walking characteristics of the pedometer user are directly reflected than the configuration in which the walking characteristics are fixed to the representative value.
  • FIG. 1 is a data and graph showing the relationship between walking speed and exercise intensity.
  • FIG. 2 is a graph and data representing the results of the walking experiment.
  • FIG. 3 is a block diagram showing the configuration of the pedometer in the embodiment according to the present invention.
  • the importance of the present invention is how to determine the walking speed from the measured number of steps and the exercise intensity that matches the ⁇ Exercise Guide 2006> or other known values from the walking speed with accuracy or practical accuracy. This technique will be described in detail from the latter exercise intensity. Before we elaborate, we refer to practical accuracy.
  • the error in the number of steps measured by the pedometer is defined as ⁇ 3% in the JIS standard.
  • ⁇ 3% in the JIS standard Within the response range of the pedometer (described later), an accurate step value within the standard error can be obtained without being substantially affected by the walking characteristics (how to walk) of the pedometer user.
  • the walking related information is greatly influenced by the walking characteristics related to the body data such as the height or weight of the pedometer user, the stride or the walking pitch, it is not easy to define an error in the standard.
  • walking-related information that does not conform to standards such as calories consumed provided with the number of steps is a calculation method originally developed by the pedometer manufacturer, and is far from known numbers. It is.
  • Pedometer users should believe and use gait-related information to generally match known values. Therefore, the accuracy of walking related information alone according to the calculation method of the present invention, which does not include a step count measurement error ( ⁇ 3%), is set to an error of about ⁇ 5 to 10%.
  • the reference value for evaluating this error is a value based on a function derived by the present invention based on a known numerical value. In the present invention, this error is referred to as practical error or practical accuracy.
  • Non-Patent Document 1 shows exercise intensity, that is, Met's value for various physical activities. The following data are shown for walking motion. This mets value is a value including one mets at rest.
  • Non-patent document 1 has been recently revised.
  • revised data the following data (referred to as revised data) of Non-Patent Document 2, which is a revised version of Non-Patent Document 1, is used as a basis for the relationship between walking speed and exercise intensity of the present invention.
  • the data of ⁇ Exercise Guide 2006>, the data of Non-Patent Document 1, and the data of Non-Patent Document 2 are well-known data published by an authoritative public institution and are sufficient for the basis.
  • the Mets value of the revised data is also a value including one Mets at rest.
  • the Mets value of the revised data has been revised upward by 0.3 / 0 / 0.2 / 0.5 / 0 / 0.7 / 0.3 Mets in order from the slower speed from the Mets value before the revision. .
  • the Mets value increases by a maximum of 0.5 / 3.8 ⁇ 13% with respect to the walking speed.
  • the problem of the excessive display of the calorie consumption of the pedometer and the problem of the prior art found in the patent literature survey described above based on the contents of the ⁇ Exercise Guide 2006> Will not be resolved.
  • FIG. 1 is a so-called piecewise linear function in which the horizontal axis is walking speed (km / hour), the vertical axis is exercise intensity (mets), and the revised data is plotted and connected by a straight line.
  • the relationship between walking speed and exercise intensity is considered to be close to a quadratic function piecewise.
  • determining this function and determining the exercise intensity is too complicated. Therefore, this continuous piecewise linear function is used as a basic (reference) function representing the relationship between walking speed and exercise intensity according to the present invention.
  • the number of sections is not small. Therefore, it is considered that there is no problem in practical use of this piecewise linear function.
  • the reason why “continuous” is given above is to distinguish it from a discontinuous piecewise linear function described later.
  • the exercise intensity can be obtained with accuracy, which is one of the problems of the present invention. Specifically, it is first determined which of the six sections the walking speed is in. Then, the exercise intensity is obtained by substituting the walking speed into the equation of the straight line (linear function) of the section.
  • This ordinary calculation procedure requires the same number of six straight lines as a section and a maximum of three section determinations. Obviously, the procedure becomes simpler if the number of intervals is reduced.
  • Another problem of the present invention is that it has practical accuracy, has a simple structure, and is economically inexpensive. Simplification of the procedure, in other words, simplification of the operation structure is an effective means for solving the latter problem.
  • the section determination is a complicated process in which the branched path is reached to the target section while comparing the walking speed.
  • the process is simplified by reducing the number of interval judgments.
  • a continuous piecewise linear function shows a concave characteristic in a continuous section if the slope of the straight line for each section is gradually non-decreasing, and shows a convex characteristic if the slope is non-increasing gradually.
  • a function that selects the maximum value of the linear expression value for each interval in the present invention, the maximum value function and Can be used).
  • a function for selecting the minimum value of the linear expression for each section (referred to as a minimum value function in the present invention) can be used. Therefore, it is not necessary to perform further section determination in continuous sections. This is likely to be easily understood and will not be described in detail.
  • the six speed sections in FIG. 1 are referred to as a first section, a second section,.
  • the piecewise linear function of FIG. 1 has a concave characteristic from the first section to the third section, a concave characteristic from the fourth section to the fifth section, and the sixth section may be treated as a concave characteristic or a convex characteristic for convenience. good.
  • the first section to the second section are concave characteristics
  • the third section to the fourth section are convex characteristics
  • the fifth section to the sixth section are convex characteristics.
  • the number of section determinations is two, and the maximum value function or the minimum value function can be used depending on the characteristics. This calculation for determining the exercise intensity is simpler than a normal calculation procedure without error. Next, a method for further simplifying the procedure will be described although an error occurs by reducing the number of sections.
  • a method of combining two or more consecutive sections into one section to make a new section, or walking speed regardless of the original six sections There is also a method of creating a new section by dividing a part or all of the section into several sections.
  • a method of obtaining a regression line by performing a regression analysis by a known least square method is simple and clear. A specific method will be described in detail below.
  • a regression line can be obtained analytically by regression analysis using the least squares method in that section.
  • a description will be given of two consecutive equally spaced intervals (v1, v2) and (v2, v3).
  • the slope and intercept of the straight line in each section be (a1, b1) and (a2, b2).
  • the slope and intercept ( ⁇ , ⁇ ) of one regression line obtained by performing the regression analysis in a single section (v1, v3) are obtained as solutions of the following binary simultaneous linear equations. Omit proof.
  • A, B, C, and D are as follows.
  • A v1 ⁇ v1 + v1 ⁇ v2 + v2 ⁇ v2
  • D v2 + v3
  • the section put together into 1 is expressed as the 1st 2nd section, for example.
  • the slope and intercept of the regression line in the third to fourth intervals are (0.9375, ⁇ 0.975).
  • this approximate value (0.94, ⁇ 0.98) is used and compared with the value of the original linear equation, it can be confirmed that the error is less than 1%, and there is no problem as a practical error.
  • the regression line in the third to fourth section becomes discontinuous at the boundary between the adjacent second and fifth sections, and the five straight lines in the five sections become discontinuous piecewise linear functions. Since the error at the discontinuity is less than 1%, it can be regarded as a piecewise linear function continuous in five sections. Furthermore, since the slopes of the straight lines in the first section, the second section, the third ⁇ 4 section, and the fifth section are gradually increasing (gradual non-decreasing), the function is regarded as a concave characteristic in these four sections. I can do it. Then, using the concave characteristic, it is possible to use the maximum value function without further section determination in these four sections.
  • the exercise speed is obtained by substituting the walking speed into the straight line expression of the sixth section. Otherwise, the walking speed is substituted into the straight line expressions of the first section, the second section, the third base 4 section, and the fifth section, and the maximum value thereof is obtained as the exercise intensity.
  • branch determination is performed faithfully for these four sections, and substitution calculation is performed using the linear expression of the section that has been reached. The determination of which method to select will be encountered during program design, for example.
  • the above method is a simplified calculation method with an error of less than 1% compared to the ordinary procedure described above. Although the error slightly increases, a simplified calculation method will be described below. This method is a calculation method in which the number of sections is further reduced and section determination is unnecessary.
  • the first section and the second section in FIG. 1 are combined into one, and the fifth section and the sixth section are combined into one.
  • the slope and intercept of the regression line in section 1 ⁇ 2 are (0.4375, 1.325) ⁇ (0.44, 1.33), and the slope and intercept of the regression line in section 5 ⁇ 6 are (2.0625). , ⁇ 8.025) ⁇ (2.06, ⁇ 8.03).
  • the slope and intercept of the regression line in the third to fourth section are (0.9375, ⁇ 0.975) ⁇ (0.94, ⁇ 0.98).
  • the adjacent regression line becomes discontinuous at the boundary of the new three sections, but the original exercise intensity (3.5 mets) at the discontinuous point (walking speed 4.8 km / h, 6.4 km / h). , 5.0 mets) are (3.532-3.442) /3.5 ⁇ 2.6%, (5.154-5.036) /5.0 ⁇ 2.4%, The error is slight.
  • the slopes of the three regression lines gradually increase. Therefore, a piecewise linear function composed of three regression lines in these three sections is continuous, and is treated as a concave characteristic in the three sections. By doing this, it is possible to obtain the exercise intensity M (Mets) by the following formula 2 using the maximum value function relating to the walking speed V (km / hour) without performing zone determination. When targeting physical activity, subtract 1 Met at rest.
  • the above-described simplified calculation method for obtaining exercise intensity from walking speed is derived from a piecewise linear function based on the present invention based on the revised data of Non-Patent Document 2.
  • This calculation method is a simplified method with practical accuracy, using one or both of the following characteristic processes. This greatly contributes to solving the problems of the present invention.
  • the characteristic process is a process using a maximum value function or a minimum value function according to the characteristics without performing further section determination in the continuous section if it is either a concave characteristic or a convex characteristic in the continuous section.
  • This is a process in which continuous sections are combined into one and replaced with one regression line obtained by regression analysis.
  • the calculation method may be determined by combining these processes in consideration of the tolerance in product design. It goes without saying that this characteristic process can also be applied to exercise intensity calculations such as jogging and running other than walking even if the shape of the piecewise linear function changes.
  • the exercise intensity can be calculated using Equation 2. Furthermore, the exercise can be calculated by multiplying the exercise intensity by the measured walking time. The calorie consumption can be calculated by multiplying this by the basal metabolic rate of 1.05 ⁇ body weight. Then, the fat burning amount can be calculated by dividing this by 7.2. In this way, the walking related information can be calculated so as to be continuous. Accordingly, since the walking speed is the basis of all walking related information, it is understood that how to determine the walking speed accurately or with practical accuracy is the key. The method for calculating the walking speed will be described in detail below.
  • Equation 3 is an arithmetic expression for walking speed.
  • N is the number of steps per unit time (for example, 1 minute), that is, the walking pitch.
  • L is height
  • the walking stride is 0.45 times the known height.
  • 0.45 ⁇ L ⁇ N is a walking distance per unit time, that is, a walking speed.
  • the stride is not always constant, it becomes wider when the pitch goes up and becomes narrower when it goes down. If the stride is set to 0.45 ⁇ L, the walking speed cannot be obtained accurately. If the stride is not corrected by any method, the walking related information lacks accuracy.
  • the stride correction according to the pitch N is performed by multiplying by the correction function f (N), and the walking speed is calculated by Equation 3.
  • Formula 3 does not use 0.45 as it is, but is a general formula using a stride factor S3 representing a magnification with respect to height. The stride factor S3 will be described later.
  • Formula 3 above shows only the form of the walking speed calculation formula without aligning the units, and is different from the actual calculation formula described later in the presence or absence of coefficients.
  • the form of Formula 3 itself is simple, the derivation of the correction function f (N) is not so easy, and the inventor of the present application has derived it from the investigation of related information including patent documents and the results of repeated walking experiments. Is.
  • a fast walk of about 6 km / h corresponds to a pitch of 120 to 130 steps / minute and a stride of a known walking stride of 0.45 ⁇ L (L is height).
  • the normal walking at a speed of about 4 km / h including the walking of daily activities shown as an example above has a pitch of 90 to 100 steps / minute and a step length of about 0.40 ⁇ L.
  • the question is the step length change in the range where the pitch is 90 steps / min or less and in the range where 130 pitches / min or more. It is not necessary to extend the straight line to this range. If it is extended, a large error occurs in the step length calculation from the following points, and it becomes impossible to obtain an accurate walking speed.
  • the stride increases as the pitch is increased, and the walking speed increases in proportion to both the pitch and the stride.
  • the pitch is in the range of 130 steps / minute or more, even if the pitch is increased, the change in the stride is small and the increase is considered to be slight, and the walking speed is mainly increased in proportion to the pitch. This is because it is not easy to keep walking while maintaining a balance between the time required for one walk with a wider stride and a fast pitch.
  • the pitch When the pitch is further increased, the stride becomes narrower and turns into an unnatural sprint for walking, and eventually the stride is recovered and the run begins. Therefore, as long as natural gait as exercise is targeted, it is necessary to set the upper limit of the pitch (for example, a value in the range of 150 to 160 steps / minute) as the response range of the pedometer.
  • the upper limit of the pitch for example, a value in the range of 150 to 160 steps / minute
  • the pitch goes down too much, it will be difficult to say that it is natural walking as an exercise including daily activities. Accordingly, as described above, it may be necessary to set the lower limit of the pitch (for example, a value in the range of 70 to 80 steps / minute) as the response range of the pedometer.
  • the lower limit of the pitch for example, a value in the range of 70 to 80 steps / minute
  • FIG. 2 shows the experimental results and graphs the relationship between the calculated walking pitch and step length.
  • a range with a small increase in stride appears from above about 125 steps / minute, and a range with a small decrease in stride appears from below about 95 steps / minute.
  • N2 steps / minute: lower limit pitch, for example 70 ⁇ N1 ⁇ 80 constant
  • N2 steps / minute: normal walking pitch, for example, 90 ⁇ N2 ⁇ 100 constant
  • N3 steps / minute: fast walking pitch, for example 120 ⁇ N3 ⁇ 130
  • Constant N4 steps / minute: upper limit pitch, for example 150 ⁇ N4 ⁇ 160 constant
  • S2 normal stride factor 0 ⁇ S2 ⁇ 1 constant, for example 0.40
  • S3 Rapid walking stride coefficient 0 ⁇ S3 ⁇ 1 constant
  • 0.45 K1 Downward slope coefficient 0 ⁇ K1 ⁇ 1 constant
  • 0.50 K4 upward slope coefficient 0 ⁇ K4 ⁇ 1 constant
  • 0.50 L N1 and
  • S2 and S3 are magnifications with respect to the height of the stride
  • K1 and K4 are coefficients relating to the slope of the correction function represented by a straight line for each section, which are multiples of the slope of the straight line in the intermediate pitch section described below.
  • the number of steps measured per unit time, that is, the walking pitch is N (steps / minute).
  • the stride correction function f (N) can be given by Equation 4, Equation 5, and Equation 6 by providing three walking pitch sections. This correction function constitutes a continuous piecewise linear function having three intervals. Note that f (N) is normalized by the rapid walking stride S3 ⁇ L.
  • Rapid walking pitch N3 to upper limit pitch N4 (hereinafter referred to as “upper pitch section”)
  • the walking speed can be accurately obtained by applying the correction value f (N) calculated by using the stride correction function of any one of the above formulas 4, 5, or 6 to the formula 3.
  • an object of the present invention is that the walking-related information provided together with the number of steps has practical accuracy, is simple in structure, and is economically inexpensive.
  • a method for solving this problem will be described in detail below by simplifying the calculation method of the walking speed according to Equation 4, Equation 5, Equation 6, and Equation 3.
  • Formula 5 is substituted into Formula 3 for the lower pitch sections N1 and N2.
  • Equation 6 is substituted into Equation 3.
  • S3 ⁇ L ⁇ N (S3-S2) / (N3-N2) (K4 ⁇ N + S3 ⁇ (N3-N2) / (S3-S2) ⁇ K4 ⁇ N3) ⁇ N ⁇ L
  • N and L are the walking pitch (steps / minute) and height (cm)
  • the coefficient k is a coefficient common to the straight lines of the three walking pitch sections
  • the coefficient ki and the constant ci are the straight lines of the three walking pitch sections. It corresponds to the slope and intercept.
  • the method for obtaining the walking speed using Equation 7 first determines the pitch interval. Since there are three sections, a maximum of two determinations are required. Then, a linear expression defined for the pitch section is selected and substitution calculation is performed. At this time, there is multiplication with a coefficient. Next, this result is multiplied by N and L.
  • This method is a normal calculation procedure through a proper process of calculating the walking speed accurately. In the previous exercise intensity calculation, a method for reducing the number of section determinations for a continuous piecewise linear function has been described. In this method, the maximum value function or the minimum value function is used according to the concave characteristic or the convex characteristic in the continuous section. By this method, the number of section determinations can be set to one. However, this alone has little effect on the simplification of the procedure.
  • Equation 7 a regression analysis is performed on a quadratic part obtained by multiplying a primary expression of N by N. If the obtained regression line is replaced with a linear expression, the number of multiplications can be reduced by one. Although the number of multiplications is reduced by one at most, if the approximation error is within a practical error, repeating such a device simplifies the structure of the calculation, and as a result, the problem of the present invention is solved. This will be specifically described below.
  • the quadratic equation (ki ⁇ N + ci) ⁇ N is subjected to regression analysis by the least square method in the interval P to Q.
  • the regression line is obtained analytically, and its slope and intercept are given by the following general formula. Omit proof. Needless to say, the slope and intercept of the regression line are coefficients and constants of the regression equation.
  • the quadratic expressions ki and ci and P and Q of the section may be considered positive values from the examination content.
  • the difference value obtained by subtracting the quadratic equation from the regression equation is maximum (positive value) in the middle of the interval, and is minimum (negative value, twice the maximum value) at both ends of the interval. . Accordingly, since the value of the quadratic expression is increased in the section, the magnitude of the error with respect to the quadratic expression of the difference is the maximum at the lower end (P) of the section and is calculated by the following expression.
  • the error is less than 1%, and there is no problem even if the quadratic equation is replaced with a regression equation. By replacing it, the number of multiplications can be reduced by one. It goes without saying that when the above common number is multiplied to return to the walking speed calculation formula, the coefficients and constants of the three regression equations change, but the error does not change. Further, the three regression lines constitute a piecewise linear function with three pitch sections.
  • the above walking speed calculation method requires the determination of the pitch interval, but the quadratic expression is simplified by the regression equation, and the miscalculation is less than 1%. This is an effective means for solving the problems of the present invention.
  • the method to be described below is a more simplified and excellent walking speed calculation method that does not require the determination of the pitch section, although the error slightly increases.
  • the quadratic part of Equation 7 is a piecewise quadratic function continuous in three pitch sections.
  • the piecewise quadratic function is subjected to regression analysis by the least square method through the pitch interval and is replaced with one regression line.
  • This regression line can also be obtained analytically.
  • the square value of the difference between the slope and the regression line having the intercept as a variable is integrated in the target section, and the variable that minimizes the integral value is determined.
  • the regression line obtained earlier is also obtained by the same method. This time, it will be a little complicated, but the results are shown below. Omit proof.
  • a quadratic expression of the intermediate pitch section is represented by (k2 ⁇ N + c2) ⁇ N.
  • the secondary expression is expressed by the following expression.
  • Quadratic formula of the lower pitch section (K1 ⁇ k2 ⁇ (N ⁇ N2) + k2 ⁇ N2 + c2) ⁇ N
  • Secondary equation of upper pitch section (K4 ⁇ k2 ⁇ (N ⁇ N3) + k2 ⁇ N3 + c2) ⁇ N
  • Regression line formula ⁇ ⁇ N + ⁇
  • the square value of the difference between the quadratic equation and the regression line equation in the pitch interval N1 to N4 is integrated in this interval, and ⁇ and ⁇ giving the minimum value of the integrated value are determined.
  • the functions G1 (X, Y), G2 (X, Y), G3 (X, Y), and G4 (X, Y), and SGM1 and SGM2 are as follows.
  • the regression equation obtained by solving the binary simultaneous linear equations is as follows. The reason for the regression analysis in the two pitch sections is related to the response range of the pedometer in addition to the confirmation of the error tendency. These will be described later. Regression equation regressed through pitch sections 70 to 160: 342 ⁇ N-9174 Regression equation regressed through pitch sections 80-150: 349 N-10094
  • the pitch to be divided into two is set to an intermediate 115 (steps / minute).
  • N1 70 (or 80)
  • N2 95
  • N3 eg 105
  • N4 115
  • S2 0.4
  • S3 0.45
  • K1 0.5
  • K4 1.0 N + 145) ⁇ N.
  • the regression line in the pitch sections 70 (80) to 115 can be determined.
  • a regression line in the pitch sections 115 to 160 (150) can be determined.
  • the determined regression equation is as follows. Regression equation of regression analysis of pitch sections 70-160 with pitch 115 and two-division pitch sections 70-115: 309 ⁇ N-6069 Regression equation for regression analysis in the pitch sections 115 to 160: 352 ⁇ N-10459 Regression equation of regression analysis of pitch sections 80 to 150 with pitch 115 and two divided pitch sections 80 to 115: 323 ⁇ N-7656 Regression equation for regression analysis in pitch interval 115 to 150: 352 ⁇ N-10361
  • pitch section 70-95 (N / 2 + 385/2) ⁇ N Secondary expression of pitch section 95-125: (N + 145) ⁇ N Secondary expression of pitch sections 125 to 160: (N / 2 + 415/2) ⁇ N Regression analysis in the pitch interval 70 to 160: 1 division: 342 ⁇ N-9174 Divided into two: MAX (309, N-6069, 352, N-10459) Regression analysis with pitch interval 80-150: 1 division: 349 ⁇ N-10094 Divided into two: MAX (323 ⁇ N-7656, 352 ⁇ N-10361)
  • the response range of the pedometer Mention the response range of the pedometer.
  • the inventor of the present application has experienced the following with respect to the response performance to the walking pitch of the pendulum and acceleration sensor built in the pedometer.
  • the previous walking experiment when walking at a pitch of 80 or less, or a pitch of 150 or more, there are rare cases where the pedometer has a strange number of steps, so that it can be clearly noticed. That is, it is considered that the sensor is not responding correctly.
  • the walking pitch when walking as a natural physical activity it can be said that the error generated when the arithmetic expression is simplified may be evaluated in the pitch sections 80 to 150.
  • the regression equation for one division in the pitch sections 70 to 160 is sufficiently practical compared to the other because the error is about 2% or less when the pitch is 80 or more. . It is a design trade-off to make the error smaller, in other words, to pursue more practical accuracy, or to simplify the arithmetic structure and make it economically cheaper. Therefore, it can be said that the method of simplifying the calculation structure described above has a great effect of expanding the selection range when the calculation method is examined in product design.
  • the calculation method for obtaining the walking speed from the walking pitch has been described in detail above.
  • the operation using one regression line obtained by regression analysis of a piecewise quadratic function through the pitch interval is the simplest method.
  • a specific calculation formula using a regression formula obtained by regression analysis in the pitch sections 80 to 150 is expressed by the following formula 8.
  • Equation 8 The walking speed V is obtained by Equation 8, and this is applied to Equation 2 to obtain the exercise intensity M.
  • Equations 2 and 8 are simplified arithmetic expressions while maintaining practical errors. This is a simplified arithmetic expression based on two piecewise linear functions derived by the inventors of the present invention through well-known numerical values and sufficient examination.
  • the two piecewise linear functions are the functions that are the basis of the present invention. One defines the relationship between walking speed and exercise intensity, and the other defines the relationship between walking pitch and stride (specifically, stature height ratio).
  • the former piecewise linear function can be applied not only to a specific pedometer user but also to an unspecified number of users.
  • the latter piecewise linear function has several parameters that determine the walking characteristics of the pedometer user in the intermediate pitch section and in the lower and upper pitch sections where the step change is small. By determining the values of these parameters, the shape of the latter piecewise linear function is specifically determined. Then, the stride according to the walking characteristics can be calculated more accurately. As a result, the walking speed can be calculated more accurately. Therefore, in addition to setting the height and weight, more accurate walking related information can be obtained by allowing the pedometer to set a walking characteristic parameter that matches the walking characteristic of the pedometer user.
  • Formula 8 is an arithmetic expression obtained by fixing characteristic parameters to representative numerical values and greatly simplifying the arithmetic structure.
  • This representative value is the following fixed value derived based on commonly used numerical values or the results of walking experiments conducted by the inventors of the present application. These numbers were often used in the above explanations.
  • Lower limit pitch N1 (steps / minute): 70 Normal walking pitch N2 (steps / minute): 95 Rapid walking pitch N3 (steps / minute): 125 Maximum pitch N4 (steps / minute): 160 Normal stride factor S2: 0.40 Rapid walking stride coefficient S3: 0.45 Downward slope coefficient K1: 0.50 Upward slope coefficient K4: 0.50
  • the error that occurs between the walking speed calculated by Equation 8 and the exercise intensity obtained by applying it to Equation 2 is a simple equation.
  • This is a total error that includes both errors due to the conversion (approximation) and the fixation of the walking characteristic parameters. That is, it is an error in the structure of the pedometer when a simplified arithmetic expression is adopted. Then, the accuracy of the walking related information provided by the pedometer, that is, the practical performance is determined. Therefore, verification of this total error is essential.
  • the walking speed of the pedometer user that is, the difference in walking characteristics
  • the walking speed V (km / hour) obtained by Formula 8 using a fixed value is calculated.
  • the error from the exercise intensity M (mets) obtained by applying to 2 is evaluated.
  • the reference value for error evaluation is a function value of a piecewise linear function used as a reference in the present invention.
  • the reference value of the exercise intensity is based on the piecewise linear function shown in FIG.
  • the reference value of the walking speed is an hourly speed converted value based on calculations using Equation 4, Equation 5, Equation 6, and Equation 7 when the walking characteristic parameter is changed.
  • the change of the walking characteristic parameter from the fixed value is as shown in Table 2 below.
  • Table 3 shows the verification results when (N), Table 4 (S), and Table 5 (inclination) are changed from the fixed values to the four sets of values in Table 2 above.
  • These tables show the calculated value of walking speed and the error of this calculated value, and the calculated value of exercise intensity and the error of this calculated value.
  • the error is expressed in% by subtracting the reference value from the calculated value of Equation 8 (or Equation 8 and Equation 2) and dividing the result by the reference value.
  • the first decimal place is rounded off in order to capture the error as an approximate number.
  • the calculated value of exercise intensity includes 1 Mets at rest.
  • the walking speed error is within ⁇ 10%
  • the exercise intensity error is within ⁇ 12% except for some sections 140 to 150 as shown in Table 4.
  • the reason why the error of the exercise intensity is enlarged in this section is considered as follows. As shown in Table 4, the walking speed calculation error that occurs when the parameter S3 changes from 45% to 47% or 43% is as small as 5% to 6%. However, as can be seen from FIG.
  • the above verification is a case where only one type of characteristic parameter is changed.
  • the error when three types are changed at the same time and two parameters of each type are simultaneously changed is also verified.
  • the error of walking speed the result almost the same as the above-mentioned aggregation result was obtained.
  • 36 combinations have an error of ⁇ 10% or less in the sections 80 to 150, and the remaining 28 patterns have an error exceeding ⁇ 10% in some sections 140 to 150.
  • the breakdown of 28 patterns was 14 patterns with errors exceeding ⁇ 10% and ⁇ 12% or less, 8 patterns exceeding ⁇ 12% and ⁇ 15% or less, and 6 combinations exceeding ⁇ 15%.
  • the walking speed calculated by Expression 8 of the present invention and the error (total error) included in the value of exercise intensity calculated by applying the result to Expression 2 were numerically verified in detail. There are two types of verification: only one parameter is changed, and three are changed simultaneously. Comprehensive evaluation of two types of verification results. The following conclusion is obtained except for the six extreme combinations shown above.
  • the walking distance, exercise, calories burned or fat burning amount of walking related information is the walking speed, exercise intensity, measured walking time (the pedometer that provides walking related information generally has a built-in clock function, Can be ignored, accurate time information that can be ignored), weight setting values, constants, etc. are simply multiplied. Therefore, it goes without saying that the error of the walking related information is not different from the above.
  • the numerical verification results using this parameter show that the walking speed is 80 to 140, the error is ⁇ 2% or less, the 80 to 150 is ⁇ 4% or less, and the exercise intensity is 80 to 135, ⁇ 4% or less, 80 It was ⁇ 8% or less at ⁇ 150.
  • the inventor's way of walking is by no means an extremely biased way of walking. I'm not going to say it's a typical way to walk, but, like many others, it's a natural gait. If there is a distribution of walking characteristic parameters, we think that it is not so far from the center of the distribution. Such an error when using the walking characteristic parameter of the present inventor has no problem as described above. From the numerical verification results shown at the end, it is considered that the practicality of the calculation method based on Formula 2 and Formula 8 fixed to the representative value has been sufficiently proved.
  • the pedometer can set a walking characteristic parameter that matches the walking characteristic of the pedometer user.
  • an arithmetic circuit built in the pedometer will have a high capability.
  • the walking speed and exercise intensity are calculated using the normal calculation procedure without simplifying the piecewise linear function determined from the set walking characteristic parameters and without further simplifying the piecewise linear function of exercise intensity. do it. There is no calculation error, and accurate walking related information reflecting the walking characteristics of the pedometer user is obtained.
  • the pedometer user's walking characteristics can be reflected in some way.
  • the walking characteristic of the pedometer user can be reflected with a small burden on an economically inexpensive and general-purpose pedometer that employs a simplified arithmetic expression in which the walking characteristic is fixed to a representative value as in Expression 8.
  • the method is as follows. For example, a walking characteristic parameter determined by walking data obtained by a walking experiment or the like is input to a personal computer or the like in which a program is previously incorporated. Then, the slope and intercept of one regression line are output. These are values that replace the coefficients and constants of the linear expression of N in Equation 8. This value is set as a set value for the pedometer. By doing so, the pedometer reflects the walking characteristics of the pedometer user with a minimum burden.
  • the default value of the set value is set to, for example, the slope and intercept value of the linear expression of N in Formula 8 obtained by fixing to a representative value. And what is necessary is just to enable it to set according to a request
  • the program incorporated in a personal computer or the like is the above-described pedometer user's walking characteristic parameters N2 (normal walking pitch), N3 (fast walking pitch), S2 (normal walking step coefficient), S3 (fast walking step coefficient). , K1 (downward slope coefficient), K4 (upward slope coefficient), and predetermined N1 (lower limit pitch) and N4 (upper limit pitch) as inputs, and the binary of ⁇ and ⁇ described above Calculate the coefficients and constants of simultaneous linear equations. Then, two solutions of this equation are output. These are the slope and intercept of one regression line.
  • Formula 8 is the most simplified walking speed calculation formula of one division.
  • the pedometer has a structure in which a coefficient and a constant of a linear expression of N in Expression 8 can be set, and must have a structure in which a set value can be read and calculated.
  • Formula 9 shows the structure of the arithmetic expression provided in the pedometer. This is the simplest form of multiplying the expression of the linear function by the height L.
  • a coefficient k and a constant c which are parameters that determine the characteristics of the linear expression N in Expression 9, are set values for the pedometer.
  • This set value is the slope and intercept of a regression line calculated by a program relating to a binary simultaneous linear equation of ⁇ and ⁇ incorporated in the above-described personal computer based on the walking characteristic parameter of the pedometer user.
  • N2 100
  • N3 125
  • S2 40%
  • S3 45%
  • K1 33%
  • K4 4%
  • lower limit N1 80
  • upper limit N4 150
  • the handling of k and c such as the number of significant digits and the sign, is a matter to be considered in the design.
  • MIN minimum value function
  • the structure of the arithmetic expression provided in the pedometer is one of the following. Since the slope does not necessarily increase gradually, the maximum value function (MAX) is used when the inclination does not decrease gradually.
  • the slopes and intercepts (k1, c1) and (k2, c2) of the two regression lines, and any of MAX and MIN are parameters that determine the characteristics of the walking speed calculation formula. These are set. Of course, the following three-part arithmetic expression and setting structure may be used.
  • walking speed V (km / h) (MAX (k1 ⁇ N + c1, k2 ⁇ N + c2)) ⁇ L
  • Walking speed V (km / h) (MIN (k1 ⁇ N + c1, k2 ⁇ N + c2)) ⁇ L
  • Three regression lines are obtained by regression analysis of the piecewise quadratic function.
  • the slopes and intercepts of these regression lines can also be obtained by utilizing the program relating to the above-mentioned binary simultaneous linear equations of ⁇ and ⁇ .
  • the slopes of the regression lines are not necessarily non-decreasing gradually or non-gradual increasing in the three sections, and there are several combinations.
  • the calculation method is not as simple as two divisions, and the method of section determination described below will be simple.
  • the division pitches that are the division points of the three divisions are defined as p1 and p2 from below.
  • a regression analysis is performed on the segmented quadratic function in a plurality of divided sections to obtain a plurality of regression lines. These constitute a new piecewise linear function. Then, the walking speed is calculated based on this piecewise linear function.
  • This calculation method can easily generalize the calculation flow in the case of the above three divisions regardless of whether the calculation flow is two divisions or more than three divisions. For example, (k1, c1), p1, (k2, c2), p2, (k3, c3), p3, (k4) are set in order from the lower side, such as the slopes and intercepts of the regression lines, and the division pitches. , C4), p4... Can uniquely determine the new piecewise linear function.
  • these set values are parameters that determine the calculation formula of the walking speed, including the setting order. They are regression line parameters and segment point parameters.
  • the above method is a uniform setting method for all divisions, and can uniformly determine the calculation structure of walking speed. This unified calculation method will be referred to as a step calculation method for the convenience of later explanation. Increasing the number of divisions naturally reduces the error, but it leads to complicated settings, an increase in calculation flow and storage capacity.
  • the characteristic of the stature height ratio with respect to the walking pitch is a characteristic originally defined in three walking pitch sections. Therefore, the division will be about the same as the number of sections.
  • the calculation method of the walking speed and exercise intensity in the pedometer has been described in detail.
  • This calculation method is derived based on two reference piecewise linear functions. Even if the number of sections of these piecewise linear functions and the linear expression in the sections change, it is not limited to pedometers, but also to portable devices such as activity meters and mobile phones, and also to jogging and running, not limited to walking exercises. Needless to say, the calculation method of the present invention can be applied or applied.
  • FIG. 3 is a block diagram showing the configuration of the pedometer using the simplified formula 9 and formula 2 described at the end of the present invention. Even in the case where the simplified equations 9 and 2 are used, even in the case where an ordinary calculation procedure is used without simplifying the two piecewise linear functions used as the basis of the present invention, or a part thereof is simplified. Even in this case, an arithmetic circuit corresponding to the required performance is selected. However, in either case, the configuration of FIG. 3 does not change significantly.
  • the unit time for calculating the walking pitch and the calculation cycle for making a round of various calculations will be described. Since the unit of pitch is usually steps / minute, the unit time is also set to 1 minute in the embodiment. There is no problem at other times.
  • MPU microprocessor
  • the required time will be about 100 ms and 200 ms. Therefore, waiting for the unit time of 1 minute when the next step value is obtained causes the MPU to play. Therefore, for example, 1/6 of 10 seconds is set as a calculation cycle, and a predetermined amount of memory is stored for the step value for each calculation cycle in such a manner that the oldest is discarded and the latest is left. Then, the step value before unit time is subtracted from the latest step value in the memory to obtain the step value of unit time in the calculation cycle, that is, the walking pitch. By adopting such a method, the MPU can be used efficiently.
  • the MPU and its peripheral functions for example, a memory unit such as a ROM (Read Only Memory) and a RAM (Random Access Memory), an input / output unit, a power supply unit, etc. are not directly related to the pedometer technology according to the present invention. Is not shown.
  • the explanation will proceed with the calculation cycle, memory, etc. in mind.
  • the calculation cycle is 10 seconds. One second would be possible. Although there is little change in the number of steps in 1 second, there is a disadvantage that the amount of memory increases.
  • the display unit that is an interface with the pedometer user the responsiveness is poor in the 10 second period. Therefore, for example, the first 1 second of 10 seconds will be calculated, and the remaining 9 seconds will be processed by the display unit.
  • the blocks numbered 1 to 8 in FIG. 3 will be described below.
  • a personal computer program
  • the walking characteristics parameters are input to the personal computer.
  • the personal computer incorporates a program for outputting k and c, which are regression line parameters corresponding to the slope and intercept of the linear function of Equation 9, (the program relating to the above-mentioned binary simultaneous linear equations of ⁇ and ⁇ ). .
  • the obtained regression line parameters k and c are input to the pedometer as set values. This minimizes the burden on the pedometer and reflects the walking characteristics of the pedometer user.
  • This personal computer is necessary only when the regression line parameter is obtained, and it is desirable to obtain the personal computer prior to the start of use of the pedometer of the embodiment.
  • the regression line parameter it is necessary to prepare in advance, such as collecting gait data and determining gait characteristic parameters, and installing a program on a personal computer. Considering the effort of this preparation, it is desirable that the regression line parameter can be set according to the request of the pedometer user. If not set, for example, the regression line parameter of Equation 8 determined from the representative value of the walking characteristic parameter described above may be used as the default value.
  • This default value is stored in a ROM (not shown) and transferred to the set value storage unit 1 when the pedometer is initialized. And when it is set, it is overwritten. The set value in the set value storage unit 1 is protected by the battery of the pedometer and does not disappear.
  • the step count measurement unit 2 is a step count measurement unit based on walking exercise, which is a basic function of a pedometer. Any step counting means such as a pendulum type or an acceleration sensor type may be used. Using existing technology, it is possible to configure a measurement unit with high accuracy within standard errors.
  • the timer 3 transmits an activation signal every 10 seconds. This activation signal is given to the walking pitch calculation unit 4, and the calculation cycle starts.
  • Various calculation processes shown below are calculation processes in the calculation cycle.
  • the walking pitch calculation unit 4 reads the latest step count data of the step count measurement unit 2 and updates the step count data in such a manner that the oldest step count data is discarded and the latest step count data is left. To do. Then, the data 6 data before (unit time before) is subtracted from the latest data to obtain the unit time step value, that is, the walking pitch N (steps / minute) in the calculation cycle.
  • N ⁇ p1 500
  • the process immediately proceeds to the calculation step, N and k1 are multiplied, c1 is added to this, and the obtained result is multiplied by the input height setting value L in the same part 5 to walk.
  • the speed V is obtained and the calculation is finished.
  • the walking speed V output from the walking speed calculator 5 is input to the exercise intensity calculator 6, and the exercise intensity M (Mets) is calculated according to Equation 2. This will be specifically described.
  • the slopes and intercepts of the linear expressions 0.44 ⁇ V + 1.33, 0.94 ⁇ V ⁇ 0.98, and 2.06 ⁇ V ⁇ 8.03 for the three walking speeds V are stored in the ROM.
  • the value of each primary expression with respect to the walking speed V input to the same unit 6 is calculated. Then, the maximum value of the obtained results is obtained as the exercise intensity M. Subtract 1 from the maximum value for physical activity only.
  • the exercise intensity M which is the output of the exercise intensity calculation unit 6, is input to the calorie consumption calculation unit 7 together with the weight setting value W (kg) of the pedometer user set in the set value storage unit 1.
  • calorie consumption K (kcal) equivalent to one hour is calculated with an implementation time of 1 (hour). More specifically, the exercise intensity M input to the part 7 is multiplied by the basal metabolic rate obtained by multiplying the weight setting value W input to the part 7 by a coefficient 1.05. This is the calorie consumption equivalent to one hour.
  • the reason for setting the value to 1 hour is that it is not necessary to change the calculation in the same part 7 even if the calculation period is changed in design, as will be described below.
  • the factor of 1.05 is an approximate number, or sex and age can be set in addition to height and weight. Basal metabolism can also be used.
  • the walking speed V in the walking speed calculation unit 5 and the calorie consumption K in the calorie consumption calculation unit 7 obtained in the calculation cycle are input to the calculation display unit 8.
  • the calorie consumption K is a value corresponding to one hour. Since the walking speed V is also in units of hourly speed, the value of the walking speed V is a distance corresponding to one hour. By multiplying both by the calculation cycle time 1/360 (10 seconds), it is converted into a value in the calculation cycle. Further, in the same section 8, in order to display a walking distance and a cumulative value of calorie consumption, a cumulative calculation is also performed. These conversion calculation and total calculation are performed in common for V and K in the same section 8. The structure is simpler than when the walking speed calculation unit 5 and the calorie consumption calculation unit 7 individually perform conversion calculation and total calculation. In addition, even if the calculation cycle time is changed in design, there is a merit because only the calculation change in the part 8 is required.
  • the walking speed V and the calorie consumption K input to the calculation display unit 8 are updated in such a manner that they are added to each cumulative value before one calculation cycle.
  • the cumulative value of the walking speed V and the calorie consumption K is multiplied by 1/360 to be converted into display data.
  • These display data can be confirmed by the pedometer user via the calculation display unit 8 together with the number of steps as walking related information.
  • the setting value in the setting value storage unit 1 is also input to the same unit 8, and the setting value is confirmed or changed via the same unit 8.
  • the output of the exercise intensity calculation unit 6 is exercise intensity M (Mets). This value is the amount of physical activity per hour, that is, the value of exercise (Ex) itself. By multiplying this by the calculation cycle time 1/360 (10 seconds), it can be converted into a value in the calculation cycle. Further, the display format is a cumulative value. Therefore, if the output of the same unit 6 is directly input to the calculation display unit 8 (dotted arrow next to the figure) and the cumulative calculation and conversion calculation are performed in the same manner as the above walking distance and calorie consumption, exercise is also related to walking. Can be provided as information.
  • the walking speed V and the exercise intensity M input to the part 8 may be handled not only as a cumulative value but also as an original immediate value.
  • the average value or the maximum value can be processed by the same unit 8 and displayed from the same unit 8 without significantly changing the structure.
  • the amount of fat burning can be obtained by simply dividing the calorie consumption by the predetermined value 7.2. Therefore, when displaying this as walking related information, the value of the calorie consumption displayed may be divided by 7.2 and displayed.

Abstract

Provided is a technique in which walking-related information provided by a pedometer, such as walking speed, walking distance, exercise intensity, and consumed calories have accuracy or practical accuracy and are provided through a simple configuration and at a low cost. A change in the ratio between the stride for walking pitch and height is captured by a piecewise linear function. The relationship between the walking speed and the exercise intensity is expressed as a piecewise linear function based on a known value. The arithmetical expression of the walking speed and the exercise intensity derived therefrom is subject to regression analysis, and the obtained regression line is simplified. The technique is thereby basically constituted. An error caused by the simplification is changed by the number of divided sections or the like. In the present invention, a plurality of directly usable techniques are provided so that a calculation method corresponding to a requested tolerance can be selected. Also, in order to raise the accuracy, a technique reflecting the walking characteristics of a pedometer user is provided. By combining these techniques, an ideal pedometer that is inexpensive and accurate can be created.

Description

歩数計Pedometer
本発明は、歩行時の歩数を計測し、歩数と併せて歩行速度、歩行距離、運動強度、消費カロリー、または脂肪燃焼量などの歩行関連情報を提供する歩数計に関する。 The present invention relates to a pedometer that measures the number of steps during walking and provides walking-related information such as walking speed, walking distance, exercise intensity, calorie consumption, or fat burning amount together with the number of steps.
歩数計の歩数計測の原理は振り子式、或いは加速度センサ式がある。機能に関しては、基本の歩数の計測のみの歩数計、或いは歩数の計測と併せて歩行関連情報の演算を行う歩数計もある。現在では、さらに付加機能も備わった、多くの種類の歩数計が市販されている。 The principle of the step count measurement of the pedometer is a pendulum type or an acceleration sensor type. Regarding functions, there are pedometers that only measure the basic number of steps, or pedometers that calculate walking related information together with the measurement of steps. At present, many types of pedometers with additional functions are commercially available.
歩数計の計測歩数に関しては、ＪＩＳ（日本工業規格ＪＩＳ　Ｓ　７２００）で誤差が規定（±３％）されているため、誤差内で正確な歩数値を得ることが出来る。 Regarding the number of steps measured by the pedometer, since an error is defined (± 3%) in JIS (Japanese Industrial Standards JIS S 7200), an accurate step value can be obtained within the error.
歩数計の提供する歩行関連情報のなかでも消費カロリーまたは脂肪燃焼量は、歩数計を健康管理に活用している利用者には有益な情報である。しかし、歩行関連情報に関しては、歩数のように規格が定められていない。そして、歩数計製造者の独自の演算方式が採用されているため、現状ではその正確さに関して予想がつかない。 Among the walking-related information provided by the pedometer, the calorie consumption or the amount of fat burning is useful information for users who use the pedometer for health management. However, no standard is defined for the walking related information like the number of steps. And since the pedometer manufacturer's original calculation method is adopted, the accuracy cannot be predicted at present.
本願発明者は健康状態改善のためにウォーキング（以下では歩行を同意語として使う）を日課としてきた。歩数計を携帯して歩行距離と歩行時間の基本データ（以下ではこの２量を原始データと呼ぶ）と、歩数計が提供する歩数および消費カロリー、脂肪燃焼量などの歩行関連情報を、歩行データとして記録してきた。予め歩行コースをいくつか定めてその距離を地図で測っておいた。そして、この予め測ったコース距離と歩行時に計った時間を原始データとして記録した。 The inventor of the present application has been walking (hereinafter, walking is used as a synonym) for daily health improvement. Carry your pedometer with basic data on walking distance and walking time (hereinafter these two quantities are called primitive data), walking-related information such as the number of steps, calories burned, and fat burning provided by the pedometer. Has been recorded as. I set some walking courses in advance and measured the distance on a map. The course distance measured in advance and the time measured during walking were recorded as primitive data.
本願発明者は市の開催した健康づくりのための説明会に参加する機会があった。この時に厚生労働省の運動施策の一環として報告された「健康づくりのための運動指針２００６＜エクササイズガイド２００６＞」の説明を受け、運動強度（メッツ）、エクササイズ、消費カロリーおよび脂肪燃焼量などの諸量の間の関係、歩行速度と運動強度の関係などの知識を得た。この知識を用いて、歩行記録の原始データからその歩行での消費カロリーを計算し、歩数計の消費カロリー表示値と比較し分析することにした。上記の諸量の間の関係、そして歩行速度と運動強度の関係は、今回の発明に深く関わるため、分析結果を述べる前に詳述する。 The inventor of the present application had an opportunity to participate in a briefing session for health promotion held by the city. In response to the explanation of “Exercise Guidelines 2006 for Health Promotion <Exercise Guide 2006>” reported as part of the Ministry of Health, Labor and Welfare's exercise measures, I gained knowledge such as the relationship between quantity and the relationship between walking speed and exercise intensity. Using this knowledge, we calculated calories burned during walking from the original data of walking records, and compared with the calorie consumption display value of the pedometer for analysis. Since the relationship between the above quantities and the relationship between walking speed and exercise intensity are deeply related to the present invention, they will be described in detail before describing the analysis results.
厚生労働省の運動施策の一環として報告された＜エクササイズガイド２００６＞では、体力の維持・向上を目的として行われる「運動」以外に、日常生活で行われる「生活活動」も身体活動とされる。身体活動の強さ、即ち運動強度はメッツの単位で表され、この値は安静時（１メッツ）の倍数に相当する。例えば、普通歩行は３メッツとされる。エクササイズ（Ｅｘ）は身体活動の量を表す単位であり、その身体活動の運動強度（メッツ）に身体活動の実施時間（時）を乗じたものである。３メッツの身体活動を３０分間行った時のエクササイズは、１．５Ｅｘである。 In the <Exercise Guide 2006> reported as part of the Ministry of Health, Labor and Welfare's exercise measures, in addition to “exercise” performed for the purpose of maintaining and improving physical fitness, “life activity” performed in daily life is also regarded as physical activity. The intensity of physical activity, ie, exercise intensity, is expressed in units of mets, and this value corresponds to a multiple of rest (1 mets). For example, normal walking is 3 mets. The exercise (Ex) is a unit representing the amount of physical activity, and is obtained by multiplying the exercise intensity (Mets) of the physical activity by the execution time (hour) of the physical activity. Exercise for 3 minutes of physical activity at 3Mets is 1.5Ex.
消費カロリーの計算については、身体活動量に相当するエネルギー消費量の計算式が、上記の＜エクササイズガイド２００６＞に記載されている。身体活動を行っている者の体重に比例し、安静時の分を含めて数式１で計算される。 Regarding the calculation of calorie consumption, a formula for calculating the amount of energy consumption corresponding to the amount of physical activity is described in <Exercise Guide 2006>. It is proportional to the weight of the person who is performing physical activity, and is calculated by Equation 1 including the rest.
Figure JPOXMLDOC01-appb-M000001
Figure JPOXMLDOC01-appb-M000001
数式１の１．０５は、安静時酸素摂取量（３．５ｍｌ／ｋｇ／分）と酸素１０００ｍｌ当りのエネルギー消費量＝５ｋｃａｌから計算される１時間・１ｋｇ当りのエネルギー消費量である。１．０５×体重の部分が１時間当りの基礎代謝量に相当する。１．０５が概略１とされる場合もあり、この場合は、運動強度×実施時間に直接に体重が乗算される。また、身長、体重、性別、年齢から公知の計算式で求められた１時間当りの基礎代謝量が使われることもある。以下では、１．０５を乗ずる数式１を用いて説明する。また、エネルギー消費量の単位がｋｃａｌであり、以下では、消費カロリーと表現する。 1.05 in Formula 1 is the energy consumption per hour / kg calculated from the oxygen intake at rest (3.5 ml / kg / min) and the energy consumption per 1000 ml of oxygen = 5 kcal. The portion of 1.05 × weight corresponds to the basal metabolic rate per hour. In some cases, 1.05 is roughly 1. In this case, exercise intensity × execution time is directly multiplied by weight. Moreover, the basal metabolic rate per hour calculated | required by the well-known calculation formula from height, weight, sex, and age may be used. Below, it demonstrates using Numerical formula 1 multiplied by 1.05. Moreover, the unit of energy consumption is kcal, and is expressed as calorie consumption below.
脂肪燃焼量については、脂肪１ｇの燃焼に必要な消費カロリーは７．２ｋｃａｌであり（概略７ｋｃａｌとされることもある）、消費カロリーから脂肪燃焼量を計算出来る。 Regarding the fat burning amount, the calorie consumption necessary for burning 1 g of fat is 7.2 kcal (may be approximately 7 kcal), and the fat burning amount can be calculated from the calorie consumption.
次に、歩行速度と運動強度の関係について説明する。一般に、人の歩く速さは４ｋｍ／時程度と言われている。＜エクササイズガイド２００６＞には、歩行速度と運動強度の関係が段階にわけて次のように示されている。
ゆっくりした歩行　　：平地、５４ｍ／分（３．２ｋｍ／時）　　　　　２．５メッツ
普通歩行　　　　　　：平地、６７ｍ／分（４．０ｋｍ／時）　　　　　３メッツ
歩行（通勤時など）　：平地、８１ｍ／分（４．８ｋｍ／時）　　　　　３．３メッツ
やや速歩　　　　　　：平地、９４ｍ／分（５．６ｋｍ／時）　　　　　３．８メッツ
速歩　　　　　　　　：平地、９５～１００ｍ／分（６ｋｍ／時程度）　４メッツ
かなり速歩　　　　　：平地、１０７ｍ／分（６．４ｋｍ／時）　　　　５メッツ Next, the relationship between walking speed and exercise intensity will be described. In general, it is said that the walking speed of a person is about 4 km / hour. In <Exercise Guide 2006>, the relationship between walking speed and exercise intensity is shown in stages as follows.
Slow walking: Flat ground, 54 m / min (3.2 km / hr) 2.5 Mets ordinary walking: Flat ground, 67 m / min (4.0 km / hr) 3 Mets walking (commuting, etc.): Flat ground, 81 m / min ( 4.8 km / hour) 3.3 Mets slightly fast walking: Flat ground, 94 m / min (5.6 km / hour) 3.8 Mets fast walking: Flat ground, 95-100 m / min (about 6 km / hour) 4 Mets fairly fast walking: Flat ground 107 m / min (6.4 km / h) 5 mets
歩行記録の原始データから消費カロリーを計算するには、原始データの歩行距離と歩行時間から歩行速度を計算し、その歩行速度に対応する運動強度を上記の関係から求め、数式１を用いて消費カロリーを計算する。＜エクササイズガイド２００６＞には段階ごとの歩行速度に対する運動強度しか示されていないため、その間の歩行速度に対しては線形補間することで計算する。 To calculate calorie consumption from the original data of walking records, calculate the walking speed from the walking distance and walking time of the original data, find the exercise intensity corresponding to the walking speed from the above relationship, and use Equation 1 to consume. Calculate calories. Since <Exercise Guide 2006> only shows the exercise intensity with respect to the walking speed for each stage, the walking speed during that time is calculated by linear interpolation.
蓄積された歩行記録データをパソコンで分析することは、便利なソフトウェアツールが提供されているため比較的容易なことである。本願発明者もこれを活用して、原始データから数式１で計算される消費カロリーと歩数計の消費カロリー表示値を比較し分析を行った。分析の結果、原始データから計算した消費カロリーに比べて、歩数計の消費カロリー表示値が過大であることに気付き（歩行速度により、１．５倍程度、またはそれ以上）、何故なのかと疑問を持つに至った。 It is relatively easy to analyze the accumulated walking record data with a personal computer because a convenient software tool is provided. The inventor of the present application also made use of this to compare and analyze the calorie consumption calculated from Formula 1 with the formula 1 and the calorie consumption display value of the pedometer. As a result of the analysis, compared to the calorie consumption calculated from the original data, it is noticed that the calorie consumption display value of the pedometer is excessive (about 1.5 times or more depending on walking speed), and wonders why. I came to have it.
ここで、市販されている歩数計の現状について触れておく。歩数計は、原理が振り子式と加速度センサ式に大別され、提供される歩行関連情報が、歩行距離と消費カロリーに限定、歩行距離、歩行時間、歩行速度、運動強度、エクササイズ、消費カロリー、または脂肪燃焼量など豊富、さらには付加機能として、歩行データのメモリー（例えば１週間分）が可能、歩行データの表示が数値表示またはグラフ表示と多様、データ通信機能付など、多くの種類のものが市販されている。歩行関連情報または付加機能が多ければ多いほど複雑な構造となり価格も高く、付加機能が無く歩行関連情報が限定された単純構造の歩数計は低価格である。また、歩数計の機能を基本にした日常の行動（デスクワークなどの仕事や家事）も対象とする活動量計、歩数計の機能を内蔵した携帯電話に代表される携帯機器なども普及し始めている。 Here, I will touch on the current status of commercially available pedometers. Pedometers are broadly divided into pendulum type and acceleration sensor type, and provided walking related information is limited to walking distance and calorie consumption, walking distance, walking time, walking speed, exercise intensity, exercise, calorie consumption, Or abundant fat burning amount, etc. Furthermore, as an additional function, memory of walking data (for example, for one week) is possible, walking data display is diverse with numerical display or graph display, with many types of data communication functions, etc. Is commercially available. The more walking-related information or additional functions, the more complicated the structure and the higher the price. A simple structure pedometer with no additional functions and limited walking-related information is inexpensive. In addition, activity meters for daily activities based on pedometer functions (deskwork and other household tasks) and mobile devices such as mobile phones with built-in pedometer functions are beginning to become popular. .
先述の通り、歩数計の歩数計測値に関してはＪＩＳで誤差が規定されている。低価格品であるために誤差が大きく正確さに欠けるということはない。しかし、歩行関連情報に関しては準拠規格が無く、特に注目している消費カロリーの正確さに関しては全く予想がつかない。 As described above, an error is defined by JIS for the step count measurement value of the pedometer. Because it is a low-priced product, there are no errors and lack of accuracy. However, there is no compliant standard for walking-related information, and the accuracy of the calorie consumption that is of particular interest is completely unpredictable.
そこで、上記消費カロリーに関する疑問点について製造者に問合せてみたが、歩数計内部の独自演算方式に関するため開示は出来ないとの回答であった。このため本願発明者は特許文献調査などを鋭意行った。 Therefore, the manufacturer was inquired about the above-mentioned question about calorie consumption, but the answer was that it was not possible to disclose because of the unique calculation method inside the pedometer. For this reason, the inventor of the present application diligently investigated patent documents.
歩数計は歩数をより正確に計測することが主な機能であり、直接に歩行速度を検出しているわけではない。単位時間での歩数計測値が多くなれば歩行速度が速くなり、少なくなれば遅くなることは容易に分かる。しかし、歩行速度を正確に求めることは容易なことではないように思われた。事実、調査を進める中で、消費カロリーなどの計算の基礎となる歩行速度をいかに正確に求めるかが重要な技術であることが分かった。また、調査の結果、以下に示す特許文献１～特許文献３に開示された技術ではいくつかの問題があることも分かった。 The main function of the pedometer is to measure the number of steps more accurately, and it does not directly detect the walking speed. It can be easily understood that the walking speed increases as the number of steps measured per unit time increases, and decreases as the number of steps measured decreases. However, it seems that it is not easy to find the walking speed accurately. In fact, as the survey progressed, it turned out that how to accurately determine the walking speed, which is the basis for calculating calories burned, was an important technique. Further, as a result of the investigation, it has been found that the techniques disclosed in Patent Documents 1 to 3 described below have some problems.
特許文献１には、歩行中の歩幅を、設定された身長と単位時間の歩数計測値である歩行ピッチとから演算し、この歩幅を用いて、歩行速度を歩幅×歩行ピッチで演算する技術が開示されている。また、消費カロリー演算は物理学で公知の運動エネルギー公式に基づき、この公式の速度の項に歩行速度を適用する技術が開示されている。 Japanese Patent Application Laid-Open No. 2004-133826 calculates a step length during walking from a set height and a walking pitch that is a step count measurement value per unit time, and uses this step length to calculate a walking speed by a step length × walking pitch. It is disclosed. The calorie consumption calculation is based on a kinetic energy formula known in physics, and a technique is disclosed in which walking speed is applied to the speed term of this formula.
上記の歩幅演算には、研究により見出されたとされる回帰分析に基づく回帰直線が使われている。しかし、後述する歩行ピッチ変化に対して歩幅変化が少なくなるピッチ範囲のことが全く考慮されていない。この結果、歩行ピッチが上がれば上がるだけ歩幅が広く、下れば下るだけ歩幅が狭く計算され、歩行関連情報の誤差が拡大する問題がある。考慮されていないことの理由は、回帰分析で求めたとされる係数を歩行ピッチ範囲で変更して演算するという記載や示唆がいずれもないことである。 In the above-mentioned stride calculation, a regression line based on a regression analysis that has been found by research is used. However, no consideration is given to the pitch range in which the change in the stride is less than the change in the walking pitch described later. As a result, if the walking pitch increases, the step length increases as the walking pitch increases, and as the walking pitch decreases, the step length decreases as it decreases. The reason why it is not taken into account is that there is no description or suggestion that the coefficient calculated in the regression analysis is changed in the walking pitch range.
消費カロリー計算に関しても、＜エクササイズガイド２００６＞に記載の計算式の値と比べて大きな差が生じる問題がある。このことを示す数値計算例を以下に示す。歩幅：０．８ｍ、歩行ピッチ：１２５歩／分、体重：６５ｋｇ、歩行時間：１時間として、１時間の消費カロリーを計算してみる。歩行速度は、０．８×１２５×６０＝６ｋｍ／時、１００ｍ／分、１．６７ｍ／秒である。＜エクササイズガイド２００６＞では歩行速度が６ｋｍ／時程度では運動強度は４メッツである。この４メッツを用い、安静時の１メッツ分は差し引いて計算する。
特許文献１による計算結果
消費カロリー（ｋｃａｌ）
＝１／２×６５×１．６７×１．６７×３６００／４．２／１０００＝７７．７
＜エクササイズガイド２００６＞に記載の計算式による計算結果
消費カロリー（ｋｃａｌ）
＝（４－１）×１×１．０５×６５＝２０５ Regarding calorie consumption calculation, there is a problem that a large difference occurs compared to the value of the calculation formula described in <Exercise Guide 2006>. A numerical calculation example showing this will be shown below. Let's calculate the calorie consumption for 1 hour, assuming the step length: 0.8 m, walking pitch: 125 steps / minute, weight: 65 kg, walking time: 1 hour. The walking speed is 0.8 × 125 × 60 = 6 km / hour, 100 m / minute, and 1.67 m / second. In <Exercise Guide 2006>, when the walking speed is about 6 km / hour, the exercise intensity is 4 mets. Use the 4 Mets, and subtract 1 Met at rest.
Calculation result by Patent Document 1 Calorie consumption (kcal)
= 1/2 * 65 * 1.67 * 1.67 * 3600 / 4.2 / 1000 = 77.7
<Calculation result calorie consumption (kcal) by the calculation formula described in <Exercise Guide 2006>
= (4-1) × 1 × 1.05 × 65 = 205
特許文献２には、歩行ピッチと身長から歩行スピードを演算する方法（同文献の（３）式）、この歩行スピードと体重から運動負荷量を演算する方法（同文献の（４）式）が開示されている。前者の歩行スピード演算方法は、特許文献１に関しても述べたように、後述する歩行ピッチ変化に対して歩幅変化が少なくなるピッチ範囲のことが全く考慮されていない。この結果、正確な歩行スピードが求められない問題がある。考慮されていないことの理由は、歩行スピードの演算式が、歩行ピッチ範囲を通して同一の演算式で与えられている、また、補正係数に関しても歩行ピッチ範囲で変更して演算するという記載や示唆のいずれもないことである。 In Patent Document 2, there is a method of calculating the walking speed from the walking pitch and height (equation (3) of the same document), and a method of calculating the exercise load from the walking speed and weight (equation (4) of the same document). It is disclosed. The former walking speed calculation method does not take into account the pitch range in which the change in the stride is small with respect to the change in the walking pitch, which will be described later. As a result, there is a problem that an accurate walking speed is not required. The reason for not being considered is that the calculation formula of walking speed is given by the same calculation formula throughout the walking pitch range, and that the correction coefficient is also changed and calculated in the walking pitch range. None of them.
後者の運動エネルギーに基づくとされる運動負荷量は、消費カロリーに相当する量と考えられる。上で述べた正確さを欠く歩行スピードから演算される量であるため、運動負荷量もやはり正確さを欠く問題がある。 The amount of exercise load based on the latter kinetic energy is considered to be an amount corresponding to calorie consumption. Since it is an amount calculated from the walking speed lacking the accuracy described above, the exercise load also has a problem of lacking accuracy.
特許文献３には、既存の技術とされる運動強度を求める２例が記載されている。歩行についてこの２例を検証してみる。歩幅：８５ｃｍ、歩行ピッチ：１２５歩／分とすると、歩行速度は６．４ｋｍ／時であり、＜エクササイズガイド２００６＞に記載の運動強度は５メッツである。安静時の１メッツを差し引いて４メッツである。
１例目での計算結果：－７．０６５＋０．１０５×１２５＝６．０６
２例目での計算結果：０．０１５×１２５×０．８５＋１．５９９＝３．１９
計算方法により計算結果のメッツ値が異なり、＜エクササイズガイド２００６＞に記載のメッツ値とも合わず、既存の技術にも問題があると言える。 Patent Document 3 describes two examples for obtaining exercise intensity, which is an existing technique. Let us examine these two examples of walking. If the step length is 85 cm and the walking pitch is 125 steps / minute, the walking speed is 6.4 km / hour, and the exercise intensity described in <Exercise Guide 2006> is 5 mets. Subtracting 1 Met at rest is 4 Mets.
Calculation result in the first example: −7.065 + 0.105 × 125 = 6.06
Calculation result in second example: 0.015 × 125 × 0.85 + 1.599 = 3.19
The Met value of the calculation result differs depending on the calculation method, and does not match the Met value described in <Exercise Guide 2006>, and it can be said that there is a problem with the existing technology.
特許第３７３４４２９号公報（請求項１、請求項２）Japanese Patent No. 3734429 (Claim 1, Claim 2) 特許第３９１６２２８号公報（（３）式、（４）式）Japanese Patent No. 3916228 (Formula (3), Formula (4)) 特開２００９－２７９２３９号公報（段落００２３、００２４）JP 2009-279239 A (paragraphs 0023 and 0024)
本発明は、上で述べた従来の問題点に鑑みてなされたものである。本発明の課題は、振り子式あるいは加速度センサ式の歩数計の原理を問わず、計測された歩数と設定された歩数計利用者の身長または体重などから演算される歩行速度、歩行距離、運動強度または消費カロリーなどの歩行関連情報が、正確さをもった歩数計に関する技術、あるいは、実用上の正確さをもち、かつ、構造が単純で経済的に安価な歩数計に関する技術を提供することにある。実用上の正確さに関しては後で述べる。 The present invention has been made in view of the conventional problems described above. The subject of the present invention is the walking speed, walking distance, exercise intensity calculated from the measured number of steps and the height or weight of the set pedometer user regardless of the principle of the pendulum type or acceleration sensor type pedometer Or to provide pedometer technology with accurate walking-related information such as calories burned, or pedometer with practical accuracy and simple structure and economically cheap. is there. The practical accuracy will be described later.
上記の課題を解決するために、本発明に係わる歩数計は、歩行速度と運動強度の演算に以下の特徴的な構成を採用し、算出された歩行速度または運動強度に基づいて歩行距離や消費カロリーなどを算出して、歩数と併せて表示提供する構成とする。 In order to solve the above-mentioned problems, the pedometer according to the present invention adopts the following characteristic configuration for the calculation of walking speed and exercise intensity, and the walking distance and consumption based on the calculated walking speed or exercise intensity. Calories and the like are calculated and displayed together with the number of steps.
請求項１による、歩行速度演算の構成に関しては、歩数計利用者の身長を設定する設定手段と、歩数計利用者の歩行時の歩数を計測する歩数計測手段と、前記歩数計測手段で計測される単位時間当たりの歩数を歩行ピッチとして算出し、前記歩行ピッチを歩行ピッチに関する補正関数の式に代入して得られる結果と前記設定手段に設定された身長とに基づいて歩行速度を算出する演算手段とを備える。そして、歩行特性を定める歩行ピッチに関する特性区分線形関数と前記特性区分線形関数に歩行ピッチを乗じて得られる関数を特性区分二次関数とし、前記補正関数は、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間で前記特性区分二次関数に回帰分析を施して得られる１つの回帰直線、もしくは前記特性区分線形関数の複数の区間の少なくとも１つを含む区間を複数に分割した再分割区間ごとに前記特性区分二次関数に回帰分析を施して得られる前記再分割区間ごとの回帰直線、もしくは前記特性区分二次関数、のいずれかであり、かつ、前記特性区分線形関数は、歩行ピッチに対する歩幅の身長に対する割合の変化を前記変化に応じて複数に区分した区間ごとに歩行ピッチに関する一次関数で表した区分線形関数であり、かつ、前記特性区分二次関数を前記補正関数とする場合にあっては、前記特性区分線形関数の前記変化に応じて複数に区分した区間数は３であることを特徴とする。 The walking speed calculation configuration according to claim 1 is measured by the setting means for setting the height of the pedometer user, the step count measuring means for measuring the number of steps when the pedometer user walks, and the step count measuring means. An operation for calculating a walking speed based on a result obtained by substituting the walking pitch into a formula of a correction function relating to the walking pitch and a height set in the setting means. Means. A characteristic piecewise linear function relating to the walking pitch that defines the walking characteristics and a function obtained by multiplying the characteristic piecewise linear function by the walking pitch is a characteristic piecewise quadratic function, and the correction function includes a plurality of sections of the characteristic piecewise linear function. A regression line obtained by performing regression analysis on the characteristic segmented quadratic function in an interval including at least one of the above or a segment including at least one of the plurality of segments of the characteristic segmented linear function into a plurality of segments. It is either a regression line for each subdivision section obtained by performing regression analysis on the characteristic section quadratic function for each divided section, or the characteristic section quadratic function, and the characteristic section linear function is: It is a piecewise linear function that expresses a change in the ratio of the stride height to the walking pitch as a linear function related to the walking pitch for each section divided into a plurality according to the change. And there the characteristic segment quadratic function when said correction function is characterized in that the number of sections obtained by dividing the plurality is 3 in response to the change in the characteristics piecewise linear function.
これにより、歩行特性を定めた特性区分線形関数とこれに基づく特性区分二次関数とに基づいて、歩行速度の演算式を最も単純化でき、歩行速度を最も簡単に算出できる、もしくは演算式をより単純化でき、歩行速度をより簡単に算出できる、もしくは演算式を単純化せずにそのまま用いることができ、この場合は区関数が３であり歩行速度を比較的簡単に算出できることになる。単純化の程度に応じて演算式の単純化による誤差を少なくすることが出来る。特性区分線形関数に歩行特性の代表値を反映させた場合、歩数計利用者の歩行特性との乖離が大きくなければ、歩行速度を実用上の正確で簡単に算出できることになる。このことについては、後に詳しく述べる。 Based on the characteristic segmentation linear function that defines the walking characteristics and the characteristic segmentation quadratic function based on this, it is possible to simplify the calculation formula of the walking speed most easily, or to calculate the walking speed most easily, or The walking speed can be calculated more easily, or can be used as it is without simplifying the arithmetic expression. In this case, the section function is 3, and the walking speed can be calculated relatively easily. The error due to simplification of the arithmetic expression can be reduced according to the degree of simplification. When the representative value of the walking characteristic is reflected in the characteristic piecewise linear function, the walking speed can be calculated accurately and easily in practical use unless the difference from the walking characteristic of the pedometer user is large. This will be described in detail later.
請求項２による、歩行速度演算の構成に関しては、歩数計利用者の身長を設定する設定手段と、前記歩数計利用者の歩行時の歩数を計測する歩数計測手段と、前記歩数計測手段で計測される単位時間当たりの歩数を歩行ピッチとして算出し、前記歩行ピッチを歩行ピッチに関する補正関数の式に代入して得られる結果と前記設定手段に設定された身長とに基づいて歩行速度を算出する演算手段とを備える。そして、前記補正関数の特性を定めるパラメータが前記設定手段に設定できる。前記歩数計利用者の歩行特性を定める歩行ピッチに関する特性区分線形関数と前記特性区分線形関数に歩行ピッチを乗じて得られる関数を特性区分二次関数とし、前記パラメータは、前記補正関数が直線として定められる場合にあっては、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間で前記特性区分二次関数に回帰分析を施して得られる１つの回帰直線の傾きおよび切片、もしくは前記補正関数が区分線形関数として定められる場合にあっては、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間を複数に分割した再分割区間ごとに前記特性区分二次関数に回帰分析を施して得られる前記再分割区間ごとの回帰直線の傾きおよび切片、並びに隣接区間との区分点、もしくは前記補正関数が前記特性区分二次関数となる場合にあっては、前記特性区分線形関数の区間ごとの直線の傾きおよび切片、並びに隣接区間との区分点、のいずれかであり、かつ、前記特性区分線形関数は、前記歩数計利用者の歩行ピッチに対する歩幅の身長に対する割合の変化を前記変化に応じて複数に区分した区間ごとに歩行ピッチに関する一次関数で表した区分線形関数であり、かつ、前記補正関数が前記特性区分二次関数となる場合にあっては、前記特性区分線形関数の前記変化に応じて複数に区分した区間数は３であることを特徴とする。 With regard to the configuration of the walking speed calculation according to claim 2, the setting means for setting the height of the pedometer user, the step count measuring means for measuring the number of steps when the pedometer user walks, and the step count measuring means The number of steps per unit time is calculated as the walking pitch, and the walking speed is calculated based on the result obtained by substituting the walking pitch into the correction function formula for the walking pitch and the height set in the setting means. And an arithmetic means. And the parameter which determines the characteristic of the said correction function can be set to the said setting means. A characteristic piecewise linear function relating to the walking pitch that determines the walking characteristics of the pedometer user and a function obtained by multiplying the characteristic piecewise linear function by the walking pitch is a characteristic piecewise quadratic function, and the parameter is such that the correction function is a straight line If determined, the slope and intercept of one regression line obtained by performing regression analysis on the characteristic segmented quadratic function in an interval including at least one of the plurality of intervals of the characteristic segmented linear function, or When the correction function is defined as a piecewise linear function, regression analysis is performed on the characteristic piecewise quadratic function for each subdivision section obtained by dividing a section including at least one of the plurality of sections of the characteristic piecewise linear function into a plurality of sections. The slope and intercept of the regression line for each of the subdivision sections obtained by applying the segmentation points with the adjacent sections, or the correction function The characteristic piecewise linear function is any one of the slope and intercept of the straight line for each section, and the sectioning point with the adjacent section, and the characteristic piecewise linear function uses the pedometer A change in the ratio of the stride height to the person's walking pitch is a piecewise linear function expressed by a linear function related to the walking pitch for each section divided into a plurality according to the change, and the correction function is the characteristic classification quadratic In the case of a function, the number of sections divided into a plurality according to the change of the characteristic piecewise linear function is three.
これにより、歩数計利用者の歩行特性値をパラメータとして設定できることになる。さらに、歩行速度の演算に係る補正関数が、最も単純な直線とされる場合は、歩行速度を最も簡単に算出できる、もしくはより単純な区分線形関数とされる場合は、歩行速度をより簡単に算出できる、もしくは単純化されずに特性区分二次関数となる場合は、区関数が３であり歩行速度を比較的簡単に算出できることになる。歩数計利用者の歩行特性値をパラメータとして設定できるため、歩行特性の乖離による誤差はなく、歩行速度を、演算式の単純化による誤差内で正確に求めることが出来る。このことについては、歩数計利用者の歩行特性値をパラメータとして設定する方法などと共に後述する。 Thereby, the walking characteristic value of the pedometer user can be set as a parameter. Furthermore, when the correction function for calculating the walking speed is the simplest straight line, the walking speed can be calculated most easily, or when the correction function is a simpler piecewise linear function, the walking speed is more easily calculated. When it can be calculated or becomes a quadratic function of characteristic division without being simplified, the division function is 3, and the walking speed can be calculated relatively easily. Since the walking characteristic value of the pedometer user can be set as a parameter, there is no error due to the deviation of the walking characteristic, and the walking speed can be accurately obtained within the error due to simplification of the arithmetic expression. This will be described later together with a method of setting a pedometer user's walking characteristic value as a parameter.
請求項３による運動強度演算の構成に関しては、請求項１に記載の歩行速度演算の構成に、あるいは、請求項４による運動強度演算の構成に関しては、請求項２に記載の歩行速度演算の構成に、それぞれ、さらに以下の特徴的な構成を備える。即ち、前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出する。そして、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であることを特徴とする。 With regard to the configuration of the exercise intensity calculation according to claim 3, the configuration of the walking speed calculation according to claim 1, or the configuration of the exercise intensity calculation according to claim 4, the configuration of the walking speed calculation according to claim 2. Further, each has the following characteristic configuration. That is, the calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed as an exercise intensity. The exercise intensity function is a function obtained by performing the first operation or the second operation on the current piecewise linear function in which the relationship of the exercise intensity to the walking speed is expressed, and the first operation is: An operation of replacing the current piecewise linear function section with a new new piecewise linear function comprising a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function for each section divided into a plurality of sections including at least one. And the second operation includes a continuous section of the current piecewise linear function or the new piecewise linear function, and when the slope of the linear function in the continuous section is gradually non-decreasing, the continuous section of the linear function is Replaced with a new one section as the maximum value function for selecting the maximum value of the function value, and replaced with a new single section as the minimum value function for selecting the minimum value of the function value when gradually increasing, But Time, wherein the subtracting from the continuous sections one section is an operation of repeating the second operation to become impossible replacement.
これにより、歩行速度と運動強度の関係を表した運動強度の演算式に対し、正確さの要求に応じて、第１の操作による演算式の単純化、または第２の操作による演算過程の単純化を行うことが出来る。正確さが求められる場合は、第１の操作は限定することが望ましい。また、第２の操作では誤差は生じない。求められた歩行速度を、第１または第２の操作で置き換えて得られた運動強度関数に適用して、運動強度が演算される。運動強度の演算結果には歩行速度の演算誤差も含まれるため総合誤差の検証が必要となる。詳細は後述する。 As a result, the calculation formula for the exercise intensity representing the relationship between the walking speed and the exercise intensity is simplified according to the request for accuracy, or the calculation process by the second operation is simplified. Can be made. If accuracy is required, it is desirable to limit the first operation. Further, no error occurs in the second operation. The exercise intensity is calculated by applying the obtained walking speed to the exercise intensity function obtained by replacing the first or second operation. Since the calculation result of exercise intensity includes a calculation error of walking speed, it is necessary to verify the total error. Details will be described later.
請求項５による運動強度演算の構成、および歩行速度、歩行距離、運動強度または消費カロリーなどの歩行関連情報を演算して歩数と併せて表示提供する構成に関しては、請求項１に記載の歩行速度演算の構成に、あるいは、請求項６による運動強度演算の構成、および歩行速度、歩行距離、運動強度または消費カロリーなどの歩行関連情報を演算して歩数と併せて表示提供する構成に関しては、請求項２に記載の歩行速度演算の構成に、それぞれ、さらに以下の特徴的な構成を備える。即ち、前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出し、前記歩行速度と前記運動強度とに歩行時間を乗じて歩行距離とエクササイズとを算出し、前記エクササイズに基礎代謝量を乗じて消費カロリーを算出する。加えて、前記歩数計測手段で計測された歩数と併せて前記演算手段で算出された歩行速度、歩行距離、運動強度、エクササイズ、または消費カロリーを表示する表示手段とを備える。そして、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であることを特徴とする。そして、前記基礎代謝量は、前記設定手段に設定された身長に加えて設定された体重の値、もしくは前記体重に係数１．０５を乗じた値、もしくは前記設定手段にさらに加えて設定された性別と年齢および前記身長と前記体重とから計算される値、のいずれかであることを特徴とする。 Regarding the configuration of the exercise intensity calculation according to claim 5 and the configuration for calculating and providing walking-related information such as walking speed, walking distance, exercise intensity or calorie consumption and displaying it together with the number of steps, the walking speed according to claim 1 Regarding the configuration of the calculation, or the configuration of the exercise intensity calculation according to claim 6 and the configuration of calculating the walking related information such as the walking speed, the walking distance, the exercise intensity, or the calorie consumption and providing the display together with the number of steps. The walking speed calculation configuration according to Item 2 further includes the following characteristic configuration. That is, the calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, and multiplies the walking speed and the exercise intensity by a walking time to calculate a walking distance. And the exercise, and the calorie consumption is calculated by multiplying the exercise by the basal metabolic rate. In addition, display means for displaying the walking speed, walking distance, exercise intensity, exercise, or calorie consumption calculated by the calculating means together with the number of steps measured by the step counting means. The exercise intensity function is a function obtained by performing the first operation or the second operation on the current piecewise linear function in which the relationship of the exercise intensity to the walking speed is expressed, and the first operation is: An operation of replacing the current piecewise linear function section with a new new piecewise linear function comprising a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function for each section divided into a plurality of sections including at least one. And the second operation includes a continuous section of the current piecewise linear function or the new piecewise linear function, and when the slope of the linear function in the continuous section is gradually non-decreasing, the continuous section of the linear function is Replaced with a new one section as the maximum value function for selecting the maximum value of the function value, and replaced with a new single section as the minimum value function for selecting the minimum value of the function value when gradually increasing, But Time, wherein the subtracting from the continuous sections one section is an operation of repeating the second operation to become impossible replacement. The basal metabolic rate is set in addition to the height set in the setting means, the weight value set in the setting means, or a value obtained by multiplying the weight by a factor of 1.05, or further set in the setting means. It is one of a value calculated from sex, age, and height and weight.
これにより、得られた歩行速度から、要求の正確さに応じた運動強度が算出できる。これら２量から歩行距離、消費カロリーなどを演算して、歩行速度、歩行距離、運動強度または消費カロリーなどの歩行関連情報が歩数と併せて表示できる。歩行関連情報の値には、これら２量の正確さがそのまま反映される。 Thereby, the exercise intensity according to the required accuracy can be calculated from the obtained walking speed. The walking distance, calorie consumption, and the like are calculated from these two quantities, and walking related information such as walking speed, walking distance, exercise intensity, or calorie consumption can be displayed together with the number of steps. The accuracy of these two quantities is directly reflected in the value of the walking related information.
以上に課題を解決するための手段について説明した。これらの手段を講ずることにより、歩行速度、運動強度、およびその他の歩行関連情報を、以下の通り、所望の正確さで求めることが出来る。後述するように、中間ピッチ区間と歩幅変化の少なくなる下方ピッチ区間および上方ピッチ区間における歩行特性が区分線形関数で表現できることに着目した。この区分線形関数に基づいて導かれる歩行速度の演算式を、回帰分析により実用上の正確さを保って単純化した演算式で、歩行速度をより簡単に求めることが出来る。また、歩行速度に対する運動強度の関係を、公知の数値に基づいて区分線形関数で表し、これを回帰分析により実用上の正確さを保って単純化した演算式で、運動強度をより簡単に求めることが出来る。単純化は、要求される正確さの程度に応じてすることができる。また、単純化を行わずに、元の区分線形関数をそのまま用いることもできる。この場合は、演算式の単純化による誤差はなく、当然、正確さは単純化した演算式より優れる。さらに、歩行特性が設定できる構成は、歩行特性が代表値に固定される構成よりも、歩数計利用者の歩行特性が直接に反映されて、正確さは大幅に増す。以上の手段を講ずることにより、本発明の課題は解決され、歩数と併せて提供される歩行速度、歩行距離、運動強度、または消費カロリーなどの歩行関連情報が、正確さをもった、あるいは、実用上の正確さをもち、かつ、構造が単純で経済的に安価な歩数計を提供出来ることになる。 The means for solving the problem has been described above. By taking these measures, walking speed, exercise intensity, and other walking related information can be obtained with desired accuracy as follows. As will be described later, attention was paid to the fact that the walking characteristics in the intermediate pitch interval, the lower pitch interval and the upper pitch interval in which the step change is reduced can be expressed by a piecewise linear function. The walking speed can be obtained more easily by calculating the walking speed calculated based on the piecewise linear function with a regression analysis while maintaining practical accuracy. In addition, the relationship of exercise intensity to walking speed is expressed as a piecewise linear function based on known numerical values, and this is simplified by maintaining the practical accuracy by regression analysis. I can do it. Simplification can be made depending on the degree of accuracy required. Further, the original piecewise linear function can be used as it is without simplification. In this case, there is no error due to simplification of the arithmetic expression, and naturally the accuracy is superior to the simplified arithmetic expression. Furthermore, the configuration in which the walking characteristics can be set has a greater accuracy because the walking characteristics of the pedometer user are directly reflected than the configuration in which the walking characteristics are fixed to the representative value. By taking the above measures, the problem of the present invention is solved, and walking-related information such as walking speed, walking distance, exercise intensity, or calorie consumption provided together with the number of steps has accuracy, or It is possible to provide a pedometer that has practical accuracy, has a simple structure, and is economically inexpensive.
図１は歩行速度と運動強度の関係を表すデータとグラフである。FIG. 1 is a data and graph showing the relationship between walking speed and exercise intensity. 図２は歩行実験結果を表すデータとグラフである。FIG. 2 is a graph and data representing the results of the walking experiment. 図３は本発明に係わる実施例での歩数計の構成を表すブロック図である。FIG. 3 is a block diagram showing the configuration of the pedometer in the embodiment according to the present invention.
計測された歩数から歩行速度を、歩行速度から＜エクササイズガイド２００６＞またはその他の公知の数値に合った運動強度を、いかにして正確に、あるいは実用上の正確さで求めるかが本発明の重要な技術であり、後者の運動強度から詳述する。詳述する前に実用上の正確さについて言及する。 The importance of the present invention is how to determine the walking speed from the measured number of steps and the exercise intensity that matches the <Exercise Guide 2006> or other known values from the walking speed with accuracy or practical accuracy. This technique will be described in detail from the latter exercise intensity. Before we elaborate, we refer to practical accuracy.
歩数計で計測される歩数の誤差はＪＩＳ規格で±３％と規定されている。歩数計の応動範囲内（後述する）では、歩数計利用者の歩行特性（歩き方）にほとんど影響されることなく、規格誤差内で正確な歩数値が得られる。一方、歩行関連情報は、歩数計利用者の身長または体重などの身体データ、歩幅または歩行ピッチなどが関係する歩行特性に大きく影響されるため、規格で誤差を規定することは容易ではない。しかし、歩数と併せて提供される消費カロリーなどの規格に準拠しない歩行関連情報が、歩数計製造者が独自に開発した演算方式であることを理由に、公知の数値とかけ離れていることは問題である。歩数計利用者は、歩行関連情報が公知の数値と概ね合っていると信じて使っているはずである。そこで、歩数の計測誤差（±３％）を含まない、本発明の演算方式による歩行関連情報単独の正確さを、±５～１０％程度の誤差とする。この誤差を評価するための基準値は、公知の数値に基づいて本発明で導き出した関数に基づく値である。本発明ではこの誤差を、実用上の誤差、あるいは、実用上の正確さと呼ぶことにする。 The error in the number of steps measured by the pedometer is defined as ± 3% in the JIS standard. Within the response range of the pedometer (described later), an accurate step value within the standard error can be obtained without being substantially affected by the walking characteristics (how to walk) of the pedometer user. On the other hand, since the walking related information is greatly influenced by the walking characteristics related to the body data such as the height or weight of the pedometer user, the stride or the walking pitch, it is not easy to define an error in the standard. However, it is problematic that walking-related information that does not conform to standards such as calories consumed provided with the number of steps is a calculation method originally developed by the pedometer manufacturer, and is far from known numbers. It is. Pedometer users should believe and use gait-related information to generally match known values. Therefore, the accuracy of walking related information alone according to the calculation method of the present invention, which does not include a step count measurement error (± 3%), is set to an error of about ± 5 to 10%. The reference value for evaluating this error is a value based on a function derived by the present invention based on a known numerical value. In the present invention, this error is referred to as practical error or practical accuracy.
＜エクササイズガイド２００６＞には、１０７ｍ／分の“かなり速歩”を超える歩行に関する歩行速度と運動強度の関係は示されていない。非特許文献１には、さまざまな身体活動に対する運動強度、即ち、メッツ値が示されている。歩行運動に関しては次のデータが示されている。このメッツ値は安静時の１メッツ分を含む値である。
５３ｍ／分　（３．２ｋｍ／時）平地、遅い　　　　　　　　　　　　２．５メッツ
６７ｍ／分　（４．０ｋｍ／時）硬く安定した平地　　　　　　　　　３．０メッツ
８０ｍ／分　（４．８ｋｍ／時）平地、適度な速度　　　　　　　　　３．３メッツ
９３ｍ／分　（５．６ｋｍ／時）平地、運動として、小気味よい速度　３．８メッツ
１０７ｍ／分（６．４ｋｍ／時）平地、小気味よい速度　　　　　　　５．０メッツ
１２０ｍ／分（７．２ｋｍ／時）平地、とてもきびきびとした速度　　６．３メッツ
１３３ｍ／分（８．０ｋｍ／時）　　　　　　　　　　　　　　　　　８．０メッツ <Exercise Guide 2006> does not show the relationship between the walking speed and the exercise intensity related to walking exceeding “much fast walking” of 107 m / min. Non-Patent Document 1 shows exercise intensity, that is, Met's value for various physical activities. The following data are shown for walking motion. This mets value is a value including one mets at rest.
53 m / min (3.2 km / h) flat, slow 2.5 mets 67 m / min (4.0 km / h) hard and stable flat 3.0 mets 80 m / min (4.8 km / h) flat, moderate speed 3.3 mets 93m / min (5.6km / h) flat ground, as a motion, refreshing speed 3.8 mets 107m / min (6.4km / hr) flat, refreshing speed 5.0 mets 120m / min (7.2km) / Hour) Flat land, very crisp speed 6.3 mets 133m / min (8.0km / hr) 8.0 mets
上記データは、＜エクササイズガイド２００６＞のデータおよびインターネット上の多くの関連情報のデータとよく合う。＜エクササイズガイド２００６＞は、改定作業中であると聞く。また、非特許文献１は最近改定された。これらを考えて、非特許文献１の改訂版である非特許文献２の以下に示すデータ（改定データと呼ぶ）を、本発明の歩行速度と運動強度の関係の根拠とする。＜エクササイズガイド２００６＞のデータ、非特許文献１のデータ、および非特許文献２のデータは権威ある公的機関から発表されている公知のデータであり、根拠とするには十分である。この改定データのメッツ値も安静時の１メッツ分を含む値である。
５３ｍ／分　（３．２ｋｍ／時）ゆっくり、平らで固い地面　　　　　　２．８メッツ
６７ｍ／分　（４．０ｋｍ／時）平らで固い地面　　　　　　　　　　　３．０メッツ
８０ｍ／分　（４．８ｋｍ／時）ほどほどの速度、平らで固い地面　　　３．５メッツ
９３ｍ／分　（５．６ｋｍ／時）速い、平らで固い地面、運動目的で歩く４．３メッツ
１０７ｍ／分（６．４ｋｍ／時）平らで固い地面、とても速い　　　　　５．０メッツ
１２０ｍ／分（７．２ｋｍ／時）平らで固い地面、極めて速い　　　　　７．０メッツ
１３３ｍ／分（８．０ｋｍ／時）平らで固い地面　　　　　　　　　　　８．３メッツ The above data fits well with the data from the <Exercise Guide 2006> and a lot of relevant information on the Internet. <Exercise Guide 2006> hears that it is being revised. Non-patent document 1 has been recently revised. Considering these, the following data (referred to as revised data) of Non-Patent Document 2, which is a revised version of Non-Patent Document 1, is used as a basis for the relationship between walking speed and exercise intensity of the present invention. The data of <Exercise Guide 2006>, the data of Non-Patent Document 1, and the data of Non-Patent Document 2 are well-known data published by an authoritative public institution and are sufficient for the basis. The Mets value of the revised data is also a value including one Mets at rest.
53 m / min (3.2 km / h) Slow, flat and hard ground 2.8 metres 67 m / min (4.0 km / hr) Flat and hard ground 3.0 metres 80 m / min (4.8 km / hr) Speed, flat and solid ground 3.5 mets 93m / min (5.6km / h) fast, flat and solid ground, walking for exercise purpose 4.3 mets 107m / min (6.4km / h) flat and hard ground, Very fast 5.0 metres 120m / min (7.2km / h) flat and hard ground, very fast 7.0 mets 133m / min (8.0km / hr) flat and hard ground 8.3 mets
改定データのメッツ値は、改定前のメッツ値から、速度の遅い方から順に、０．３／０／０．２／０．５／０／０．７／０．３メッツ上方修正されている。歩行速度に対してメッツ値が最大で０．５／３．８≒１３％増加している。しかし、この上方修正によるメッツ値が増加したことで、＜エクササイズガイド２００６＞の内容を根拠として先に説明した、歩数計の消費カロリーの過大表示の問題や特許文献調査で見つかった先行技術の問題が解消されることはない。 The Mets value of the revised data has been revised upward by 0.3 / 0 / 0.2 / 0.5 / 0 / 0.7 / 0.3 Mets in order from the slower speed from the Mets value before the revision. . The Mets value increases by a maximum of 0.5 / 3.8≈13% with respect to the walking speed. However, due to the increase in the Met's value due to this upward revision, the problem of the excessive display of the calorie consumption of the pedometer and the problem of the prior art found in the patent literature survey described above based on the contents of the <Exercise Guide 2006> Will not be resolved.
図１は、横軸を歩行速度（ｋｍ／時）、縦軸を運動強度（メッツ）とし、改定データをプロットして直線で結んだグラフ、所謂、区分線形関数である。歩行速度と運動強度の関係は、区分的に二次関数に近いと考えられる。しかし、この関数を決定し運動強度を求めることは複雑すぎる。そこで、この連続した区分線形関数を、本発明の歩行速度と運動強度の関係を表す基本（基準）の関数とする。図１から分かるように区間の数は少なくない。従って、この区分線形関数を用いることは実用上まったく問題ないと考えられる。上で、“連続した”と付けた理由は、後述する不連続な区分線形関数と区別するためである。 FIG. 1 is a so-called piecewise linear function in which the horizontal axis is walking speed (km / hour), the vertical axis is exercise intensity (mets), and the revised data is plotted and connected by a straight line. The relationship between walking speed and exercise intensity is considered to be close to a quadratic function piecewise. However, determining this function and determining the exercise intensity is too complicated. Therefore, this continuous piecewise linear function is used as a basic (reference) function representing the relationship between walking speed and exercise intensity according to the present invention. As can be seen from FIG. 1, the number of sections is not small. Therefore, it is considered that there is no problem in practical use of this piecewise linear function. The reason why “continuous” is given above is to distinguish it from a discontinuous piecewise linear function described later.
歩行速度をこの区分線形関数の式に代入することで、運動強度を、本発明の課題の１つである、正確さをもって、求めることができる。具体的には、最初に歩行速度が６つの区間のいずれにあるかを判定する。そして、その区間の直線（線形関数）の式に歩行速度を代入して運動強度を求める。この普通の演算手順は、区間と同数の６つの直線と、最大３回の区間判定を必要とする。区間の数が少なくなれば、手順はより単純になることは明らかである。本発明の課題のもう１つは、実用上の正確さをもち、かつ構造が単純で経済的に安価なことである。手順の単純化、換言すると演算構造の単純化は、後者の課題解決に有効な手段である。区間を少なくして単純化する方法を説明する前に、区間判定の回数を減らす考え方を説明する。 By substituting the walking speed into the equation of the piecewise linear function, the exercise intensity can be obtained with accuracy, which is one of the problems of the present invention. Specifically, it is first determined which of the six sections the walking speed is in. Then, the exercise intensity is obtained by substituting the walking speed into the equation of the straight line (linear function) of the section. This ordinary calculation procedure requires the same number of six straight lines as a section and a maximum of three section determinations. Obviously, the procedure becomes simpler if the number of intervals is reduced. Another problem of the present invention is that it has practical accuracy, has a simple structure, and is economically inexpensive. Simplification of the procedure, in other words, simplification of the operation structure is an effective means for solving the latter problem. Before explaining the method of simplifying by reducing the number of sections, the concept of reducing the number of section determinations will be described.
区間判定は、分岐したパスを、歩行速度の大小比較をしながら目的の区間にたどり着くといった、煩雑な過程である。区間判定の回数を減らすことで過程は単純になる。連続した区分線形関数は、連続した区間で、区間ごとの直線の傾きが漸次非減少であれば、その連続した区間で凹特性を示し、漸次非増加であれば、凸特性を示す。そして、連続した区間での区分線形関数の関数値の演算には、連続した区間で凹特性であれば、その区間ごとの直線式の値の最大値を選ぶ関数（本発明では最大値関数と呼ぶ）を用いることが出来る。また、連続した区間で凸特性であれば、その区間ごとの直線式の値の最小値を選ぶ関数（本発明では最小値関数と呼ぶ）を用いることが出来る。従って、連続した区間では、さらに区間判定を行う必要がない。このことは、容易に理解できると思われるので、詳しく説明しない。 The section determination is a complicated process in which the branched path is reached to the target section while comparing the walking speed. The process is simplified by reducing the number of interval judgments. A continuous piecewise linear function shows a concave characteristic in a continuous section if the slope of the straight line for each section is gradually non-decreasing, and shows a convex characteristic if the slope is non-increasing gradually. Then, in the calculation of the function value of the piecewise linear function in the continuous interval, if the concave characteristic is in the continuous interval, a function that selects the maximum value of the linear expression value for each interval (in the present invention, the maximum value function and Can be used). In addition, if the convex characteristic is in a continuous section, a function for selecting the minimum value of the linear expression for each section (referred to as a minimum value function in the present invention) can be used. Therefore, it is not necessary to perform further section determination in continuous sections. This is likely to be easily understood and will not be described in detail.
図１の６つの速度区間を速度の遅い方から、第１区間、第２区間・・・第６区間と呼ぶことにする。図１の区分線形関数は、第１区間から第３区間までは凹特性、第４区間から第５区間までは凹特性であり、第６区間は、便宜上、凹特性もしくは凸特性として扱っても良い。あるいは、第１区間から第２区間までは凹特性、第３区間から第４区間までは凸特性、そして第５区間から第６区間までは凸特性である。いずれの場合も、区間判定の回数は２回となり、特性に応じて最大値関数、もしくは最小値関数を用いることが出来る。運動強度を求めるこの演算は、誤差を伴うことなく、普通の演算手順よりは単純となる。次に、区間の数を少なくすることにより、誤差は発生するが、手順をさらに単純化する方法を説明する。 The six speed sections in FIG. 1 are referred to as a first section, a second section,. The piecewise linear function of FIG. 1 has a concave characteristic from the first section to the third section, a concave characteristic from the fourth section to the fifth section, and the sixth section may be treated as a concave characteristic or a convex characteristic for convenience. good. Alternatively, the first section to the second section are concave characteristics, the third section to the fourth section are convex characteristics, and the fifth section to the sixth section are convex characteristics. In either case, the number of section determinations is two, and the maximum value function or the minimum value function can be used depending on the characteristics. This calculation for determining the exercise intensity is simpler than a normal calculation procedure without error. Next, a method for further simplifying the procedure will be described although an error occurs by reducing the number of sections.
図１で、連続する第３区間と第４区間の２つの直線の傾きはわずかに異なるが、この２つの区間を１つの区間と１つの直線にまとめても誤差の点で問題はないようである。図１で、第１区間と第２区間、あるいは、第５区間と第６区間を１つにまとめると、多少誤差が発生するようである。しかし、これが実用上の誤差であれば、１つにまとめることで、手順がさらに単純化できる。 In FIG. 1, the slopes of the two straight lines in the third and fourth consecutive sections are slightly different, but it seems that there is no problem in terms of error even if these two sections are combined into one section and one straight line. is there. In FIG. 1, when the first section and the second section, or the fifth section and the sixth section are combined into one, an error seems to occur to some extent. However, if this is a practical error, the procedure can be further simplified by combining them into one.
手順の単純化のために区間の数を少なくするには、連続する２つ以上の区間を１つの区間にまとめて新たな区間とする方法、あるいは、元の６つの区間に関係なく、歩行速度区間の一部あるいは全部を、いくつかに分割して新たな区間を作る方法もある。新たな区間で１つの直線を定めるには、周知の最小二乗法による回帰分析を行って回帰直線を得る方法が、単純明快で優れている。以下に具体的な方法を詳しく説明する。 To reduce the number of sections in order to simplify the procedure, a method of combining two or more consecutive sections into one section to make a new section, or walking speed regardless of the original six sections. There is also a method of creating a new section by dividing a part or all of the section into several sections. In order to define one straight line in a new section, a method of obtaining a regression line by performing a regression analysis by a known least square method is simple and clear. A specific method will be described in detail below.
ある区間で定義された関数に対して、その区間で最小二乗法を用いた回帰分析により、解析的に回帰直線を求めることができる。簡単化のため、連続する等間隔の２つの区間（ｖ１，ｖ２）、（ｖ２，ｖ３）について説明する。各区間の直線の傾きと切片を、（ａ１，ｂ１）、（ａ２，ｂ２）とする。この時、１つにまとめた区間（ｖ１，ｖ３）で回帰分析を行って得られる１つの回帰直線の傾きと切片（α，β）は、次の二元連立一次方程式の解として得られる。証明は省く。
２・（Ａ＋Ｂ）・α＋３・（Ｃ＋Ｄ）・β＝２・（ａ１・Ａ＋ａ２・Ｂ）＋
３・（ｂ１・Ｃ＋ｂ２・Ｄ）
（Ｃ＋Ｄ）・α＋４・β＝（ａ１・Ｃ＋ａ２・Ｄ）＋２・（ｂ１＋ｂ２）
ここで、Ａ、Ｂ、Ｃ、およびＤは次の通りである。
Ａ＝ｖ１・ｖ１＋ｖ１・ｖ２＋ｖ２・ｖ２、Ｃ=ｖ１＋ｖ２
Ｂ＝ｖ２・ｖ２＋ｖ２・ｖ３＋ｖ３・ｖ３、Ｄ=ｖ２＋ｖ３ For a function defined in a certain section, a regression line can be obtained analytically by regression analysis using the least squares method in that section. For the sake of simplification, a description will be given of two consecutive equally spaced intervals (v1, v2) and (v2, v3). Let the slope and intercept of the straight line in each section be (a1, b1) and (a2, b2). At this time, the slope and intercept (α, β) of one regression line obtained by performing the regression analysis in a single section (v1, v3) are obtained as solutions of the following binary simultaneous linear equations. Omit proof.
2 ・ (A + B) ・ α + 3 ・ (C + D) ・ β = 2 ・ (a1 ・ A + a2 ・ B) +
3 ・ (b1 ・ C + b2 ・ D)
(C + D) · α + 4 · β = (a1 · C + a2 · D) + 2 · (b1 + b2)
Here, A, B, C, and D are as follows.
A = v1 · v1 + v1 · v2 + v2 · v2, C = v1 + v2
B = v2 / v2 + v2 / v3 + v3 / v3, D = v2 + v3
１つにまとめた区間を、例えば、第１∨２区間と表す。上記の解析結果を、図１の第３区間と第４区間に適用すると、第３∨４区間の回帰直線の傾きと切片は（０．９３７５，－０．９７５）となる。この近似値（０．９４，－０．９８）を用いて元の直線の式の値と比較すると、誤差は１％未満であることが確認でき、実用上の誤差としては全く問題ない。 The section put together into 1 is expressed as the 1st 2nd section, for example. When the above analysis results are applied to the third and fourth intervals in FIG. 1, the slope and intercept of the regression line in the third to fourth intervals are (0.9375, −0.975). When this approximate value (0.94, −0.98) is used and compared with the value of the original linear equation, it can be confirmed that the error is less than 1%, and there is no problem as a practical error.
第３∨４区間の回帰直線は、隣接の第２区間および第５区間の境界で厳密には不連続となり、５つの区間の５つの直線は不連続な区分線形関数となる。不連続点での誤差が１％未満であるため、５つの区間で連続な区分線形関数とみなすことが出来る。さらに、第１区間、第２区間、第３∨４区間、および第５区間の直線の傾きは漸次増加（漸次非減少）であることから、これら４つの区間ではこの関数は凹特性とみなすことが出来る。そして、凹特性を利用して、これら４つの区間ではさらに区間判定を行わず、最大値関数を用いることが出来る。具体的には、歩行速度が第６区間にあるか否かの１回の判定を行い、第６区間にあれば、第６区間の直線の式に歩行速度を代入して運動強度を求める。さもなければ、第１区間、第２区間、第３∨４区間、および第５区間の直線の式に歩行速度を代入し、それらの最大値を運動強度として求める。もちろん、この４つの区間に対しても、分岐をたどって区間判定を忠実に行い、たどり着いた区間の直線式で代入計算する方法でもよい。いずれの方法を選択するかの判断は、例えば、プログラム設計時に出くわすであろう。 Strictly speaking, the regression line in the third to fourth section becomes discontinuous at the boundary between the adjacent second and fifth sections, and the five straight lines in the five sections become discontinuous piecewise linear functions. Since the error at the discontinuity is less than 1%, it can be regarded as a piecewise linear function continuous in five sections. Furthermore, since the slopes of the straight lines in the first section, the second section, the third ∨4 section, and the fifth section are gradually increasing (gradual non-decreasing), the function is regarded as a concave characteristic in these four sections. I can do it. Then, using the concave characteristic, it is possible to use the maximum value function without further section determination in these four sections. Specifically, it is determined once whether or not the walking speed is in the sixth section, and if it is in the sixth section, the exercise speed is obtained by substituting the walking speed into the straight line expression of the sixth section. Otherwise, the walking speed is substituted into the straight line expressions of the first section, the second section, the third base 4 section, and the fifth section, and the maximum value thereof is obtained as the exercise intensity. Of course, it is also possible to use a method in which branch determination is performed faithfully for these four sections, and substitution calculation is performed using the linear expression of the section that has been reached. The determination of which method to select will be encountered during program design, for example.
上記の方法は、先に述べた普通の手順と比べて、誤差１％未満で単純化された演算方法である。誤差が多少増加するが、さらに単純化された演算方法について以下に説明する。この方法は、区間の数をさらに少なくして、かつ、区間判定が不要な演算方法である。 The above method is a simplified calculation method with an error of less than 1% compared to the ordinary procedure described above. Although the error slightly increases, a simplified calculation method will be described below. This method is a calculation method in which the number of sections is further reduced and section determination is unnecessary.
図１の第１区間と第２区間を１つにまとめ、さらに第５区間と第６区間を１つにまとめる。上記のαとβの二元連立一次方程式を適用する。第１∨２区間の回帰直線の傾きと切片は（０．４３７５，１．３２５）≒（０．４４，１．３３）、第５∨６区間の回帰直線の傾きと切片は（２．０６２５，－８．０２５）≒（２．０６，－８．０３）となる。上記の通り、第３∨４区間の回帰直線の傾きと切片は（０．９３７５，－０．９７５）≒（０．９４，－０．９８）である。新たな３つの区間の境界で、隣接する回帰直線は不連続となるが、不連続点（歩行速度４．８ｋｍ／時、６．４ｋｍ／時）での、元の運動強度（３．５メッツ、５．０メッツ）に対する誤差は、（３．５３２－３．４４２）／３．５≒２．６％、（５．１５４－５．０３６）／５．０≒２．４％であり、誤差はわずかである。また、３つの回帰直線の傾きは漸次増加である。そこで、これらの３つの区間の３つの回帰直線からなる区分線形関数は連続であり、３つの区間で凹特性であるとして扱う。こうすると、区間判定を行わず、歩行速度Ｖ（ｋｍ／時）に関する最大値関数を用いた次の数式２により運動強度Ｍ（メッツ）を求めることが出来る。身体活動分を対象とする時は、安静時の１メッツ分を差し引く。 The first section and the second section in FIG. 1 are combined into one, and the fifth section and the sixth section are combined into one. Apply the above binary simultaneous linear equations of α and β. The slope and intercept of the regression line in section 1∨2 are (0.4375, 1.325) ≈ (0.44, 1.33), and the slope and intercept of the regression line in section 5∨6 are (2.0625). , −8.025) ≈ (2.06, −8.03). As described above, the slope and intercept of the regression line in the third to fourth section are (0.9375, −0.975) ≈ (0.94, −0.98). The adjacent regression line becomes discontinuous at the boundary of the new three sections, but the original exercise intensity (3.5 mets) at the discontinuous point (walking speed 4.8 km / h, 6.4 km / h). , 5.0 mets) are (3.532-3.442) /3.5≈2.6%, (5.154-5.036) /5.0≈2.4%, The error is slight. In addition, the slopes of the three regression lines gradually increase. Therefore, a piecewise linear function composed of three regression lines in these three sections is continuous, and is treated as a concave characteristic in the three sections. By doing this, it is possible to obtain the exercise intensity M (Mets) by the following formula 2 using the maximum value function relating to the walking speed V (km / hour) without performing zone determination. When targeting physical activity, subtract 1 Met at rest.
Figure JPOXMLDOC01-appb-M000002
Figure JPOXMLDOC01-appb-M000002
基準とする６つの区間の区分線形関数の値と、数式２による演算値との誤差を確認する。数値検証結果、最大誤差は、歩行速度Ｖ＝６．４ｋｍ／時で、約３．１％であり、実用上の誤差としては問題ないと言える。 An error between the value of the piecewise linear function of the six sections as a reference and the calculated value according to Equation 2 is confirmed. As a result of the numerical verification, the maximum error is about 3.1% at walking speed V = 6.4 km / hour, and it can be said that there is no problem as a practical error.
歩行速度から運動強度を求める上記の単純化された演算方法は、非特許文献２の改訂版データに基づく本発明で基準とする区分線形関数から導き出されている。この演算方法は、次の特徴ある過程の一方または双方を用いて、実用上の正確さを保って単純化された方法である。そして、本発明の課題解決に大きく貢献する。その特徴ある過程とは、連続する区間で凹特性もしくは凸特性のいずれかであれば、その連続する区間ではさらに区間判定を行わず特性に応じて最大値関数もしくは最小値関数を用いる過程と、連続する区間を１つにまとめて、回帰分析で得られた１つの回帰直線に置き換える過程である。製品設計上の許容誤差を考慮し、これらの過程を組み合わせて演算方法を決定すればよい。この特徴ある過程は、区分線形関数の形が変わっても、また、歩行以外のジョギングやランニングなどの運動強度演算にも応用出来ることは言うまでもない。 The above-described simplified calculation method for obtaining exercise intensity from walking speed is derived from a piecewise linear function based on the present invention based on the revised data of Non-Patent Document 2. This calculation method is a simplified method with practical accuracy, using one or both of the following characteristic processes. This greatly contributes to solving the problems of the present invention. The characteristic process is a process using a maximum value function or a minimum value function according to the characteristics without performing further section determination in the continuous section if it is either a concave characteristic or a convex characteristic in the continuous section. This is a process in which continuous sections are combined into one and replaced with one regression line obtained by regression analysis. The calculation method may be determined by combining these processes in consideration of the tolerance in product design. It goes without saying that this characteristic process can also be applied to exercise intensity calculations such as jogging and running other than walking even if the shape of the piecewise linear function changes.
歩行速度を求めた後は、例えば、数式２を用いて運動強度が算出できる。さらに、この運動強度に計測された歩行時間を乗じてエクササイズが算出できる。これに１．０５×体重の基礎代謝量を乗じて消費カロリーが算出できる。そして、これを７．２で除して脂肪燃焼量が算出できる。このように、連なるように歩行関連情報が計算できる。従って、歩行速度が全ての歩行関連情報の基礎となるため、歩行速度をいかに正確に、あるいは、実用上の正確さもって求めるかが鍵となることが理解される。以下に歩行速度の演算方法を詳述する。 After obtaining the walking speed, for example, the exercise intensity can be calculated using Equation 2. Furthermore, the exercise can be calculated by multiplying the exercise intensity by the measured walking time. The calorie consumption can be calculated by multiplying this by the basal metabolic rate of 1.05 × body weight. Then, the fat burning amount can be calculated by dividing this by 7.2. In this way, the walking related information can be calculated so as to be continuous. Accordingly, since the walking speed is the basis of all walking related information, it is understood that how to determine the walking speed accurately or with practical accuracy is the key. The method for calculating the walking speed will be described in detail below.
先に結論を示す。以下の数式３が歩行速度の演算式となる。Ｎが単位時間（例えば１分）の歩数、即ち歩行ピッチである。以下では、単にピッチとも呼ぶ。Ｌは身長であり、ウォーキング歩幅は公知の身長の０．４５倍を用いる。０．４５・Ｌ・Ｎは、単位時間の歩行距離、即ち歩行速度である。しかし、歩幅は常に一定ではなく、ピッチが上ると広くも、下ると狭くもなる。歩幅を０．４５・Ｌとしたままでは正確に歩行速度を求めることは出来ない。歩幅を何らかの方法で補正しなければ、歩行関連情報も正確さを欠く。そこで、ピッチＮに応じた歩幅の補正を、補正関数ｆ（Ｎ）を乗ずることにより行い、数式３で歩行速度を演算する。数式３は、０．４５をそのまま使わず、身長に対する倍率を表す歩幅係数Ｓ３を用いた一般式としている。歩幅係数Ｓ３は後に説明する。 The conclusion is shown first. The following Equation 3 is an arithmetic expression for walking speed. N is the number of steps per unit time (for example, 1 minute), that is, the walking pitch. Hereinafter, it is also simply referred to as a pitch. L is height, and the walking stride is 0.45 times the known height. 0.45 · L · N is a walking distance per unit time, that is, a walking speed. However, the stride is not always constant, it becomes wider when the pitch goes up and becomes narrower when it goes down. If the stride is set to 0.45 · L, the walking speed cannot be obtained accurately. If the stride is not corrected by any method, the walking related information lacks accuracy. Therefore, the stride correction according to the pitch N is performed by multiplying by the correction function f (N), and the walking speed is calculated by Equation 3. Formula 3 does not use 0.45 as it is, but is a general formula using a stride factor S3 representing a magnification with respect to height. The stride factor S3 will be described later.
Figure JPOXMLDOC01-appb-M000003
Figure JPOXMLDOC01-appb-M000003
上記の数式３は、単位を揃えず、歩行速度演算式の形についてのみ示したものであり、後述の実際の演算式とは、係数の有無などに違いがある。また数式３の形自体は単純であるが、補正関数ｆ（Ｎ）の導出はそれほど簡単ではなく、本願発明者が特許文献を含めて関連情報の調査や、繰り返し行った歩行実験結果から導き出したものである。 Formula 3 above shows only the form of the walking speed calculation formula without aligning the units, and is different from the actual calculation formula described later in the presence or absence of coefficients. In addition, although the form of Formula 3 itself is simple, the derivation of the correction function f (N) is not so easy, and the inventor of the present application has derived it from the investigation of related information including patent documents and the results of repeated walking experiments. Is.
健康の増進あるいは改善のために意識的に速度を上げて行う運動としての歩行があり、買い物や散歩に出かけるといった生活活動の中での歩行もある。両者のピッチと歩幅は、当然異なり、前者は後者に比べ、いずれも大きくなることは容易に分かる。そこで、ピッチと歩幅の関係がどのように捉えられるかについて、まず説明する。 There is walking as an exercise to increase the speed consciously to promote or improve health, and walking in daily activities such as going out for shopping or walking. The pitch and stride of both are naturally different, and it is easy to see that the former is larger than the latter. Therefore, how the relationship between the pitch and the stride can be grasped will be described first.
時速６ｋｍ程度の速歩は、ピッチは１２０～１３０歩／分、歩幅は公知のウォーキング歩幅０．４５・Ｌ（Ｌは身長）に相当する。一方、上に例として示した生活活動の歩行も含めた時速４ｋｍ前後の普通歩行は、ピッチは９０～１００歩／分、そして、歩幅は０．４０・Ｌ程度とされる。 A fast walk of about 6 km / h corresponds to a pitch of 120 to 130 steps / minute and a stride of a known walking stride of 0.45 · L (L is height). On the other hand, the normal walking at a speed of about 4 km / h including the walking of daily activities shown as an example above has a pitch of 90 to 100 steps / minute and a step length of about 0.40 · L.
次に、ピッチに対する歩幅の変化について説明する。ピッチが９０～１３０歩／分の範囲では、ピッチと歩幅の変化は直線的であると考えられる。この点で特許文献１での回帰直線を用いる方法は妥当であり、本願発明者の行った歩行実験からもほぼ直線的変化が確認された。この歩行実験に関しては後述する。 Next, changes in the stride with respect to the pitch will be described. When the pitch is in the range of 90 to 130 steps / minute, the change in pitch and step length is considered to be linear. In this respect, the method using the regression line in Patent Document 1 is appropriate, and a substantially linear change was confirmed also from the walking experiment conducted by the present inventor. This walking experiment will be described later.
しかし、疑問はピッチが９０歩／分以下の範囲と１３０歩／分以上の範囲での歩幅変化である。この範囲にまで前記の直線を延長して考えればよいわけではない。延長すれば、次に述べる点から、歩幅計算に大きな誤差が生じ、正確な歩行速度を求めることが出来なくなる。 However, the question is the step length change in the range where the pitch is 90 steps / min or less and in the range where 130 pitches / min or more. It is not necessary to extend the straight line to this range. If it is extended, a large error occurs in the step length calculation from the following points, and it becomes impossible to obtain an accurate walking speed.
ピッチが９０～１３０歩／分の範囲では、ピッチを上げると同時に歩幅も広くなり、歩行速度はピッチにも歩幅にも概ね比例して増加する。ピッチが１３０歩／分以上の範囲ではピッチを上げても、歩幅変化は少なく増加はわずかと考えられ、歩行速度はピッチに比例した増加が主となる。なぜなら、歩幅をより広げた一歩行にかかる時間と、速いピッチとのバランスを維持して歩行を継続することは容易ではないことが理由である。専門家の次のような意見がある。身長の５０％の歩幅で歩く人がいないと言うことは出来ないが、その歩行はむしろ不自然な歩行か、あるいは、余程下半身の筋群のトレーニングを積んだ例外的な人であるだろう。（ｈｔｔｐ：／／ｗｗ２．ｗａｉｎｅｔ．ｎｅ．ｊｐ／～ｔｕｋａｓａ／Ｕ＿６．ｈｔｍｌ） When the pitch is in the range of 90 to 130 steps / minute, the stride increases as the pitch is increased, and the walking speed increases in proportion to both the pitch and the stride. When the pitch is in the range of 130 steps / minute or more, even if the pitch is increased, the change in the stride is small and the increase is considered to be slight, and the walking speed is mainly increased in proportion to the pitch. This is because it is not easy to keep walking while maintaining a balance between the time required for one walk with a wider stride and a fast pitch. There are the following opinions of experts. It can't be said that no one walks at 50% of the stature, but the gait would be an unnatural gait or an exceptional person trained with muscles in the lower body. . (Http://www2.winet.ne.jp/˜tukasa/U — 6.html)
さらにピッチを上げると歩幅は逆に狭くなり、歩行としては不自然な小走りに転じ、やがて、歩幅を回復して走行へと移る。従って、運動としての自然な歩行を対象とする限り、歩数計の応動範囲としてピッチの上限（例えば１５０～１６０歩／分の範囲の値）を設定する必要があろう。 When the pitch is further increased, the stride becomes narrower and turns into an unnatural sprint for walking, and eventually the stride is recovered and the run begins. Therefore, as long as natural gait as exercise is targeted, it is necessary to set the upper limit of the pitch (for example, a value in the range of 150 to 160 steps / minute) as the response range of the pedometer.
一方、ピッチが９０歩／分以下の範囲では、一歩行の時間に余裕があるため、歩幅を広くする、あるいは狭くすることは可能である。しかし、上げた片足を着地させるまでは、身体を他方の足で支える必要があるため、ピッチと身体バランス維持の点から、歩幅を広くすることは限界があり、さらに、不自然な歩行となる。逆に、歩幅を狭くすることは、身体バランスの問題はないが、狭くしすぎることは不自然な歩行となる。以上から、ピッチが９０歩／分以下の範囲では、自然な歩行での歩幅変化は少なく、歩幅の減少はわずかと考えられる。後述の本願発明者の歩行実験でもこのことを確認している。ピッチが下り過ぎると、生活活動を含めた運動としての自然な歩行とは言い難くなる。従って、上記と同様に、歩数計の応動範囲としてピッチの下限（例えば７０～８０歩／分の範囲の値）を設定することも必要であろう。 On the other hand, in the range where the pitch is 90 steps / minute or less, there is a margin for one walking time, and therefore it is possible to widen or narrow the stride. However, since it is necessary to support the body with the other leg until the raised one leg is landed, there is a limit to widening the stride from the standpoint of maintaining the pitch and the balance of the body, and it also leads to unnatural walking . Conversely, narrowing the stride does not cause a problem of body balance, but making it too narrow results in unnatural walking. From the above, it can be considered that when the pitch is 90 steps / minute or less, the change in the stride during natural walking is small and the decrease in the stride is slight. This is also confirmed by the inventor's walking experiment described later. If the pitch goes down too much, it will be difficult to say that it is natural walking as an exercise including daily activities. Accordingly, as described above, it may be necessary to set the lower limit of the pitch (for example, a value in the range of 70 to 80 steps / minute) as the response range of the pedometer.
以上に定量的に、定性的にピッチと歩幅との関係を詳述した。この関係を検証するために本願発明者は歩行実験を行った。一定区間（距離５５０ｍ）を、歩行ピッチを維持するために携帯した電子メトロノームの発信音に合わせて歩行し、歩行時間と歩数計の歩数を記録しデータを分析した。図２が実験結果を表し、計算された歩行ピッチと歩幅の関係をグラフ化している。ピッチ１２５歩／分あたり以上から歩幅増加の少ない範囲が現れ、ピッチ９５歩／分あたり以下から歩幅減少の少ない範囲が現れている。実験結果は上述の内容とよく一致する。本願発明者の身長１７２ｃｍから、計算上、ウォーキング歩幅＝１７２×０．４５＝７７．４ｃｍ、普通歩行歩幅＝１７２×０．４０＝６８．８ｃｍとなり、実験結果ともよく合う。 The relationship between pitch and stride has been described in detail quantitatively and qualitatively. In order to verify this relationship, the present inventor conducted a walking experiment. A certain section (distance 550 m) was walked according to the sound of the electronic metronome carried to maintain the walking pitch, the walking time and the number of steps of the pedometer were recorded and the data was analyzed. FIG. 2 shows the experimental results and graphs the relationship between the calculated walking pitch and step length. A range with a small increase in stride appears from above about 125 steps / minute, and a range with a small decrease in stride appears from below about 95 steps / minute. The experimental results agree well with the above. From the height of the present inventor's height of 172 cm, the walking stride = 172 × 0.45 = 77.4 cm and the normal walking stride = 172 × 0.40 = 68.8 cm, which are also in good agreement with the experimental results.
さて、歩幅の補正関数ｆ（Ｎ）について以下に説明する。説明で使う記号の意味は次の通りである。Ｎ２、Ｎ３、Ｓ２、Ｓ３、Ｋ１、およびＫ４は歩行特性を定めるパラメータと捉えることが出来る。
Ｎ１（歩／分）：下限ピッチ　　　例えば　７０≦Ｎ１≦　８０の定数
Ｎ２（歩／分）：普通歩行ピッチ　例えば　９０≦Ｎ２≦１００の定数
Ｎ３（歩／分）：速歩ピッチ　　　例えば１２０≦Ｎ３≦１３０の定数
Ｎ４（歩／分）：上限ピッチ　　　例えば１５０≦Ｎ４≦１６０の定数
Ｓ２：普通歩幅係数　０≦Ｓ２≦１の定数　例えば、０．４０
Ｓ３：速歩歩幅係数　０≦Ｓ３≦１の定数　例えば、０．４５
Ｋ１：下方傾き係数　０≦Ｋ１≦１の定数　例えば、０．５０
Ｋ４：上方傾き係数　０≦Ｋ４≦１の定数　例えば、０．５０
Ｌ（ｃｍ）：身長
記号のＮ１とＮ４は、歩数計の応動範囲の下限と上限のピッチであり、歩行特性とは直接関係しない。Ｓ２とＳ３は、歩幅の身長に対する倍率、また、Ｋ１とＫ４は、区間ごとに直線で表される補正関数の傾きに関する係数で、以下に説明する中間ピッチ区間の直線の傾きに対する倍数である。 Now, the stride correction function f (N) will be described below. The meanings of the symbols used in the explanation are as follows. N2, N3, S2, S3, K1, and K4 can be regarded as parameters that determine walking characteristics.
N1 (steps / minute): lower limit pitch, for example 70 ≦ N1 ≦ 80 constant N2 (steps / minute): normal walking pitch, for example, 90 ≦ N2 ≦ 100 constant N3 (steps / minute): fast walking pitch, for example 120 ≦ N3 ≦ 130 Constant N4 (steps / minute): upper limit pitch, for example 150 ≦ N4 ≦ 160 constant S2: normal stride factor 0 ≦ S2 ≦ 1 constant, for example 0.40
S3: Rapid walking stride coefficient 0 ≦ S3 ≦ 1 constant For example, 0.45
K1: Downward slope coefficient 0 ≦ K1 ≦ 1 constant, for example, 0.50
K4: upward slope coefficient 0 ≦ K4 ≦ 1 constant For example, 0.50
L (cm): N1 and N4 of the height symbol are the lower and upper pitches of the response range of the pedometer, and are not directly related to the walking characteristics. S2 and S3 are magnifications with respect to the height of the stride, and K1 and K4 are coefficients relating to the slope of the correction function represented by a straight line for each section, which are multiples of the slope of the straight line in the intermediate pitch section described below.
単位時間に計測される歩数、即ち、歩行ピッチをＮ（歩／分）とする。先の詳細な説明に基づいて、歩幅の補正関数ｆ（Ｎ）は、３つの歩行ピッチ区間を設けて、数式４、数式５、および数式６で与えることができる。この補正関数は、３つの区間を持つ連続な区分線形関数を構成する。尚、ｆ（Ｎ）は速歩歩幅Ｓ３・Ｌで正規化している。 The number of steps measured per unit time, that is, the walking pitch is N (steps / minute). Based on the above detailed description, the stride correction function f (N) can be given by Equation 4, Equation 5, and Equation 6 by providing three walking pitch sections. This correction function constitutes a continuous piecewise linear function having three intervals. Note that f (N) is normalized by the rapid walking stride S3 · L.
普通歩行ピッチＮ２～速歩ピッチＮ３（以下では“中間ピッチ区間”と呼ぶ） Normal walking pitch N2 to rapid walking pitch N3 (hereinafter referred to as “intermediate pitch section”)
Figure JPOXMLDOC01-appb-M000004
Figure JPOXMLDOC01-appb-M000004
下限ピッチＮ１～普通歩行ピッチＮ２（以下では“下方ピッチ区間”と呼ぶ） Lower limit pitch N1 to normal walking pitch N2 (hereinafter referred to as “downward pitch section”)
Figure JPOXMLDOC01-appb-M000005
Figure JPOXMLDOC01-appb-M000005
速歩ピッチＮ３～上限ピッチＮ４（以下では“上方ピッチ区間”と呼ぶ） Rapid walking pitch N3 to upper limit pitch N4 (hereinafter referred to as “upper pitch section”)
Figure JPOXMLDOC01-appb-M000006
Figure JPOXMLDOC01-appb-M000006
上記の数式４、数式５、もしくは数式６のいずれかの歩幅の補正関数を用いて計算された補正値ｆ（Ｎ）を数式３に適用することで正確に歩行速度を求めることが出来る。 The walking speed can be accurately obtained by applying the correction value f (N) calculated by using the stride correction function of any one of the above formulas 4, 5, or 6 to the formula 3.
しかし、本発明は、歩数と併せて提供される歩行関連情報が、実用上の正確さもち、かつ、構造が単純で経済的に安価であることも課題としている。上記の数式４、数式５、数式６、および数式３による歩行速度の演算方式を単純化することによって、この課題を解決する方法を以下に詳しく説明する。 However, an object of the present invention is that the walking-related information provided together with the number of steps has practical accuracy, is simple in structure, and is economically inexpensive. A method for solving this problem will be described in detail below by simplifying the calculation method of the walking speed according to Equation 4, Equation 5, Equation 6, and Equation 3.
まず、数式４、数式５、および数式６を数式３に代入し、歩行速度の演算式を具体的に展開してみる。中間ピッチ区間Ｎ２～Ｎ３については、数式４を数式３に代入する。
歩行速度Ｖ＝ｆ（Ｎ）・Ｓ３・Ｌ・Ｎ
＝（（１－Ｓ２／Ｓ３）／（Ｎ３－Ｎ２）・（Ｎ－Ｎ３）＋１）・
Ｓ３・Ｌ・Ｎ
＝（Ｓ３－Ｓ２）／（Ｎ３－Ｎ２）・
（Ｎ＋（Ｓ２・Ｎ３－Ｓ３・Ｎ２）／（Ｓ３－Ｓ２））・Ｎ・Ｌ First, formula 4, formula 5, and formula 6 are substituted into formula 3, and the formula for calculating the walking speed is specifically developed. For intermediate pitch sections N2 to N3, Formula 4 is substituted into Formula 3.
Walking speed V = f (N) / S3 / L / N
= ((1-S2 / S3) / (N3-N2). (N-N3) +1).
S3 ・ L ・ N
= (S3-S2) / (N3-N2)
(N + (S2, N3-S3, N2) / (S3-S2)), N, L
下方ピッチ区間Ｎ１～Ｎ２については、数式５を数式３に代入する。
歩行速度Ｖ＝ｆ（Ｎ）・Ｓ３・Ｌ・Ｎ
＝（Ｋ１・（１－Ｓ２／Ｓ３）／（Ｎ３－Ｎ２）・（Ｎ－Ｎ２）＋Ｓ２／Ｓ３）・
Ｓ３・Ｌ・Ｎ
＝（Ｓ３－Ｓ２）／（Ｎ３－Ｎ２）・
（Ｋ１・Ｎ＋Ｓ２・（Ｎ３－Ｎ２）／（Ｓ３－Ｓ２）－Ｋ１・Ｎ２）・Ｎ・Ｌ Formula 5 is substituted into Formula 3 for the lower pitch sections N1 and N2.
Walking speed V = f (N) / S3 / L / N
= (K1 · (1-S2 / S3) / (N3-N2) · (N−N2) + S2 / S3)
S3 ・ L ・ N
= (S3-S2) / (N3-N2)
(K1 ・ N + S2 ・ (N3-N2) / (S3-S2) −K1 ・ N2) ・ N ・ L
上方ピッチ区間Ｎ３～Ｎ４については、数式６を数式３に代入する。
歩行速度Ｖ＝ｆ（Ｎ）・Ｓ３・Ｌ・Ｎ
＝（Ｋ４・（１－Ｓ２／Ｓ３）／（Ｎ３－Ｎ２）・（Ｎ－Ｎ３）＋１）・
Ｓ３・Ｌ・Ｎ
＝（Ｓ３－Ｓ２）／（Ｎ３－Ｎ２）・
（Ｋ４・Ｎ＋Ｓ３・（Ｎ３－Ｎ２）／（Ｓ３－Ｓ２）－Ｋ４・Ｎ３）・Ｎ・Ｌ For the upper pitch sections N3 to N4, Equation 6 is substituted into Equation 3.
Walking speed V = f (N) / S3 / L / N
= (K4. (1-S2 / S3) / (N3-N2). (N-N3) +1).
S3 ・ L ・ N
= (S3-S2) / (N3-N2)
(K4 ・ N + S3 ・ (N3-N2) / (S3-S2) −K4 ・ N3) ・ N ・ L
歩行速度演算式を展開した式の形は、歩行速度Ｖ＝ｋ・（ｋｉ・Ｎ＋ｃｉ）・Ｎ・Ｌである。ここで、ＮとＬは歩行ピッチ（歩／分）と身長（ｃｍ）、係数ｋは３つの歩行ピッチ区間の直線に共通の係数であり、係数ｋｉと定数ｃｉは３つの歩行ピッチ区間の直線の傾きと切片に相当する。上式に歩行時速への換算係数ｈ＝６０／１００／１０００を乗算して歩行時速が得られる。そして、ｈ・ｋ・ｋｉを新たな係数ｋｉと考え、ｈ・ｋ・ｃｉを新たな定数ｃｉと考える。このようにして、歩行速度の演算式は、次の数式７で与えられる。数式７において、３つのピッチ区間ごとに定められたＮの一次式が表す直線が、連続な区分線形関数を構成していることは言うまでもない。そして、係数ｋｉと定数ｃｉは歩行ピッチ区間ごとに定められる直線の傾きと切片である。また、この一次式にＮを乗じた二次式も、３つのピッチ区間で連続な区分的に二次関数となる。本発明では区分二次関数と呼ぶ。この区分二次関数が、後述の各種の回帰式の誤差評価の基準となる。 The form of the expression obtained by developing the walking speed calculation expression is walking speed V = k · (ki · N + ci) · N · L. Here, N and L are the walking pitch (steps / minute) and height (cm), the coefficient k is a coefficient common to the straight lines of the three walking pitch sections, and the coefficient ki and the constant ci are the straight lines of the three walking pitch sections. It corresponds to the slope and intercept. The walking speed is obtained by multiplying the above equation by the conversion factor h = 60/100/1000 for walking speed. Then, h · k · ki is considered as a new coefficient ki, and h · k · ci is considered as a new constant ci. In this way, the calculation formula of the walking speed is given by the following formula 7. In Formula 7, it goes without saying that a straight line represented by a linear expression of N determined for every three pitch sections constitutes a continuous piecewise linear function. The coefficient ki and the constant ci are the slope and intercept of a straight line determined for each walking pitch section. Further, a quadratic expression obtained by multiplying the linear expression by N also becomes a quadratic function in a piecewise manner continuous in three pitch sections. In the present invention, this is called a piecewise quadratic function. This piecewise quadratic function is a standard for error evaluation of various regression equations described later.
Figure JPOXMLDOC01-appb-M000007
Figure JPOXMLDOC01-appb-M000007
数式７を用いて歩行速度を求める方法は、まず、ピッチ区間の判定を行う。３つの区間であるから、最大２回の判定が必要ある。そして、そのピッチ区間に定められた一次式を選択して代入計算を行う。この時、係数との乗算がある。次に、この結果にＮとＬを乗算する。この方法は歩行速度を正確に演算する、順当な過程を経る、普通の演算手順である。先の運動強度演算で、連続な区分線形関数に対して区間判定回数を減らす方法を説明した。連続する区間での凹特性、もしくは凸特性に応じて最大値関数、もしくは最小値関数を用いる方法である。この方法によって、区間判定の回数を１回とすることが出来る。しかし、これだけでは、手順の単純化の効果は少ない。 The method for obtaining the walking speed using Equation 7 first determines the pitch interval. Since there are three sections, a maximum of two determinations are required. Then, a linear expression defined for the pitch section is selected and substitution calculation is performed. At this time, there is multiplication with a coefficient. Next, this result is multiplied by N and L. This method is a normal calculation procedure through a proper process of calculating the walking speed accurately. In the previous exercise intensity calculation, a method for reducing the number of section determinations for a continuous piecewise linear function has been described. In this method, the maximum value function or the minimum value function is used according to the concave characteristic or the convex characteristic in the continuous section. By this method, the number of section determinations can be set to one. However, this alone has little effect on the simplification of the procedure.
数式７において、Ｎの一次式にＮが乗算された二次式部分を回帰分析する。そして得られた回帰直線の一次式に置き換えると、乗算回数を１回減らすことが出来る。高々１回の乗算回数の減少だが、近似誤差が実用上の誤差内であれば、このような工夫を重ねることは演算の構造を単純化し、結果、本発明の課題解決につながる。以下に具体的に説明する。 In Equation 7, a regression analysis is performed on a quadratic part obtained by multiplying a primary expression of N by N. If the obtained regression line is replaced with a linear expression, the number of multiplications can be reduced by one. Although the number of multiplications is reduced by one at most, if the approximation error is within a practical error, repeating such a device simplifies the structure of the calculation, and as a result, the problem of the present invention is solved. This will be specifically described below.
二次式（ｋｉ・Ｎ＋ｃｉ）・Ｎを、区間Ｐ～Ｑで最小二乗法により回帰分析する。回帰直線は解析的に求められ、その傾きと切片は、次の一般式で与えられる。証明は省く。尚、この回帰直線の傾きと切片が、回帰式の係数と定数であることは言うまでもない。
回帰直線の傾き：ｋｉ・（Ｐ＋Ｑ）＋ｃｉ
回帰直線の切片：－ｋｉ・（Ｐ・Ｐ＋４・Ｐ・Ｑ＋Ｑ・Ｑ）／６
二次式のｋｉ、ｃｉ、区間のＰ、Ｑは検討内容から正値と考えてよい。回帰式から二次式を引いた差分の値は、区間の中間で最大（正値）となり、区間の両端で最小（負値で、大きさは最大値の２倍）となることが示される。従って、二次式の値が区間で増加であるから、差分の二次式に対する誤差の大きさは区間の下端（Ｐ）で最大で、次式で計算される。
差分絶対値の最大値：ｋｉ・（Ｐ－Ｑ）・（Ｐ－Ｑ）／６
誤差絶対値の最大値：ｋｉ・（Ｐ－Ｑ）・（Ｐ－Ｑ）／６／（（ｋｉ・Ｐ＋ｃｉ）・Ｐ） The quadratic equation (ki · N + ci) · N is subjected to regression analysis by the least square method in the interval P to Q. The regression line is obtained analytically, and its slope and intercept are given by the following general formula. Omit proof. Needless to say, the slope and intercept of the regression line are coefficients and constants of the regression equation.
Inclination of regression line: ki · (P + Q) + ci
Regression line intercept: −ki · (P · P + 4 · P · Q + Q · Q) / 6
The quadratic expressions ki and ci and P and Q of the section may be considered positive values from the examination content. The difference value obtained by subtracting the quadratic equation from the regression equation is maximum (positive value) in the middle of the interval, and is minimum (negative value, twice the maximum value) at both ends of the interval. . Accordingly, since the value of the quadratic expression is increased in the section, the magnitude of the error with respect to the quadratic expression of the difference is the maximum at the lower end (P) of the section and is calculated by the following expression.
Maximum difference absolute value: ki · (PQ) · (PQ) / 6
Maximum error absolute value: ki · (PQ) · (PQ) / 6 / ((ki · P + ci) · P)
具体的な数値を使って確認してみる。代表的な数値、Ｎ１＝７０、Ｎ２＝９５、Ｎ３＝１２５、Ｎ４＝１６０、Ｓ２＝０．４０、Ｓ３＝０．４５、Ｋ１＝０．５、およびＫ４＝０．５を使う。二次式と回帰式および最大誤算は、３つのピッチ区間ごとに以下の通りである。尚、計算上、３つの一次式（ｋｉ・Ｎ＋ｃｉ）の係数ｋｉと定数ｃｉは、これらに共通する値の（Ｓ３－Ｓ２）／（Ｎ３－Ｎ２）＝１／６００に、時速換算係数ｈ＝６０／１００／１０００を乗じた値で割り算している。 Check using specific values. Use representative values: N1 = 70, N2 = 95, N3 = 125, N4 = 160, S2 = 0.40, S3 = 0.45, K1 = 0.5, and K4 = 0.5. The quadratic equation, regression equation and maximum miscalculation are as follows for each of the three pitch sections. In the calculation, the coefficient ki and the constant ci of the three linear expressions (ki · N + ci) are the same value (S3−S2) / (N3−N2) = 1/600, and the hourly speed conversion coefficient h = It is divided by the value multiplied by 60/100/1000.
下方ピッチ区間（７０～９５歩／分）
二次式と回帰式：（Ｎ／２＋３８５／２）・Ｎ≒２７５・Ｎ－３３７７
最大誤差：０．００３２７≒０．３３％ Lower pitch section (70-95 steps / minute)
Quadratic and regression equations: (N / 2 + 385/2) · N≈275 · N-3377
Maximum error: 0.00327 ≒ 0.33%
中間ピッチ区間（９５～１２５歩／分）
二次式と回帰式：（Ｎ＋１４５）・Ｎ≒３６５・Ｎ－１２０２５
最大誤差：０．００６５７≒０．６６％ Intermediate pitch section (95 to 125 steps / minute)
Quadratic and regression equations: (N + 145) · N≈365 · N−12025
Maximum error: 0.00657 ≒ 0.66%
上方ピッチ区間（１２５～１６０歩／分）
二次式と回帰式：（Ｎ／２＋４１５／２）・Ｎ≒３５０・Ｎ－１０１０２
最大誤差：０．００３０２≒０．３０％ Upper pitch section (125-160 steps / minute)
Quadratic and regression equations: (N / 2 + 415/2) · N≈350 · N-10102
Maximum error: 0.00302 ≒ 0.30%
いずれのピッチ区間でも誤差は１％未満であり、二次式を回帰式に置き換えても全く問題はない。置き換えることで乗算回数を１回減らすことが出来る。歩行速度計算式に戻すために、上記の共通数を乗算すると、３つの回帰式の係数と定数は変わるが、誤差は変わらないことは言うまでもない。さらに、３つの回帰直線は、３つのピッチ区間で区分線形関数を構成する。厳密には区間の境界で不連続であるが、元の二次式の値に対す不連続点の誤差は１％未満であり、連続な区分線形関数とみなし、加えて、回帰直線の傾きから、下方ピッチ区間と中間ピッチ区間で凹特性、あるいは、中間ピッチ区間と上方ピッチ区間で凸特性と見なすことも出来る。従って、最大値関数、あるいは最小値関数を用いて凹特性、もしくは凸特性区間での区間判定を不要にする方法を組み合わせることも出来る。 In any pitch interval, the error is less than 1%, and there is no problem even if the quadratic equation is replaced with a regression equation. By replacing it, the number of multiplications can be reduced by one. It goes without saying that when the above common number is multiplied to return to the walking speed calculation formula, the coefficients and constants of the three regression equations change, but the error does not change. Further, the three regression lines constitute a piecewise linear function with three pitch sections. Strictly speaking, it is discontinuous at the boundary of the interval, but the error of the discontinuous point with respect to the original quadratic value is less than 1%, and is regarded as a continuous piecewise linear function, and in addition, from the slope of the regression line Also, it can be regarded as a concave characteristic in the lower pitch section and the intermediate pitch section, or as a convex characteristic in the intermediate pitch section and the upper pitch section. Therefore, it is possible to combine a method that makes it unnecessary to determine the section in the concave characteristic or convex characteristic section by using the maximum value function or the minimum value function.
上記の歩行速度の演算方法はピッチ区間の判定が必要だが、二次式が回帰式で単純化され、その誤算も１％未満である。本発明の課題解決の有効な手段と出来る１つの方法である。これから説明する方法は、誤差が多少増加するが、ピッチ区間の判定が不要な、より単純化された優れた歩行速度の演算方法である。 The above walking speed calculation method requires the determination of the pitch interval, but the quadratic expression is simplified by the regression equation, and the miscalculation is less than 1%. This is an effective means for solving the problems of the present invention. The method to be described below is a more simplified and excellent walking speed calculation method that does not require the determination of the pitch section, although the error slightly increases.
数式７の二次式部分は、３つのピッチ区間で連続な区分二次関数となることを先に述べた。この区分二次関数を、ピッチ区間を通して最小二乗法によって回帰分析し、１つの回帰直線に置き換えようとする方法である。この回帰直線も、解析的に求めることができる。傾きと切片を変数とする回帰直線との差分の二乗値を、対象とする区間で積分し、その積分値を最少にする変数を決定する方法である。先に求めた回帰直線も同じ手法で求めている。今回は、多少複雑となるが、結果を以下に示す。証明は省く。 As described above, the quadratic part of Equation 7 is a piecewise quadratic function continuous in three pitch sections. In this method, the piecewise quadratic function is subjected to regression analysis by the least square method through the pitch interval and is replaced with one regression line. This regression line can also be obtained analytically. In this method, the square value of the difference between the slope and the regression line having the intercept as a variable is integrated in the target section, and the variable that minimizes the integral value is determined. The regression line obtained earlier is also obtained by the same method. This time, it will be a little complicated, but the results are shown below. Omit proof.
以上で使ってきた記号Ｎ１、Ｎ２、Ｎ３、Ｎ４、Ｋ１、およびＫ４を用いる。尚、Ｎ１≦Ｎ２≦Ｎ３≦Ｎ４とする。中間ピッチ区間の二次式を、（ｋ２・Ｎ＋ｃ２）・Ｎで表す。この時、下方ピッチ区間および上方ピッチ区間の一次式は連続であるため、二次式は次の式で表される。
下方ピッチ区間の二次式：（Ｋ１・ｋ２・（Ｎ－Ｎ２）＋ｋ２・Ｎ２＋ｃ２）・Ｎ
上方ピッチ区間の二次式：（Ｋ４・ｋ２・（Ｎ－Ｎ３）＋ｋ２・Ｎ３＋ｃ２）・Ｎ
また、求める回帰直線の式を次式とする。
回帰直線の式：γ・Ｎ＋δ
ピッチ区間Ｎ１～Ｎ４における、二次式と回帰直線の式との差分の二乗値をこの区間で積分し、その積分値の最小値を与えるγとδを決定する。 The symbols N1, N2, N3, N4, K1, and K4 that have been used above are used. Note that N1 ≦ N2 ≦ N3 ≦ N4. A quadratic expression of the intermediate pitch section is represented by (k2 · N + c2) · N. At this time, since the primary expression of the lower pitch section and the upper pitch section is continuous, the secondary expression is expressed by the following expression.
Quadratic formula of the lower pitch section: (K1 · k2 · (N−N2) + k2 · N2 + c2) · N
Secondary equation of upper pitch section: (K4 · k2 · (N−N3) + k2 · N3 + c2) · N
Moreover, let the equation of the regression line to be obtained be the following equation.
Regression line formula: γ · N + δ
The square value of the difference between the quadratic equation and the regression line equation in the pitch interval N1 to N4 is integrated in this interval, and γ and δ giving the minimum value of the integrated value are determined.
回帰直線の傾きγと切片δ、即ち、回帰式の係数γと定数δは、次の二元連立一次方程式の解として与えられる。
（２／３）・（Ｇ３（Ｎ４，Ｎ１））・γ＋（Ｇ２（Ｎ４，Ｎ１））・δ＝ＳＧＭ１
（Ｇ２（Ｎ４，Ｎ１））・γ＋２・（Ｇ１（Ｎ４，Ｎ１））・δ＝ＳＧＭ２
ここで、関数Ｇ１（Ｘ，Ｙ）、Ｇ２（Ｘ，Ｙ）、Ｇ３（Ｘ，Ｙ）、およびＧ４（Ｘ，Ｙ）、並びに、ＳＧＭ１とＳＧＭ２は次の通りである。
Ｇ１（Ｘ，Ｙ）＝Ｘ－Ｙ
Ｇ２（Ｘ，Ｙ）＝Ｘ・Ｘ－Ｙ・Ｙ
Ｇ３（Ｘ，Ｙ）＝Ｘ・Ｘ・Ｘ－Ｙ・Ｙ・Ｙ
Ｇ４（Ｘ，Ｙ）＝Ｘ・Ｘ・Ｘ・Ｘ－Ｙ・Ｙ・Ｙ・Ｙ
ＳＧＭ１＝（２／４）・ｋ２・（Ｇ４（Ｎ４，Ｎ１））
＋（２／３）・ｃ２・（Ｇ３（Ｎ４，Ｎ１））
－２・（１－Ｋ１）・ｋ２・（１／４）・（Ｇ４（Ｎ２，Ｎ１））
－２・（１－Ｋ４）・ｋ２・（１／４）・（Ｇ４（Ｎ４，Ｎ３））
＋２・（１－Ｋ１）・ｋ２・（１／３）・Ｎ２・（Ｇ３（Ｎ２，Ｎ１））
＋２・（１－Ｋ４）・ｋ２・（１／３）・Ｎ３・（Ｇ３（Ｎ４，Ｎ３））
ＳＧＭ２＝（２／３）・ｋ２・（Ｇ３（Ｎ４，Ｎ１））
＋（２／２）・ｃ２・（Ｇ２（Ｎ４，Ｎ１））
－２・（１－Ｋ１）・ｋ２・（１／３）・（Ｇ３（Ｎ２，Ｎ１））
－２・（１－Ｋ４）・ｋ２・（１／３）・（Ｇ３（Ｎ４，Ｎ３））
＋２・（１－Ｋ１）・ｋ２・（１／２）・Ｎ２・（Ｇ２（Ｎ２，Ｎ１））
＋２・（１－Ｋ４）・ｋ２・（１／２）・Ｎ３・（Ｇ２（Ｎ４，Ｎ３）） The slope γ and intercept δ of the regression line, that is, the coefficient γ and the constant δ of the regression equation are given as solutions of the following binary simultaneous linear equations.
(2/3) · (G3 (N4, N1)) · γ + (G2 (N4, N1)) · δ = SGM1
(G2 (N4, N1)) · γ + 2 · (G1 (N4, N1)) · δ = SGM2
Here, the functions G1 (X, Y), G2 (X, Y), G3 (X, Y), and G4 (X, Y), and SGM1 and SGM2 are as follows.
G1 (X, Y) = XY
G2 (X, Y) = X, XY, Y
G3 (X, Y) = X, X, XY, Y, Y
G4 (X, Y) = X, X, X, XY, Y, Y, Y
SGM1 = (2/4) · k2 · (G4 (N4, N1))
+ (2/3) · c2 · (G3 (N4, N1))
-2 ・ (1-K1) ・ k2 ・ (1/4) ・ (G4 (N2, N1))
-2 ・ (1-K4) ・ k2 ・ (1/4) ・ (G4 (N4, N3))
+2 ・ (1-K1) ・ k2 ・ (1/3) ・ N2 ・ (G3 (N2, N1))
+2 ・ (1-K4) ・ k2 ・ (1/3) ・ N3 ・ (G3 (N4, N3))
SGM2 = (2/3) · k2 · (G3 (N4, N1))
+ (2/2) · c2 · (G2 (N4, N1))
-2 ・ (1-K1) ・ k2 ・ (1/3) ・ (G3 (N2, N1))
-2 ・ (1-K4) ・ k2 ・ (1/3) ・ (G3 (N4, N3))
+2 ・ (1-K1) ・ k2 ・ (1/2) ・ N2 ・ (G2 (N2, N1))
+2 ・ (1-K4) ・ k2 ・ (1/2) ・ N3 ・ (G2 (N4, N3))
上記の二元連立一次方程式の解であるγとδを、一般式の形で解くことは相当に複雑である。また、元の区分二次関数と、求められた回帰直線との差分誤差を一般式の形で導出することも同様に複雑である。しかし、具体的な数値によって二元連立一次方程式の係数と定数が決れば、容易に解くことが出来、回帰直線が決定出来る。そして、誤差も計算できる。そこで、具体的な数値で確認してみる。先に使った代表的な数値、Ｎ１＝７０、Ｎ２＝９５、Ｎ３＝１２５、Ｎ４＝１６０、Ｓ２＝０．４０、Ｓ３＝０．４５、Ｋ１＝０．５、Ｋ４＝０．５、および、中間ピッチ区間の二次式（Ｎ＋１４５）・Ｎを用いる。この時は、ｋ２＝１、ｃ２＝１４５である。二元連立一次方程式を解き、得られた回帰式は、次の通りである。２つのピッチ区間で回帰分析した理由は、誤差傾向の確認の他に、歩数計の応動範囲とも関係している。これらについては後で説明する。
ピッチ区間７０～１６０を通して回帰分析した回帰式：３４２・Ｎ－　９１７４
ピッチ区間８０～１５０を通して回帰分析した回帰式：３４９・Ｎ－１００９４ It is quite complicated to solve γ and δ, which are solutions of the above binary simultaneous linear equations, in the form of general formulas. It is also complicated to derive the difference error between the original piecewise quadratic function and the obtained regression line in the form of a general formula. However, if the coefficients and constants of the binary simultaneous linear equations are determined by specific numerical values, they can be solved easily and the regression line can be determined. And the error can also be calculated. Therefore, we will check with specific numerical values. Representative numerical values used earlier, N1 = 70, N2 = 95, N3 = 125, N4 = 160, S2 = 0.40, S3 = 0.45, K1 = 0.5, K4 = 0.5, and Further, a quadratic expression (N + 145) · N of the intermediate pitch section is used. At this time, k2 = 1 and c2 = 145. The regression equation obtained by solving the binary simultaneous linear equations is as follows. The reason for the regression analysis in the two pitch sections is related to the response range of the pedometer in addition to the confirmation of the error tendency. These will be described later.
Regression equation regressed through pitch sections 70 to 160: 342 · N-9174
Regression equation regressed through pitch sections 80-150: 349 N-10094
上記の回帰式を用いると、ピッチ区間の判定は不要となり演算式はただ１つでよく、演算構造は最も単純化される。誤差が実用上の範囲内か否かを確認する前に、この方法に至る１つ手前の演算方法について説明する。最も単純化された方法よりは、誤差が少なくなることが期待出来そうである。１つ手前の方法とは、３つのピッチ区間を、例えば中間当たりで分割し、２つのピッチ区間とする。それぞれのピッチ区間で二次式を回帰分析して、２つの回帰直線を求める。そして、最大値関数、もしくは最小値関数を用いて区間判定を省く方法である。 If the above regression equation is used, it is not necessary to determine the pitch interval, and only one arithmetic equation is required, and the arithmetic structure is simplified. Before confirming whether or not the error is within a practical range, a calculation method immediately before this method will be described. It seems likely that there will be fewer errors than the simplest method. In the previous method, the three pitch sections are divided, for example, in the middle and are set to two pitch sections. Two regression lines are obtained by regression analysis of the quadratic expression in each pitch interval. And it is the method of omitting area determination using the maximum value function or the minimum value function.
２分割するピッチを中間の１１５（歩／分）とする。Ｎ１＝７０（または８０）、Ｎ２＝９５、Ｎ３＝例えば１０５、Ｎ４＝１１５、Ｓ２＝０．４、Ｓ３＝０．４５、Ｋ１＝０．５、Ｋ４＝１．０、二次式を（Ｎ＋１４５）・Ｎとする。そして、先のγとδに関する二元連立一次方程式を解くことにより、ピッチ区間７０（８０）～１１５での回帰直線が決定できる。また、Ｎ１＝１１５、Ｎ２＝例えば１２０、Ｎ３＝１２５、Ｎ４＝１６０（または１５０）、Ｓ２＝０．４、Ｓ３＝０．４５、Ｋ１＝１．０、Ｋ４＝０．５とすれば、ピッチ区間１１５～１６０（１５０）での回帰直線が決定できる。決定された回帰式は次の通りである。
ピッチ区間７０～１６０をピッチ１１５で２分割
ピッチ区間　７０～１１５で回帰分析した回帰式：３０９・Ｎ－　６０６９
ピッチ区間１１５～１６０で回帰分析した回帰式：３５２・Ｎ－１０４５９
ピッチ区間８０～１５０をピッチ１１５で２分割
ピッチ区間　８０～１１５で回帰分析した回帰式：３２３・Ｎ－　７６５６
ピッチ区間１１５～１５０で回帰分析した回帰式：３５２・Ｎ－１０３６１ The pitch to be divided into two is set to an intermediate 115 (steps / minute). N1 = 70 (or 80), N2 = 95, N3 = eg 105, N4 = 115, S2 = 0.4, S3 = 0.45, K1 = 0.5, K4 = 1.0 N + 145) · N. Then, by solving the binary simultaneous linear equations related to γ and δ, the regression line in the pitch sections 70 (80) to 115 can be determined. Also, if N1 = 115, N2 = 120, N3 = 125, N4 = 160 (or 150), S2 = 0.4, S3 = 0.45, K1 = 1.0, K4 = 0.5, A regression line in the pitch sections 115 to 160 (150) can be determined. The determined regression equation is as follows.
Regression equation of regression analysis of pitch sections 70-160 with pitch 115 and two-division pitch sections 70-115: 309 · N-6069
Regression equation for regression analysis in the pitch sections 115 to 160: 352 · N-10459
Regression equation of regression analysis of pitch sections 80 to 150 with pitch 115 and two divided pitch sections 80 to 115: 323 · N-7656
Regression equation for regression analysis in pitch interval 115 to 150: 352 · N-10361
誤差評価の基準となる区分二次関数と得られ回帰直線との誤差を評価する。基準となる二次式は先に示した通り。比較する回帰式はすぐ上に示した通り。尚、１分割とはピッチ区間７０～１６０、あるいは８０～１５０を通した回帰分析を言う。表１に誤差の計算結果を示す。尚、誤差は、回帰式の値から二次式の値を減じ、その結果を二次式の値で割り算をして％で示している。
ピッチ区間　７０～　９５の二次式：（Ｎ／２＋３８５／２）・Ｎ
ピッチ区間　９５～１２５の二次式：（Ｎ＋１４５）・Ｎ
ピッチ区間１２５～１６０の二次式：（Ｎ／２＋４１５／２）・Ｎ
ピッチ区間７０～１６０で回帰分析
１分割：３４２・Ｎ－９１７４
２分割：ＭＡＸ（３０９・Ｎ－６０６９，３５２・Ｎ－１０４５９）
ピッチ区間８０～１５０で回帰分析
１分割：３４９・Ｎ－１００９４
２分割：ＭＡＸ（３２３・Ｎ－７６５６，３５２・Ｎ－１０３６１） Evaluate the error between the piecewise quadratic function that is the standard for error evaluation and the regression line obtained. The standard secondary equation is as shown above. The regression equation to compare is as shown immediately above. One division means a regression analysis through the pitch sections 70 to 160 or 80 to 150. Table 1 shows the error calculation results. The error is expressed as% by subtracting the value of the quadratic expression from the value of the regression equation and dividing the result by the value of the quadratic expression.
Secondary expression of pitch section 70-95: (N / 2 + 385/2) · N
Secondary expression of pitch section 95-125: (N + 145) · N
Secondary expression of pitch sections 125 to 160: (N / 2 + 415/2) · N
Regression analysis in the pitch interval 70 to 160: 1 division: 342 · N-9174
Divided into two: MAX (309, N-6069, 352, N-10459)
Regression analysis with pitch interval 80-150: 1 division: 349 ・ N-10094
Divided into two: MAX (323 · N-7656, 352 · N-10361)
Figure JPOXMLDOC01-appb-T000008
Figure JPOXMLDOC01-appb-T000008
表１に示されるように、誤差が約５％以上は、ピッチ区間７０～１６０で１分割の回帰式を用いた場合である。それは、ピッチ７０台半ば以下の一部の区間のみである。いずれの回帰式を用いた場合も、ピッチ８０から８０台の半ばまでは約４％以下、ピッチ８０台半ば以上では約２％以下、さらに、１１０台半ば以上では約１％以下に収まっている。２分割では、ピッチ区間を通して約２％以下であり、期待通りである。この誤差結果から、区間判定を不要とでき、かつ、演算構造をより単純化できる上記の方法は、本発明の課題解決の手段として十分に有効であると言える。 As shown in Table 1, when the error is about 5% or more, a one-part regression equation is used in the pitch sections 70 to 160. It is only a part of the section below the mid 70 pitches. Whichever regression equation is used, it is about 4% or less from the pitch 80 to the middle of the 80 units, about 2% or less at the middle of the pitch 80 or more, and about 1% or less at the middle of the 110 units or more. . In 2 divisions, it is about 2% or less throughout the pitch section, as expected. From this error result, it can be said that the above-described method that can eliminate the interval determination and can further simplify the calculation structure is sufficiently effective as means for solving the problems of the present invention.
歩数計の応動範囲について言及する。歩数計に内蔵の振り子や加速度センサの歩行ピッチに対する応答性能について、本願発明者は次のようなことを経験した。先の歩行実験時に、ピッチ８０以下、或いは、ピッチ１５０以上で歩行した時に、まれに歩数計の歩数値がおかしいと、はっきりと気が付くほど少ないことがあった。つまり、センサが正しく応答していないと考えられる。また、自然な身体活動として歩行をした時の歩行ピッチも考えると、演算式を単純化したときに発生する誤差は、ピッチ区間８０～１５０で評価すればよいと言える。 Mention the response range of the pedometer. The inventor of the present application has experienced the following with respect to the response performance to the walking pitch of the pendulum and acceleration sensor built in the pedometer. In the previous walking experiment, when walking at a pitch of 80 or less, or a pitch of 150 or more, there are rare cases where the pedometer has a strange number of steps, so that it can be clearly noticed. That is, it is considered that the sensor is not responding correctly. Considering the walking pitch when walking as a natural physical activity, it can be said that the error generated when the arithmetic expression is simplified may be evaluated in the pitch sections 80 to 150.
上記の点から表１を見直すと、ピッチ区間７０～１６０での１分割の回帰式は、ピッチ８０以上において誤差は約２％以下であるから、他と比較しても十分に実用性がある。誤差をより小さくする、換言すると、実用上の正確さをより追求するか、あるいは、演算構造をより単純化して経済的に安価にするかは、設計上のトレードオフである。従って、上に説明してきた演算構造の単純化の方法は、製品設計で演算方式を検討する場合に、選択の範囲を拡げる大きな効果があると言える。 Reviewing Table 1 from the above points, the regression equation for one division in the pitch sections 70 to 160 is sufficiently practical compared to the other because the error is about 2% or less when the pitch is 80 or more. . It is a design trade-off to make the error smaller, in other words, to pursue more practical accuracy, or to simplify the arithmetic structure and make it economically cheaper. Therefore, it can be said that the method of simplifying the calculation structure described above has a great effect of expanding the selection range when the calculation method is examined in product design.
以上に歩行ピッチから歩行速度を求める演算方法について詳しく述べた。ピッチ区間を通して区分二次関数を回帰分析して得られる１つの回帰直線を用いる演算は、最も単純化された方法である。ピッチ区間８０～１５０で回帰分析して得られた回帰式を用いた具体的な演算式は次の数式８となる。 The calculation method for obtaining the walking speed from the walking pitch has been described in detail above. The operation using one regression line obtained by regression analysis of a piecewise quadratic function through the pitch interval is the simplest method. A specific calculation formula using a regression formula obtained by regression analysis in the pitch sections 80 to 150 is expressed by the following formula 8.
Figure JPOXMLDOC01-appb-M000009
Figure JPOXMLDOC01-appb-M000009
数式８で歩行速度Ｖを求め、これを数式２に適用して運動強度Ｍが求められる。数式２および数式８は、実用上の誤差を保って単純化された演算式である。本願発明者が、公知の数値と十分な検討を重ねて導き出した２つの区分線形関数に基づいて単純化された演算式である。２つの区分線形関数は本発明の基準とする関数である。１つは歩行速度と運動強度の関係を定め、もう１つは、歩行ピッチと歩幅（詳しくは歩幅の身長比）の関係を定める。 The walking speed V is obtained by Equation 8, and this is applied to Equation 2 to obtain the exercise intensity M. Equations 2 and 8 are simplified arithmetic expressions while maintaining practical errors. This is a simplified arithmetic expression based on two piecewise linear functions derived by the inventors of the present invention through well-known numerical values and sufficient examination. The two piecewise linear functions are the functions that are the basis of the present invention. One defines the relationship between walking speed and exercise intensity, and the other defines the relationship between walking pitch and stride (specifically, stature height ratio).
前者の区分線形関数は、特定の歩数計利用者に限らず不特定多数の利用者に適用できる。一方、後者の区分線形関数は、中間ピッチ区間と歩幅変化の少なくなる下方および上方ピッチ区間における歩数計利用者の歩行特性を決めるいくつかのパラメータを持つ。これらのパラメータの値を決めることによって、後者の区分線形関数の形が具体的に決定される。そして、歩行特性に応じた歩幅がより正確に算出できる。その結果、歩行速度もより正確に算出できることになる。従って、身長や体重の設定の他に、歩数計利用者の歩行特性に合わせた歩行特性パラメータを、歩数計に設定出来るようにすることで、より正確な歩行関連情報が得られる。 The former piecewise linear function can be applied not only to a specific pedometer user but also to an unspecified number of users. On the other hand, the latter piecewise linear function has several parameters that determine the walking characteristics of the pedometer user in the intermediate pitch section and in the lower and upper pitch sections where the step change is small. By determining the values of these parameters, the shape of the latter piecewise linear function is specifically determined. Then, the stride according to the walking characteristics can be calculated more accurately. As a result, the walking speed can be calculated more accurately. Therefore, in addition to setting the height and weight, more accurate walking related information can be obtained by allowing the pedometer to set a walking characteristic parameter that matches the walking characteristic of the pedometer user.
しかし、歩行特性パラメータは、身長、体重のように日常で扱う数値ではないため、設定が煩雑で構造が複雑となる。実用上の正確さ保ち、経済的に安価な汎用の歩数計を設計する場合は、歩行特性パラメータを設定する構造は不利である。数式８は、この問題を解決するために、特性パラメータを代表的な数値に固定し、演算構造の大幅な単純化を行って得た演算式である。この代表値とは、一般的に使われている公知の数値や本願発明者の歩行実験結果などに基づき導きだした、次の固定値である。これらの数値は、以上の説明でもたびたび使用した。
下限ピッチＮ１（歩／分）：７０
普通歩行ピッチＮ２（歩／分）：９５
速歩ピッチＮ３（歩／分）：１２５
上限ピッチＮ４（歩／分）：１６０
普通歩幅係数Ｓ２：０．４０
速歩歩幅係数Ｓ３：０．４５
下方傾き係数Ｋ１：０．５０
上方傾き係数Ｋ４：０．５０ However, since the walking characteristic parameter is not a numerical value that is handled daily like height and weight, the setting is complicated and the structure is complicated. When designing a general-purpose pedometer that maintains practical accuracy and is economically inexpensive, the structure for setting the walking characteristic parameter is disadvantageous. In order to solve this problem, Formula 8 is an arithmetic expression obtained by fixing characteristic parameters to representative numerical values and greatly simplifying the arithmetic structure. This representative value is the following fixed value derived based on commonly used numerical values or the results of walking experiments conducted by the inventors of the present application. These numbers were often used in the above explanations.
Lower limit pitch N1 (steps / minute): 70
Normal walking pitch N2 (steps / minute): 95
Rapid walking pitch N3 (steps / minute): 125
Maximum pitch N4 (steps / minute): 160
Normal stride factor S2: 0.40
Rapid walking stride coefficient S3: 0.45
Downward slope coefficient K1: 0.50
Upward slope coefficient K4: 0.50
歩数計利用者が上記の固定値から離れた歩行特性である時に、数式８で算出された歩行速度と、それを数式２に適用して得られる運動強度とに生ずる誤差は、演算式の単純化（近似）と歩行特性パラメータの固定化による両方の誤差を含む総合誤差である。つまり、単純化された演算式を採用した場合の歩数計の構造上の誤差である。そして、歩数計が提供する歩行関連情報の正確さ、即ち、実用性能を決定することになる。従って、この総合誤差の検証は不可欠である。 When the pedometer user has a walking characteristic away from the above fixed value, the error that occurs between the walking speed calculated by Equation 8 and the exercise intensity obtained by applying it to Equation 2 is a simple equation. This is a total error that includes both errors due to the conversion (approximation) and the fixation of the walking characteristic parameters. That is, it is an error in the structure of the pedometer when a simplified arithmetic expression is adopted. Then, the accuracy of the walking related information provided by the pedometer, that is, the practical performance is determined. Therefore, verification of this total error is essential.
そこで、歩数計利用者の歩き方、つまり歩行特性の違いを、歩行特性パラメータを変化させることによってシミュレートし、固定値による数式８で求めた歩行速度Ｖ（ｋｍ／時）と、これを数式２に適用して求めた運動強度Ｍ（メッツ）との誤差を評価する。誤差評価の基準値は、本発明で基準とする区分線形関数の関数値である。運動強度の基準値は、図１に示される区分線形関数に基づく。歩行速度の基準値は、歩行特性パラメータを変化させた時の、数式４、数式５、数式６、および数式７を用いた演算に基づく時速換算値である。歩行特性パラメータの固定値からの変化は、次の表２の通りである。尚、身長はＬ＝１７０ｃｍとしている。 Therefore, the walking speed of the pedometer user, that is, the difference in walking characteristics, is simulated by changing the walking characteristics parameter, and the walking speed V (km / hour) obtained by Formula 8 using a fixed value is calculated. The error from the exercise intensity M (mets) obtained by applying to 2 is evaluated. The reference value for error evaluation is a function value of a piecewise linear function used as a reference in the present invention. The reference value of the exercise intensity is based on the piecewise linear function shown in FIG. The reference value of the walking speed is an hourly speed converted value based on calculations using Equation 4, Equation 5, Equation 6, and Equation 7 when the walking characteristic parameter is changed. The change of the walking characteristic parameter from the fixed value is as shown in Table 2 below. The height is L = 170 cm.
Figure JPOXMLDOC01-appb-T000010
Figure JPOXMLDOC01-appb-T000010
説明の都合上、３種類の特性パラメータ（Ｎ２，Ｎ３）、（Ｓ２，Ｓ３）、（下傾，上傾）を（Ｎ）、（Ｓ）、（傾）と略して表す。ここで、上記の特性パラメータの変化幅に関して説明する。（傾）で定めた固定値の５０％は、この特性パラメータに関する公知の数値が見つからないため、０％と１００％の平均値とした。このため変化幅をあえて大きく５０％（率で１００％）とした。（Ｎ）の１０は、１０／１１０（＝９５と１２５の平均値）で約１０％である。（Ｓ）の変化幅の２％は、２／４２．５（＝４０と４５の平均値）で約５％である。決して小さい値ではない。この２％の変化幅では、身長Ｌ＝１７０ｃｍに対して、４５％歩幅：７６．５ｃｍ、４７％歩幅：７９．９ｃｍとなる。身長が１７２ｃｍの本願発明者の歩行経験からも小さな変化幅ではない。 For convenience of explanation, three types of characteristic parameters (N2, N3), (S2, S3), and (downward tilt, upward tilt) are abbreviated as (N), (S), and (tilt). Here, the change width of the characteristic parameter will be described. 50% of the fixed value determined by (tilt) was set to an average value of 0% and 100% because a known numerical value for this characteristic parameter was not found. For this reason, the range of change is deliberately set to 50% (100% in rate). 10 of (N) is about 10% at 10/110 (= average value of 95 and 125). 2% of the variation width of (S) is about 5% at 2 / 42.5 (= average value of 40 and 45). It is never a small value. At the change width of 2%, the height L = 170 cm is 45% stride: 76.5 cm and 47% stride: 79.9 cm. It is not a small change width from the walking experience of the inventor of this application whose height is 172 cm.
１種類の特性パラメータを変化させる時は、残り２種類は固定値にフィックスさせて、誤差の数値検証を行った。表３は（Ｎ）を、表４は（Ｓ）を、表５は（傾）を固定値から上表２の４組の数値に変化させた時の検証結果である。これらの表は、歩行速度の演算値とこの演算値の誤差、そして、運動強度の演算値とこの演算値の誤差を示す。誤差は、数式８（あるいは数式８と数式２）の演算値から基準値を減じ、その結果を基準値で割り算をして％で表している。また、誤差を概数で捉えるために、小数点第１位を四捨五入している。尚、運動強度の演算値は、安静時の１メッツ分を含む。 When changing one type of characteristic parameter, the remaining two types were fixed to fixed values, and numerical verification of the error was performed. Table 3 shows the verification results when (N), Table 4 (S), and Table 5 (inclination) are changed from the fixed values to the four sets of values in Table 2 above. These tables show the calculated value of walking speed and the error of this calculated value, and the calculated value of exercise intensity and the error of this calculated value. The error is expressed in% by subtracting the reference value from the calculated value of Equation 8 (or Equation 8 and Equation 2) and dividing the result by the reference value. In addition, the first decimal place is rounded off in order to capture the error as an approximate number. In addition, the calculated value of exercise intensity includes 1 Mets at rest.
Figure JPOXMLDOC01-appb-T000011
Figure JPOXMLDOC01-appb-T000011
Figure JPOXMLDOC01-appb-T000012
Figure JPOXMLDOC01-appb-T000012
Figure JPOXMLDOC01-appb-T000013
Figure JPOXMLDOC01-appb-T000013
表３、表４、および表５から、歩行速度演算値の誤差と運動強度演算値の誤差は、次の表６に集約される。 From Table 3, Table 4, and Table 5, the error of the walking speed calculation value and the error of the exercise intensity calculation value are summarized in the following Table 6.
Figure JPOXMLDOC01-appb-T000014
Figure JPOXMLDOC01-appb-T000014
表６の集約結果から、誤差が±５％以内の区間は、普通歩行ピッチＮ２＝９５、速歩ピッチＮ３＝１２５と固定して定めた中間ピッチ区間をほぼカバーし、誤差が±６％で完全にカバーしている。また、区間８０～１５０では、歩行速度の誤差は±１０％以内、運動強度の誤差は、表４に示すように一部区間１４０～１５０を除いて、±１２％以内である。運動強度の誤差が、この区間で拡大している理由は次のように考えられる。パラメータＳ３が、４５％→４７％もしくは４３％に変化することで発生する歩行速度演算誤差は、表４に示されるように、５％ないし６％と小さい。しかし、図１から分かるように、歩行速度の演算値が、６．４～７．２ｋｍ／時に在るときは、傾きが最大（２０／８＝２．５）の直線式を用いて運動強度を演算するため、運動強度の誤差が２．５倍に拡大する。このことが、運動強度の誤差拡大の原因と考えられる。 From the aggregated results in Table 6, the section with error within ± 5% almost covers the intermediate pitch section fixed with normal walking pitch N2 = 95 and fast walking pitch N3 = 125, and the error is ± 6% and complete Covered. In the sections 80 to 150, the walking speed error is within ± 10%, and the exercise intensity error is within ± 12% except for some sections 140 to 150 as shown in Table 4. The reason why the error of the exercise intensity is enlarged in this section is considered as follows. As shown in Table 4, the walking speed calculation error that occurs when the parameter S3 changes from 45% to 47% or 43% is as small as 5% to 6%. However, as can be seen from FIG. 1, when the calculated value of walking speed is 6.4 to 7.2 km / hour, exercise intensity is calculated using a linear equation with the maximum inclination (20/8 = 2.5). Therefore, the error of the exercise intensity is expanded by 2.5 times. This is considered to be the cause of the error expansion of exercise intensity.
上記の検証は、変化させる特性パラメータを１種類のみとした場合である。３種類を同時に、かつ、各種類の２つのパラメータも同時に変化させた時の誤差も検証している。この時は、同時変化であるため、変化幅を上記の１／２とし、４×４×４-＝６４通りの組み合わせで同様の数値検証を行った。歩行速度の誤差に関しては、上記の集約結果と概ね同じ結果を得た。運動強度の誤差に関しては、区間８０～１５０で誤差が±１０％以下となる組み合わせが３６通りで、残りの２８通りは、一部区間１４０～１５０で誤差が±１０％を超える。２８通りの内訳は、誤差が±１０％を超え±１２％以下が１４通り、±１２％を超え±１５％以下が８通り、±１５％超える組み合わせが６通りであった。 The above verification is a case where only one type of characteristic parameter is changed. The error when three types are changed at the same time and two parameters of each type are simultaneously changed is also verified. At this time, since it is a simultaneous change, the change range was set to the above ½, and the same numerical verification was performed with 4 × 4 × 4− = 64 combinations. About the error of walking speed, the result almost the same as the above-mentioned aggregation result was obtained. Regarding the error in the exercise intensity, 36 combinations have an error of ± 10% or less in the sections 80 to 150, and the remaining 28 patterns have an error exceeding ± 10% in some sections 140 to 150. The breakdown of 28 patterns was 14 patterns with errors exceeding ± 10% and ± 12% or less, 8 patterns exceeding ± 12% and ± 15% or less, and 6 combinations exceeding ± 15%.
誤差が±１５％を超える６通りの組み合わせを（Ｎ）、（Ｓ）、（傾）、誤差の順に示す。
（１００，１２０）、（３９，４６）、（２５もしくは７５，７５）　±２３％以内
（１００，１２０）、（４１，４６）、（２５もしくは７５，７５）　±１８％以内
（　９０，１２０）、（３９，４６）、（２５もしくは７５，７５）　±１７％以内
誤差拡大の理由は、２３％の組では、中間ピッチ区間が狭くなり（３０→２０）、同区間の歩幅補正関数の傾きが大きくなり（５／３０→７／２０）、さらに上方ピッチ区間での傾きも大きくなり（５／３０×５０％→７／２０×７５％）、その結果、固定値からの乖離が大きくなったことが主な原因である。上記の運動強度演算の直線式の傾きによる誤差拡大も重なっている。下の組も同様の理由である。これらは、数値検証下での組み合わせである。これらの組み合わせでは、上方ピッチ区間での歩幅増加が尋常ではなく、歩行速度も時速７ｋｍを超える演算結果であり、自然な歩行とは言い難い。従って、これらの組み合わせは、誤差の評価対象から除いてもよいと考えられる。 Six combinations with an error exceeding ± 15% are shown in the order of (N), (S), (tilt), and error.
(100,120), (39,46), (25 or 75,75) within ± 23% (100,120), (41,46), (25 or 75,75) within ± 18% (90,120 ), (39, 46), (25 or 75, 75) within ± 17% The reason for the error expansion is that in the group of 23%, the intermediate pitch section becomes narrow (30 → 20), and the step correction function of the same section The slope increases (5/30 → 7/20), and the slope in the upper pitch section also increases (5/30 × 50% → 7/20 × 75%). As a result, the deviation from the fixed value is large. This is the main cause. The error expansion due to the linear inclination of the exercise intensity calculation also overlaps. The lower group has the same reason. These are combinations under numerical verification. In these combinations, the increase in the stride in the upper pitch section is not normal, and the walking speed is a calculation result exceeding 7 km / h, and it is difficult to say that it is natural walking. Therefore, it is considered that these combinations may be excluded from the error evaluation target.
以上に、本発明の、数式８で演算される歩行速度と、その結果を数式２に適用して演算される運動強度の値に含まれる誤差（総合誤差）を詳細に数値検証した。１つのパラメータのみを変化させる検証と、３つを同時に変化させる検証の２種類である。２種類の検証結果を総合評価する。上で示した６通りの極端な組み合わせを除いて次の結論を得る。 As described above, the walking speed calculated by Expression 8 of the present invention and the error (total error) included in the value of exercise intensity calculated by applying the result to Expression 2 were numerically verified in detail. There are two types of verification: only one parameter is changed, and three are changed simultaneously. Comprehensive evaluation of two types of verification results. The following conclusion is obtained except for the six extreme combinations shown above.
表３、表４および表５から分かるように、本発明で実用上の誤差として定めた±５％、±１０％以内の区間はもちろん存在する。結論を最大公約数的に示すと、歩行速度および運動強度の誤差は、区間９０～１３０では、±６％以内であり、区間８０～１５０では、大半の組み合わせで、±１２％以内である。±１２％を超えるのは、運動強度の演算値の誤差のみであり、区間１４０～１５０で発生している。１４０以上の歩行ピッチは、相当速いピッチである。このピッチで歩行を続けることは容易ではなく、大多数の歩数計利用者は、このピッチ以下の歩行と考えられる。以上より、単純化された数式８、または数式８と数式２を組み合わせることは、演算構造を大幅に単純化できるだけでなく、最初に言及した、歩行関連情報に関する実用上の誤差±５～１０％程度と概ね一致することになる。従って、十分に実用性があると結論付けることが出来る。 As can be seen from Table 3, Table 4 and Table 5, there are of course sections within ± 5% and ± 10% defined as practical errors in the present invention. When the conclusion is expressed in the greatest common divisor, the error of walking speed and exercise intensity is within ± 6% in the sections 90 to 130, and within ± 12% in most combinations in the sections 80 to 150. What exceeds ± 12% is only an error in the calculated value of the exercise intensity, which occurs in the sections 140 to 150. A walking pitch of 140 or more is a considerably fast pitch. It is not easy to continue walking at this pitch, and the majority of pedometer users are considered walking below this pitch. As described above, the combination of the simplified formula 8 or the formula 8 and the formula 2 not only greatly simplifies the calculation structure, but also the practical error about walking related information mentioned above ± 5 to 10% It will generally agree with the degree. Therefore, it can be concluded that there is sufficient practicality.
歩行関連情報の歩行距離、エクササイズ、消費カロリーまたは脂肪燃焼量などは、歩行速度、運動強度に、計測された歩行時間（歩行関連情報を提供する歩数計では一般に時計機能が内蔵されており、誤差が無視出来る正確な時間情報が得られる）や体重設定値、定数など誤差のない値が乗算されるだけである。従って、歩行関連情報の誤差も上記と変わらないことは言うまでもない。 The walking distance, exercise, calories burned or fat burning amount of walking related information is the walking speed, exercise intensity, measured walking time (the pedometer that provides walking related information generally has a built-in clock function, Can be ignored, accurate time information that can be ignored), weight setting values, constants, etc. are simply multiplied. Therefore, it goes without saying that the error of the walking related information is not different from the above.
数式８と数式２を用いた数値検証の最後に、もう１つ興味ある数値検証結果を示す。本願発明者の図２の歩行実験データから、歩行特性パラメータを決定し、上記と同じ誤差検証を行って得た結果である。図２の歩行ピッチ８０～１５０までのデータを用いて、歩行特性パラメータＮ２、Ｎ３、Ｓ２、Ｓ３、Ｋ１およびＫ４を決定する。本願発明者の場合は、図２からＮ２＝１００、Ｎ３＝１２５と読み取れる。Ｎ１＝８０、Ｎ４＝１５０として、実験データから、３つの区間の直線を定める。これは、回帰分析の計算ソフトを使って傾きと切片を得た。これらの直線から、Ｓ２＝４０％、Ｓ３＝４５％、Ｋ１＝３３％、Ｋ４＝４％が得られた。このパラメータを用いた数値検証結果は、歩行速度に関しては、８０～１４０で誤差が±２％以下、８０～１５０で±４％以下、運動強度に関しては、８０～１３５で±４％以下、８０～１５０で±８％以下であった。尚、身長は本願発明者のＬ＝１７２ｃｍに変更して、数値検証を行った。 At the end of the numerical verification using Equation 8 and Equation 2, another interesting numerical verification result is shown. This is a result obtained by determining the walking characteristic parameter from the walking experiment data of FIG. 2 of the present inventor and performing the same error verification as described above. The walking characteristic parameters N2, N3, S2, S3, K1 and K4 are determined using the data of the walking pitches 80 to 150 in FIG. In the case of the present inventor, it can be read from FIG. 2 that N2 = 100 and N3 = 125. Assuming that N1 = 80 and N4 = 150, three straight lines are determined from the experimental data. This obtained the slope and intercept using the calculation software of regression analysis. From these straight lines, S2 = 40%, S3 = 45%, K1 = 33%, and K4 = 4% were obtained. The numerical verification results using this parameter show that the walking speed is 80 to 140, the error is ± 2% or less, the 80 to 150 is ± 4% or less, and the exercise intensity is 80 to 135, ± 4% or less, 80 It was ± 8% or less at ˜150. The height was changed to L = 172 cm of the present inventor, and numerical verification was performed.
本願発明者の歩き方（歩行特性）は、決して極端に偏った歩き方ではない。代表的な歩き方だと言うつもりはないが、他の多くの者と同様に、無理のない自然な歩行である。歩行特性パラメータの分布があるのなら、その分布の中央からそれほど外れてはいないと考える。このような本願発明者の歩行特性パラメータを用いた場合の誤差は、上記のように全く問題はない。この最後に示した数値検証結果からも、数式２と代表値に固定した数式８による演算方式の実用性が十分に証明できたと考える。 The inventor's way of walking (walking characteristics) is by no means an extremely biased way of walking. I'm not going to say it's a typical way to walk, but, like many others, it's a natural gait. If there is a distribution of walking characteristic parameters, we think that it is not so far from the center of the distribution. Such an error when using the walking characteristic parameter of the present inventor has no problem as described above. From the numerical verification results shown at the end, it is considered that the practicality of the calculation method based on Formula 2 and Formula 8 fixed to the representative value has been sufficiently proved.
歩数計利用者の歩行特性に合わせた歩行特性パラメータを歩数計に設定出来るようにすることで、より正確な歩行関連情報を提供できることは明らかである。経済的に安価であることよりも、歩行関連情報がより正確で付加機能も豊富である歩数計の設計を行う場合は、歩数計に内蔵させる演算回路は能力の高いものとなるであろう。この場合は、設定された歩行特性パラメータから決定される区分線形関数を単純化することなく、さらに運動強度の区分線形関数も単純化することなく、普通の演算手順で歩行速度と運動強度を演算すればよい。演算上の誤差は発生せず、歩数計利用者の歩行特性が反映された正確な歩行関連情報が得られる。 It is clear that more accurate walking-related information can be provided by allowing the pedometer to set a walking characteristic parameter that matches the walking characteristic of the pedometer user. When designing a pedometer with more accurate walking-related information and abundant additional functions than economically inexpensive, an arithmetic circuit built in the pedometer will have a high capability. In this case, the walking speed and exercise intensity are calculated using the normal calculation procedure without simplifying the piecewise linear function determined from the set walking characteristic parameters and without further simplifying the piecewise linear function of exercise intensity. do it. There is no calculation error, and accurate walking related information reflecting the walking characteristics of the pedometer user is obtained.
しかし、実用上の正確さを持ち、かつ、経済的に安価な汎用の歩数計を設計する場合は、歩行特性パラメータを設定しこれを演算に使うことは困難である。なぜなら、設定回路の容量が増加するだけでなく、汎用の演算回路に、上記と同じ普通の演算手順で歩行速度と運動強度の演算を毎回実施させることは負担が重い。また、設定された歩行特性パラメータを演算初期時にのみ使い、単純化された演算式である回帰直線の傾きと切片を算出し、通常演算時に使うことも困難である。なぜなら、回帰直線の決定には、先に示した二元連立一次方程式を解く必要があり、記憶回路の容量不足が懸念される。従って、歩行特性パラメータの設定は行わず、例えば、歩行速度は代表値で固定して単純化された数式８の採用が、運動強度は単純化された数式２の採用が検討されるであろう。 However, when designing a general-purpose pedometer that has practical accuracy and is economically inexpensive, it is difficult to set a walking characteristic parameter and use it for calculation. This is because not only the capacity of the setting circuit is increased, but it is also burdensome to cause a general-purpose arithmetic circuit to calculate the walking speed and exercise intensity each time using the same normal arithmetic procedure as described above. It is also difficult to use the set walking characteristic parameter only at the initial stage of calculation, calculate the slope and intercept of the regression line, which is a simplified calculation formula, and use it during normal calculation. This is because, in order to determine the regression line, it is necessary to solve the binary simultaneous linear equation shown above, and there is a concern that the capacity of the memory circuit is insufficient. Therefore, the setting of the walking characteristic parameter is not performed. For example, it may be considered to adopt Formula 8 which is simplified by fixing the walking speed with a representative value, and Formula 2 which is simplified for exercise intensity. .
歩行特性パラメータの決定には、例えば本願発明者が行った歩行実験などのような、事前に歩行データを収集する必要があり、確かに煩雑さを伴う。しかし、誤差の改善の点では、歩数計利用者の歩行特性が何らかの方法で反映できることが最善である。特に、数式８のような歩行特性が代表値に固定されて単純化された演算式を採用した経済的に安価で汎用の歩数計に、少ない負担で歩数計利用者の歩行特性が反映できるならば、それは非常に魅力的で価値がある。なぜなら、原理的には、歩行特性の乖離による誤差がなくなり、演算式の単純化による誤差だけとなる。つまり、安価で誤差の少ない理想的な歩数計が提供できるからである。 It is necessary to collect walking data in advance, such as a walking experiment conducted by the inventor of the present application, in order to determine the walking characteristic parameter, which is certainly complicated. However, in terms of improving the error, it is best that the pedometer user's walking characteristics can be reflected in some way. In particular, if the walking characteristic of the pedometer user can be reflected with a small burden on an economically inexpensive and general-purpose pedometer that employs a simplified arithmetic expression in which the walking characteristic is fixed to a representative value as in Expression 8. For example, it is very attractive and worthwhile. This is because, in principle, there is no error due to the difference in walking characteristics, and only an error due to simplification of the arithmetic expression. In other words, it is possible to provide an ideal pedometer that is inexpensive and has few errors.
表３～表５の、歩行速度演算値の誤差および運動強度演算値の誤差を見てみる。この一段目の誤差が参考になる。この誤差は、歩行特性に乖離がなく演算式の単純化による分だけである。誤差は小さく非常に良好である。以下に歩行特性を反映させる方法を説明する。 Look at the errors in the walking speed calculation values and the exercise intensity calculation values in Tables 3 to 5. This first stage error is helpful. This error is only due to the simplification of the arithmetic expression with no deviation in walking characteristics. The error is small and very good. A method for reflecting the walking characteristics will be described below.
その方法は次のような内容である。例えば歩行実験などで得られた歩行データで決定された歩行特性パラメータを、予めプログラムが組み込まれた、例えばパソコンなどに入力する。そして、１つの回帰直線の傾きと切片を出力する。これらが、数式８におけるＮの一次式の係数と定数に置き換わる値となる。歩数計にはこの値を設定値として設定する。こうすることで、歩数計には、最少の負担で、歩数計利用者の歩行特性が反映されることになる。この設定値のデフォルト値は、例えば代表値に固定して求められた数式８のＮの一次式の傾きと切片の値としておく。そして、歩数計利用者の要求に応じて設定できるようにすればよい。必ずしも事前の歩行データ収集と歩行特性パラメータの決定は必要なく、歩数計利用者は、この歩数計の利用に煩雑な思いをしなくてもよい。 The method is as follows. For example, a walking characteristic parameter determined by walking data obtained by a walking experiment or the like is input to a personal computer or the like in which a program is previously incorporated. Then, the slope and intercept of one regression line are output. These are values that replace the coefficients and constants of the linear expression of N in Equation 8. This value is set as a set value for the pedometer. By doing so, the pedometer reflects the walking characteristics of the pedometer user with a minimum burden. The default value of the set value is set to, for example, the slope and intercept value of the linear expression of N in Formula 8 obtained by fixing to a representative value. And what is necessary is just to enable it to set according to a request | requirement of a pedometer user. It is not always necessary to collect walking data and determine walking characteristic parameters in advance, and the pedometer user does not have to worry about using this pedometer.
例えばパソコンなどに組み込まれるプログラムは、先に示した、歩数計利用者の歩行特性パラメータであるＮ２（普通歩行ピッチ）、Ｎ３（速歩ピッチ）、Ｓ２（普通歩幅係数）、Ｓ３（速歩歩幅係数）、Ｋ１（下方傾き係数）、および、Ｋ４（上方傾き係数）、そして、予め決められたＮ１（下限ピッチ）とＮ４（上限ピッチ）とを入力とし、先に説明した、γとδの二元連立一次方程式の係数と定数を演算する。そして、この方程式の２つの解が出力される。これらが１つの回帰直線の傾きと切片である。 For example, the program incorporated in a personal computer or the like is the above-described pedometer user's walking characteristic parameters N2 (normal walking pitch), N3 (fast walking pitch), S2 (normal walking step coefficient), S3 (fast walking step coefficient). , K1 (downward slope coefficient), K4 (upward slope coefficient), and predetermined N1 (lower limit pitch) and N4 (upper limit pitch) as inputs, and the binary of γ and δ described above Calculate the coefficients and constants of simultaneous linear equations. Then, two solutions of this equation are output. These are the slope and intercept of one regression line.
ここで、歩数計利用者の歩行特性を反映させるために、歩数計に備えられる構造について説明する。数式７のＮに関する二次式部分を、分割された区間ごとに回帰分析して得られる回帰直線の回帰式に置き換えることで単純化した。数式８が、１分割の最も単純化された歩行速度演算式である。歩数計は、数式８のＮの一次式の係数と定数が設定できる構造であり、設定値を読み込んで演算できる構造でなければならない。歩数計に備えられる演算式の構造を数式９に示す。線形関数の式に身長Ｌを乗算する最も単純な形となる。 Here, in order to reflect the walking characteristics of the pedometer user, a structure provided in the pedometer will be described. Simplified by replacing the quadratic part of N in Equation 7 with a regression equation of a regression line obtained by regression analysis for each divided section. Formula 8 is the most simplified walking speed calculation formula of one division. The pedometer has a structure in which a coefficient and a constant of a linear expression of N in Expression 8 can be set, and must have a structure in which a set value can be read and calculated. Formula 9 shows the structure of the arithmetic expression provided in the pedometer. This is the simplest form of multiplying the expression of the linear function by the height L.
Figure JPOXMLDOC01-appb-M000015
Figure JPOXMLDOC01-appb-M000015
数式９のＮの一次式の特性を定めるパラメータである係数ｋと定数ｃが、歩数計の設定値となる。この設定値は、歩数計利用者の歩行特性パラメータに基づいて、上述のパソコンなどに組み込まれた、γとδの二元連立一次方程式に関するプログラムで算出される回帰直線の傾きと切片である。上記の本願発明者の歩行特性パラメータ、Ｎ２＝１００、Ｎ３＝１２５、Ｓ２＝４０％、Ｓ３＝４５％、Ｋ１＝３３％、およびＫ４＝４％、下限Ｎ１＝８０、上限Ｎ４＝１５０を入力すると、ｋ＝０．０００３３４、ｃ＝－０．００８８１３が出力される。もちろん、ｋとｃの有効桁数や正負などの扱いは設計上考慮すべき事項である。 A coefficient k and a constant c, which are parameters that determine the characteristics of the linear expression N in Expression 9, are set values for the pedometer. This set value is the slope and intercept of a regression line calculated by a program relating to a binary simultaneous linear equation of γ and δ incorporated in the above-described personal computer based on the walking characteristic parameter of the pedometer user. Enter the above inventor's walking characteristic parameters, N2 = 100, N3 = 125, S2 = 40%, S3 = 45%, K1 = 33%, and K4 = 4%, lower limit N1 = 80, upper limit N4 = 150 Then, k = 0.000334 and c = −0.008813 are output. Of course, the handling of k and c, such as the number of significant digits and the sign, is a matter to be considered in the design.
区分二次関数を２分割、あるいは３分割した場合の、歩数計に備えられる演算式の構造について説明する。まず、２分割の場合を示す。再び本願発明者の歩行特性パラメータを使う。ピッチ区間８０～１５０を、ピッチ１２５で２分割した例を示す。２つの回帰式は、区間８０～１２５で、傾きｋ１＝０．０００３３７、切片ｃ１＝－０．００９１６５、区間１２５～１５０で、傾きｋ２＝０．０００２７７、切片ｃ２＝－０．０００９０５、である。これは上記のプログラムを活用して算出できる。直線としての傾きは漸次非増加であるから、区間判定せず最小値関数（ＭＩＮ）を用いる。回帰式で単純化された演算式は次の通りである。
歩行速度Ｖ（ｋｍ／時）
＝（ＭＩＮ（０．０００３３７・Ｎ－０．００９１６５，
０．０００２７７・Ｎ－０．０００９０５））・Ｌ
また、歩数計に備えられる演算式の構造は次のいずれかとなる。傾きが漸次非増加とは限らないから、漸次非減少の場合には最大値関数（ＭＡＸ）を用いる。２つの回帰直線の傾きと切片（ｋ１、ｃ１）、（ｋ２、ｃ２）、および、ＭＡＸとＭＩＮのいずれかが、歩行速度の演算式の特性を定めるパラメータとなる。そして、これらが設定される。もちろん、次に述べる３分割の演算式と設定の構造を使ってもよい。
傾きが漸次非減少の場合
歩行速度Ｖ（ｋｍ／時）＝（ＭＡＸ（ｋ１・Ｎ＋ｃ１，ｋ２・Ｎ＋ｃ２））・Ｌ
傾きが漸次非増加の場合
歩行速度Ｖ（ｋｍ／時）＝（ＭＩＮ（ｋ１・Ｎ＋ｃ１，ｋ２・Ｎ＋ｃ２））・Ｌ The structure of the arithmetic expression provided in the pedometer when the segmented quadratic function is divided into two or three will be described. First, the case of two divisions is shown. The inventor's walking characteristic parameter is used again. An example in which the pitch sections 80 to 150 are divided into two at the pitch 125 is shown. The two regression equations have a slope k1 = 0.000337 and an intercept c1 = −0.009165 in a section 80 to 125, and a slope k2 = 0.000277 and a section c2 = −0.000905 in a section 125 to 150. . This can be calculated using the above program. Since the slope as a straight line does not gradually increase, the minimum value function (MIN) is used without determining the section. The arithmetic expression simplified by the regression equation is as follows.
Walking speed V (km / h)
= (MIN (0.000337 · N-0.009165,
0.000277 ・ N-0.000905)) ・ L
The structure of the arithmetic expression provided in the pedometer is one of the following. Since the slope does not necessarily increase gradually, the maximum value function (MAX) is used when the inclination does not decrease gradually. The slopes and intercepts (k1, c1) and (k2, c2) of the two regression lines, and any of MAX and MIN are parameters that determine the characteristics of the walking speed calculation formula. These are set. Of course, the following three-part arithmetic expression and setting structure may be used.
When the slope gradually decreases, walking speed V (km / h) = (MAX (k1 · N + c1, k2 · N + c2)) · L
Walking speed V (km / h) = (MIN (k1 · N + c1, k2 · N + c2)) · L
次に、３分割の場合の一般的な演算式を説明する。区分二次関数を回帰分析して、３つの回帰直線が得られる。これらの回帰直線の傾きと切片も、先述のγとδの二元連立一次方程式に関するプログラムを活用して求めることが出来る。回帰直線の傾きが、３つの区間で漸次非減少、あるいは漸次非増加とは限らず、いくつかの組合せとなる。２分割のように単純ではなく、演算式は、次に示す、区間判定の方法が単純であろう。３分割の区分点である分割ピッチを下方からｐ１、ｐ２とする。回帰直線の傾きと切片を、下方から、（ｋ１、ｃ１）、（ｋ２、ｃ２）、（ｋ３、ｃ３）とする。歩数計への設定手順は、例えば、（ｋ１、ｃ１）→ｐ１→（ｋ２、ｃ２）→ｐ２→（ｋ３、ｃ３）となろう。そして、演算式は次のフローで示される。
入口
ステップ１：Ｎ≦ｐ１ならば、ステップ３へ、さもなければステップ２へ
ステップ２：Ｎ≦ｐ２ならば、ステップ４へ、さもなければステップ５へ
ステップ３：歩行速度Ｖ（ｋｍ／時）＝（ｋ１・Ｎ＋ｃ１）・Ｌ　出口
ステップ４：歩行速度Ｖ（ｋｍ／時）＝（ｋ２・Ｎ＋ｃ２）・Ｌ　出口
ステップ５：歩行速度Ｖ（ｋｍ／時）＝（ｋ３・Ｎ＋ｃ３）・Ｌ　出口 Next, a general arithmetic expression in the case of three divisions will be described. Three regression lines are obtained by regression analysis of the piecewise quadratic function. The slopes and intercepts of these regression lines can also be obtained by utilizing the program relating to the above-mentioned binary simultaneous linear equations of γ and δ. The slopes of the regression lines are not necessarily non-decreasing gradually or non-gradual increasing in the three sections, and there are several combinations. The calculation method is not as simple as two divisions, and the method of section determination described below will be simple. The division pitches that are the division points of the three divisions are defined as p1 and p2 from below. Let the slope and intercept of the regression line be (k1, c1), (k2, c2), (k3, c3) from below. The setting procedure for the pedometer will be, for example, (k1, c1) → p1 → (k2, c2) → p2 → (k3, c3). The arithmetic expression is shown in the following flow.
Entrance Step 1: If N ≦ p1, go to Step 3, otherwise go to Step 2 Step 2: If N ≦ p2, go to Step 4, otherwise go to Step 5 Step 3: Walking Speed V (km / hour) = (K1 · N + c1) · L Exit step 4: walking speed V (km / hour) = (k2 · N + c2) · L Exit step 5: walking speed V (km / hour) = (k3 · N + c3) · L exit
区分二次関数を複数の分割区間で回帰分析をして複数の回帰直線が得られる。これらは、新たな区分線形関数を構成する。そして、この区分線形関数に基づいて歩行速度が演算される。この演算方法は、上記の３分割の場合の演算フローを、２分割の場合にも、３分割以上の場合にも、容易に一般化できる。複数の回帰直線の傾きと切片、および区分点を示す分割ピッチを、例えば、下方より順番に（ｋ１、ｃ１）、ｐ１、（ｋ２、ｃ２）、ｐ２、（ｋ３、ｃ３）、ｐ３、（ｋ４、ｃ４）、ｐ４・・・と設定することで、上記の新たな区分線形関数を唯一に定めることが出来る。従って、これらの設定値が、設定順序も含めて、歩行速度の演算式を定めるパラメータとなる。それは、回帰直線パラメータと区分点パラメータである。この設定方法による演算式の定義は、２分割にも、１分割にも適用できる。ありえないピッチ、例えば５００を用いる。２分割では、ｐ２＝５００、１分割では、ｐ１＝５００とするのである。この５００は、パラメータの読み込み終了にも利用される。上記の方法は、すべての分割に対して統一的な設定方法で、歩行速度の演算構造を統一的に定めることができる。この統一された演算方法を後の説明の都合上、ステップ演算法と呼ぶことにする。尚、分割数を増やすと当然誤差は少なくなるが、設定の煩雑さ、演算フローや記憶容量の増大を招くことになる。歩行ピッチに対する歩幅の身長割合の特性は、もともと、３つの歩行ピッチ区間で定めた特性である。従って、分割もこの区間数と同程度までであろう。 A regression analysis is performed on the segmented quadratic function in a plurality of divided sections to obtain a plurality of regression lines. These constitute a new piecewise linear function. Then, the walking speed is calculated based on this piecewise linear function. This calculation method can easily generalize the calculation flow in the case of the above three divisions regardless of whether the calculation flow is two divisions or more than three divisions. For example, (k1, c1), p1, (k2, c2), p2, (k3, c3), p3, (k4) are set in order from the lower side, such as the slopes and intercepts of the regression lines, and the division pitches. , C4), p4... Can uniquely determine the new piecewise linear function. Therefore, these set values are parameters that determine the calculation formula of the walking speed, including the setting order. They are regression line parameters and segment point parameters. The definition of the arithmetic expression by this setting method can be applied to two divisions or one division. An impossible pitch, for example 500, is used. In two divisions, p2 = 500, and in one division, p1 = 500. This 500 is also used for the end of parameter reading. The above method is a uniform setting method for all divisions, and can uniformly determine the calculation structure of walking speed. This unified calculation method will be referred to as a step calculation method for the convenience of later explanation. Increasing the number of divisions naturally reduces the error, but it leads to complicated settings, an increase in calculation flow and storage capacity. The characteristic of the stature height ratio with respect to the walking pitch is a characteristic originally defined in three walking pitch sections. Therefore, the division will be about the same as the number of sections.
歩数計利用者の歩行特性を歩数計に反映させる方法を詳しく説明した。この方法によれば、歩数計の構造上、演算上の負担は僅かである。歩行特性が設定されない場合は、歩行特性パラメータを代表値として算出される回帰直線パラメータがデフォルト値となる。この値による実用上の正確さは、複数分割よりも誤差が大きくなると考えられる１分割（数式８）で行ったいくつもの数値検証結果から確認済みである。歩行特性が設定された場合には、原理上、歩行特性の乖離による誤差はなく、演算式の単純化による誤差のみとなり、誤差は大幅に改善される。このようにして、実用上の正確さを大幅に高めることができ、かつ、構造が単純で経済的に安価な歩数計を創出できることになる。 The method of reflecting the pedometer user's walking characteristics in the pedometer was explained in detail. According to this method, the computational burden is small due to the structure of the pedometer. When the walking characteristic is not set, the regression line parameter calculated with the walking characteristic parameter as a representative value is the default value. Practical accuracy by this value has been confirmed from several numerical verification results obtained in one division (Equation 8), which is considered to have an error larger than that in a plurality of divisions. When the walking characteristic is set, in principle, there is no error due to the deviation of the walking characteristic, only the error due to the simplification of the arithmetic expression, and the error is greatly improved. In this way, a practical accuracy can be greatly increased, and a pedometer that is simple in structure and economical in price can be created.
以上に、歩数計における歩行速度と運動強度の演算方法について詳述した。この演算方法は２つの基準となる区分線形関数に基づいて導き出されている。これらの区分線形関数の区間数や区間での一次式が変わっても、歩数計に限らず活動量計や携帯電話などの携帯機器にも、さらには、歩行運動に限らずジョギングやランニングにも、本願発明の演算方法が適用または応用できることは言うまでもない。 In the above, the calculation method of the walking speed and exercise intensity in the pedometer has been described in detail. This calculation method is derived based on two reference piecewise linear functions. Even if the number of sections of these piecewise linear functions and the linear expression in the sections change, it is not limited to pedometers, but also to portable devices such as activity meters and mobile phones, and also to jogging and running, not limited to walking exercises. Needless to say, the calculation method of the present invention can be applied or applied.
以下に本発明の実施例について図３により説明する。図３は、本発明に係わる最後に説明した単純化された数式９および数式２を用いた歩数計の構成を示すブロック図である。この単純化された数式９および数式２を用いる場合においても、本発明の基準とする２つの区分線形関数を単純化することなく普通の演算手順を用いる場合においても、あるいは、一部を単純化した場合においても、必要とする性能に応じた演算回路が選択される。しかし、いずれの場合も、図３の構成は大幅には変わらない。 Hereinafter, an embodiment of the present invention will be described with reference to FIG. FIG. 3 is a block diagram showing the configuration of the pedometer using the simplified formula 9 and formula 2 described at the end of the present invention. Even in the case where the simplified equations 9 and 2 are used, even in the case where an ordinary calculation procedure is used without simplifying the two piecewise linear functions used as the basis of the present invention, or a part thereof is simplified. Even in this case, an arithmetic circuit corresponding to the required performance is selected. However, in either case, the configuration of FIG. 3 does not change significantly.
最初に、歩行ピッチを演算する単位時間と、各種演算を一巡する演算周期について説明する。ピッチの単位は通常、歩／分であるため、実施例においても単位時間を１分とする。これ以外の時間でも全く問題はない。 First, the unit time for calculating the walking pitch and the calculation cycle for making a round of various calculations will be described. Since the unit of pitch is usually steps / minute, the unit time is also set to 1 minute in the embodiment. There is no problem at other times.
昨今、電子回路を内蔵する民生製品の多くにＭＰＵ（マイクロプロセサ）が搭載されている。ＭＰＵの性能、機能も多岐に渡り、経済性を重視して演算速度の遅いＭＰＵを選択したとしても、上記の単位時間１分は、ＭＰＵにとって十分な時間である。 In recent years, MPU (microprocessor) is mounted on many consumer products incorporating electronic circuits. The performance and functions of the MPU are diverse, and even if an MPU having a low calculation speed is selected with emphasis on economy, the unit time of 1 minute is sufficient for the MPU.
最新の歩数値と単位時間前の歩数値とから歩行ピッチを求め、各種の歩行関連情報の演算処理を行ったとしても、所要時間は１００ｍｓ、２００ｍｓ程度であろう。従って、次の歩数値が得られる１分の単位時間を待つのは、ＭＰＵを遊ばせることになる。そこで、例えば、１／６の１０秒を演算周期とし、演算周期毎の歩数値を、最古を捨て最新を残す形で一定量メモリーする。そして、メモリー内の最新歩数値から単位時間前の歩数値を減算して、当該演算周期での単位時間の歩数値、即ち歩行ピッチとする。このような方法を採れば、ＭＰＵを効率よく活用出来る。 Even if the walking pitch is obtained from the latest step value and the step value before unit time and various kinds of walking related information are calculated, the required time will be about 100 ms and 200 ms. Therefore, waiting for the unit time of 1 minute when the next step value is obtained causes the MPU to play. Therefore, for example, 1/6 of 10 seconds is set as a calculation cycle, and a predetermined amount of memory is stored for the step value for each calculation cycle in such a manner that the oldest is discarded and the latest is left. Then, the step value before unit time is subtracted from the latest step value in the memory to obtain the step value of unit time in the calculation cycle, that is, the walking pitch. By adopting such a method, the MPU can be used efficiently.
ＭＰＵ及びその周辺機能、例えばＲＯＭ（リードオンリーメモリー）やＲＡＭ（ランダムアクセスメモリー）などのメモリー部、入出力部、電源部などは本発明に係わる歩数計の技術とは直接関係しないため、図３には図示していない。演算周期、メモリーなどＭＰＵを念頭に置いて説明を進める。説明上、演算周期を１０秒とする。１秒でも可能であろう。１秒では歩数変化が少ないにもかかわらず、メモリー量が多くなる欠点がある。ただし、歩数計利用者とのインターフェイスである表示部に関しては、１０秒周期は、応答性が悪い。そこで、例えば、１０秒の最初の１秒は演算、残り９秒は表示部の処理などとなろう。 The MPU and its peripheral functions, for example, a memory unit such as a ROM (Read Only Memory) and a RAM (Random Access Memory), an input / output unit, a power supply unit, etc. are not directly related to the pedometer technology according to the present invention. Is not shown. The explanation will proceed with the calculation cycle, memory, etc. in mind. For the sake of explanation, the calculation cycle is 10 seconds. One second would be possible. Although there is little change in the number of steps in 1 second, there is a disadvantage that the amount of memory increases. However, regarding the display unit that is an interface with the pedometer user, the responsiveness is poor in the 10 second period. Therefore, for example, the first 1 second of 10 seconds will be calculated, and the remaining 9 seconds will be processed by the display unit.
図３の１～８の数字を付したブロックについて以下に説明する。その前に、図３の数字を付していないパソコン（プログラム）について説明する。歩数計利用者の歩行特性を歩数計に反映させるために、歩行特性パラメータをパソコンに入力する。そして、パソコンには、数式９の線形関数の傾きと切片に相当する回帰直線パラメータであるｋとｃを出力するプログラム（先述のγとδの二元連立一次方程式に関するプログラム）が組み込まれている。そして、得られた回帰直線パラメータのｋとｃが歩数計に設定値として入力される。このことにより、歩数計の負担を最小限にして、歩数計利用者の歩行特性が反映できることになる。このパソコンは、回帰直線パラメータを求める時にだけ必要であり、実施例の歩数計の利用開始に先立って求めておくのが望ましい。尚、歩行速度演算には、直前に説明した、統一されたステップ演算法を用いる。従って、設定値は、（ｋ１＝ｋ、ｃ１＝ｃ）、ｐ１＝５００である。 The blocks numbered 1 to 8 in FIG. 3 will be described below. Before that, a personal computer (program) without the numerals in FIG. 3 will be described. In order to reflect the walking characteristics of the pedometer user in the pedometer, the walking characteristics parameters are input to the personal computer. The personal computer incorporates a program for outputting k and c, which are regression line parameters corresponding to the slope and intercept of the linear function of Equation 9, (the program relating to the above-mentioned binary simultaneous linear equations of γ and δ). . Then, the obtained regression line parameters k and c are input to the pedometer as set values. This minimizes the burden on the pedometer and reflects the walking characteristics of the pedometer user. This personal computer is necessary only when the regression line parameter is obtained, and it is desirable to obtain the personal computer prior to the start of use of the pedometer of the embodiment. The walking speed calculation uses the unified step calculation method just described. Accordingly, the set values are (k1 = k, c1 = c) and p1 = 500.
設定値記憶部１には、歩行速度と消費カロリー演算に必要となる歩数計利用者の身長Ｌ　（ｃｍ）、歩行特性が反映された回帰直線パラメータｋ１＝ｋとｃ１＝ｃ、区分点パラメータｐ１＝５００、および体重Ｗ（ｋｇ）が、設定値として記憶される。回帰直線パラメータを得るには、歩行データ収集を行って歩行特性パラメータを決定する、パソコンにプログラムをインストールするなどの事前準備が必要となる。この事前準備の手間を考えると、回帰直線パラメータは歩数計利用者の要求に応じて設定できることが望ましい。設定されない場合は、例えば、先述の歩行特性パラメータの代表値から決定された数式８の回帰直線パラメータを、デフォルト値として使えばよい。このデフォルト値は、図示していないＲＯＭに格納され、歩数計の初期化時に設定値記憶部１に移される。そして、設定された時に上書きされる。設定値記憶部１の設定値は、歩数計のバッテリーで保護され消失することはない。 In the set value storage unit 1, the walking speed and the pedometer user's height L (cm) necessary for calculating the calorie consumption, the regression line parameters k1 = k and c1 = c reflecting the walking characteristics, and the segment point parameter p1 = 500 and weight W (kg) are stored as set values. In order to obtain regression line parameters, it is necessary to prepare in advance, such as collecting gait data and determining gait characteristic parameters, and installing a program on a personal computer. Considering the effort of this preparation, it is desirable that the regression line parameter can be set according to the request of the pedometer user. If not set, for example, the regression line parameter of Equation 8 determined from the representative value of the walking characteristic parameter described above may be used as the default value. This default value is stored in a ROM (not shown) and transferred to the set value storage unit 1 when the pedometer is initialized. And when it is set, it is overwritten. The set value in the set value storage unit 1 is protected by the battery of the pedometer and does not disappear.
歩数計測部２は、歩数計の基本機能である歩行運動による歩数の計測部である。振り子式、加速度センサ式などの歩数計測手段は問わない。既存の技術を用いて、規格の誤差内で精度の高い計測部を構成することが可能である。 The step count measurement unit 2 is a step count measurement unit based on walking exercise, which is a basic function of a pedometer. Any step counting means such as a pendulum type or an acceleration sensor type may be used. Using existing technology, it is possible to configure a measurement unit with high accuracy within standard errors.
タイマ３は、１０秒の演算周期毎に起動信号を発信する。この起動信号は歩行ピッチ演算部４に与えられ、当該演算周期が開始する。以下に示す各種演算処理は、当該演算周期での演算処理である。 The timer 3 transmits an activation signal every 10 seconds. This activation signal is given to the walking pitch calculation unit 4, and the calculation cycle starts. Various calculation processes shown below are calculation processes in the calculation cycle.
歩行ピッチ演算部４は、上記起動信号に基づき、歩数計測部２の最新の歩数値データを読み込み、上述した最古の歩数値データを捨て最新の歩数値データを残す形で歩数値データを更新する。そして、最新データから、６データ前（単位時間前）のデータを減算して、当該演算周期での単位時間歩数値、即ち歩行ピッチＮ（歩／分）を得る。 Based on the activation signal, the walking pitch calculation unit 4 reads the latest step count data of the step count measurement unit 2 and updates the step count data in such a manner that the oldest step count data is discarded and the latest step count data is left. To do. Then, the data 6 data before (unit time before) is subtracted from the latest data to obtain the unit time step value, that is, the walking pitch N (steps / minute) in the calculation cycle.
歩行ピッチ演算部４の出力である歩行ピッチＮは、設定値記憶部１に設定された歩数計利用者の身長設定値Ｌ（ｃｍ）、回帰直線パラメータおよび区分点パラメータと共に、歩行速度演算部５に読み込まれる。回帰直線パラメータｋ１とｃ１に続いて区分点パラメータｐ１が読み込まれ、ｐ１＝５００を認識してパラメータの読み込みは終了する。そして、歩行速度Ｖ（ｋｍ／時）が、ステップ演算法に従って演算される。具体的に説明すると、同部５に読み込まれた歩行ピッチＮがｐ１と比較される。Ｎ≦ｐ１＝５００であるから、直ちに演算ステップに進み、Ｎとｋ１が乗算され、これにｃ１が加算され、得られた結果に、同部５に入力の身長設定値Ｌが乗算され、歩行速度Ｖが求められ、演算が終わる。 The walking pitch N that is the output of the walking pitch calculation unit 4 is the walking speed calculation unit 5 together with the height setting value L (cm) of the pedometer user set in the setting value storage unit 1, the regression line parameter, and the segment point parameter. Is read. Following the regression line parameters k1 and c1, the segment point parameter p1 is read, and p1 = 500 is recognized, and the parameter reading ends. Then, the walking speed V (km / hour) is calculated according to the step calculation method. If it demonstrates concretely, the walking pitch N read by the part 5 will be compared with p1. Since N ≦ p1 = 500, the process immediately proceeds to the calculation step, N and k1 are multiplied, c1 is added to this, and the obtained result is multiplied by the input height setting value L in the same part 5 to walk. The speed V is obtained and the calculation is finished.
歩行速度演算部５の出力の歩行速度Ｖは、運動強度演算部６に入力され、数式２に従って運動強度Ｍ（メッツ）が計算される。具体的に説明する。３つの歩行速度Ｖに関する一次式０．４４・Ｖ＋１．３３、０．９４・Ｖ－０．９８、２．０６・Ｖ－８．０３のそれぞれの傾きと切片はＲＯＭに格納されている。同部６に入力された歩行速度Ｖに対するそれぞれの一次式の値を算出する。そして、得られた結果の最大値を運動強度Ｍとして求める。身体活動分のみの時は最大値から１を減算する。 The walking speed V output from the walking speed calculator 5 is input to the exercise intensity calculator 6, and the exercise intensity M (Mets) is calculated according to Equation 2. This will be specifically described. The slopes and intercepts of the linear expressions 0.44 · V + 1.33, 0.94 · V−0.98, and 2.06 · V−8.03 for the three walking speeds V are stored in the ROM. The value of each primary expression with respect to the walking speed V input to the same unit 6 is calculated. Then, the maximum value of the obtained results is obtained as the exercise intensity M. Subtract 1 from the maximum value for physical activity only.
運動強度演算部６の出力である運動強度Ｍは、設定値記憶部１に設定された歩数計利用者の体重設定値Ｗ（ｋｇ）と共に、消費カロリー演算部７に入力される。数式１に従って、実施時間を１（時間）として、１時間相当の消費カロリーＫ（ｋｃａｌ）が演算される。具体的に説明すると、同部７に入力された運動強度Ｍに、同部７に入力された体重設定値Ｗに係数１．０５が乗算された基礎代謝量を乗算する。これが、１時間相当の消費カロリーである。１時間値とする理由は、以下に説明するように、演算周期時間が設計変更されても同部７での演算変更を不要とするためである。尚、上記の基礎代謝量に替えて、係数１．０５を概数の１とする、あるいは、身長、体重の他に性別、年齢が設定でき、これらから公知の計算式で求められる１時間当りの基礎代謝量を用いることもできる。 The exercise intensity M, which is the output of the exercise intensity calculation unit 6, is input to the calorie consumption calculation unit 7 together with the weight setting value W (kg) of the pedometer user set in the set value storage unit 1. According to Equation 1, calorie consumption K (kcal) equivalent to one hour is calculated with an implementation time of 1 (hour). More specifically, the exercise intensity M input to the part 7 is multiplied by the basal metabolic rate obtained by multiplying the weight setting value W input to the part 7 by a coefficient 1.05. This is the calorie consumption equivalent to one hour. The reason for setting the value to 1 hour is that it is not necessary to change the calculation in the same part 7 even if the calculation period is changed in design, as will be described below. In place of the above basal metabolic rate, the factor of 1.05 is an approximate number, or sex and age can be set in addition to height and weight. Basal metabolism can also be used.
当該演算周期で得られた歩行速度演算部５での歩行速度Ｖと、消費カロリー演算部７での消費カロリーＫは、演算表示部８に入力される。消費カロリーＫは１時間相当の値としている。また、歩行速度Ｖも単位は時速であるため、歩行速度Ｖの値は１時間相当の距離である。両者に共通に演算周期時間１／３６０（１０秒）を乗ずることで当該演算周期での値に変換される。また、同部８では、歩行距離や消費カロリーの累計値を表示するため、累計演算も行う。これらの変換演算や累計演算が同部８でＶ、Ｋに対して共通に行われる。歩行速度演算部５や消費カロリー演算部７で個別に変換演算や累計演算を行うよりも構造が単純である。また、演算周期時間が設計変更されても同部８の演算変更のみで済むのでメリットがある。 The walking speed V in the walking speed calculation unit 5 and the calorie consumption K in the calorie consumption calculation unit 7 obtained in the calculation cycle are input to the calculation display unit 8. The calorie consumption K is a value corresponding to one hour. Since the walking speed V is also in units of hourly speed, the value of the walking speed V is a distance corresponding to one hour. By multiplying both by the calculation cycle time 1/360 (10 seconds), it is converted into a value in the calculation cycle. Further, in the same section 8, in order to display a walking distance and a cumulative value of calorie consumption, a cumulative calculation is also performed. These conversion calculation and total calculation are performed in common for V and K in the same section 8. The structure is simpler than when the walking speed calculation unit 5 and the calorie consumption calculation unit 7 individually perform conversion calculation and total calculation. In addition, even if the calculation cycle time is changed in design, there is a merit because only the calculation change in the part 8 is required.
演算表示部８に入力された歩行速度Ｖと消費カロリーＫは、１演算周期前の各累計値に加算される形で更新される。歩行速度Ｖと消費カロリーＫの累計値に１／３６０を乗じて表示データに変換される。 The walking speed V and the calorie consumption K input to the calculation display unit 8 are updated in such a manner that they are added to each cumulative value before one calculation cycle. The cumulative value of the walking speed V and the calorie consumption K is multiplied by 1/360 to be converted into display data.
これらの表示データは、歩行関連情報として、歩数と共に、演算表示部８を介して歩数計利用者が確認することができる。設定値記憶部１の設定値は、同部８にも入力されており、同部８を介して設定値の確認や変更がなされる。 These display data can be confirmed by the pedometer user via the calculation display unit 8 together with the number of steps as walking related information. The setting value in the setting value storage unit 1 is also input to the same unit 8, and the setting value is confirmed or changed via the same unit 8.
最後に、図３の点線で示される内容に関して説明する。運動強度演算部６の出力は運動強度Ｍ（メッツ）である。この値は１時間の身体活動量、即ち、エクササイズ（Ｅｘ）の値そのものである。これに演算周期時間１／３６０（１０秒）を乗ずることで当該演算周期での値に変換できる。さらに、表示の形式としては累計値である。従って、同部６の出力を演算表示部８に直接入力して（同図の横の点線矢印）、上述の歩行距離や消費カロリーと同様に累計演算と変換演算を行えば、エクササイズも歩行関連情報として提供できる。尚、同部８へ入力される歩行速度Ｖと上記の運動強度Ｍを、累計値として扱うだけでなく、本来の即時値として扱うのもよい。同部８で、例えば平均値や最大値に加工して、同部８より表示することは、構造を大幅に変更することなく可能である。 Finally, the contents indicated by the dotted line in FIG. 3 will be described. The output of the exercise intensity calculation unit 6 is exercise intensity M (Mets). This value is the amount of physical activity per hour, that is, the value of exercise (Ex) itself. By multiplying this by the calculation cycle time 1/360 (10 seconds), it can be converted into a value in the calculation cycle. Further, the display format is a cumulative value. Therefore, if the output of the same unit 6 is directly input to the calculation display unit 8 (dotted arrow next to the figure) and the cumulative calculation and conversion calculation are performed in the same manner as the above walking distance and calorie consumption, exercise is also related to walking. Can be provided as information. Note that the walking speed V and the exercise intensity M input to the part 8 may be handled not only as a cumulative value but also as an original immediate value. For example, the average value or the maximum value can be processed by the same unit 8 and displayed from the same unit 8 without significantly changing the structure.
図３の縦の点線矢印について説明する。最初に説明したが、脂肪燃焼量は消費カロリーを所定値７．２で除算するだけで求められる。従って、これを歩行関連情報として表示する場合は、表示される消費カロリーの値を７．２で除算して表示すればよい。 The vertical dotted arrow in FIG. 3 will be described. As explained first, the amount of fat burning can be obtained by simply dividing the calorie consumption by the predetermined value 7.2. Therefore, when displaying this as walking related information, the value of the calorie consumption displayed may be divided by 7.2 and displayed.
歩行は、健康増進、生活習慣病の発症予防などに、気軽に行え、かつ、効果的な運動である。そして、多くの場面で歩行の大切さが力説されている。このようなことから、歩数計を健康管理に活用する利用者が年々増加すると考えられる。本願発明者も、同様の動機から歩行を始め、歩数計にも関心を持つようになった。しかし、従来の歩数計の技術には、歩行関連情報の正確さなどの点で課題があることが分かった。本発明では、この課題の解決方法を理論立てて詳細に丁寧に説明し、直ちに利用できる具体的な技術として提供している。さらに、製品設計において設計目標に応じた技術の選択が出来るように、複数の技術を提供している。以上から、本願発明の産業上の利用可能性は極めて大きいと言える。 Walking is an easy and effective exercise for health promotion and prevention of lifestyle-related diseases. And the importance of walking is stressed in many scenes. For this reason, it is considered that the number of users who use pedometers for health management increases year by year. The inventor of the present application also started to walk from the same motive and became interested in the pedometer. However, it has been found that the conventional pedometer technology has problems in terms of the accuracy of walking related information. In the present invention, the solution to this problem is theoretically explained in detail and provided as a specific technique that can be used immediately. Furthermore, a plurality of technologies are provided so that the technology can be selected according to the design goal in product design. From the above, it can be said that the industrial applicability of the present invention is extremely large.
１　設定値記憶部
２　歩数計測部
３　タイマ
４　歩行ピッチ演算部
５　歩行速度演算部
６　運動強度演算部
７　消費カロリー演算部
８　演算表示部 DESCRIPTION OF SYMBOLS 1 Set value memory | storage part 2 Step count measuring part 3 Timer 4 Walking pitch calculating part 5 Walking speed calculating part 6 Exercise intensity calculating part 7 Consumption calorie calculating part 8 Calculation display part

Claims (6)

  1. 歩数計利用者の身長を設定する設定手段と、歩数計利用者の歩行時の歩数を計測する歩数計測手段と、前記歩数計測手段で計測される単位時間当たりの歩数を歩行ピッチとして算出し、前記歩行ピッチを歩行ピッチに関する補正関数の式に代入して得られる結果と前記設定手段に設定された身長とに基づいて歩行速度を算出する演算手段とを備えた歩数計であって、歩行特性を定める歩行ピッチに関する特性区分線形関数と前記特性区分線形関数に歩行ピッチを乗じて得られる関数を特性区分二次関数とし、前記補正関数は、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間で前記特性区分二次関数に回帰分析を施して得られる１つの回帰直線、もしくは前記特性区分線形関数の複数の区間の少なくとも１つを含む区間を複数に分割した再分割区間ごとに前記特性区分二次関数に回帰分析を施して得られる前記再分割区間ごとの回帰直線、もしくは前記特性区分二次関数、のいずれかであり、かつ、前記特性区分線形関数は、歩行ピッチに対する歩幅の身長に対する割合の変化を前記変化に応じて複数に区分した区間ごとに歩行ピッチに関する一次関数で表した区分線形関数であり、かつ、前記特性区分二次関数を前記補正関数とする場合にあっては、前記特性区分線形関数の前記変化に応じて複数に区分した区間数は３であることを特徴とする歩数計。 A setting means for setting the height of the pedometer user, a step count measuring means for measuring the number of steps during walking of the pedometer user, and calculating the number of steps per unit time measured by the step count measuring means as a walking pitch, A pedometer comprising a calculation means for calculating a walking speed based on a result obtained by substituting the walking pitch into a formula of a correction function relating to the walking pitch and a height set in the setting means, A characteristic piecewise linear function relating to the walking pitch and a function obtained by multiplying the characteristic piecewise linear function by the walking pitch is a characteristic piecewise quadratic function, and the correction function is at least one of a plurality of sections of the characteristic piecewise linear function. A plurality of sections including at least one of a plurality of sections of the characteristic section linear function, or one regression line obtained by performing regression analysis on the characteristic section quadratic function in the section including Each of the divided subdivision sections is either a regression line for each subdivision section obtained by performing regression analysis on the characteristic section quadratic function or the characteristic section quadratic function, and the characteristic section linear The function is a piecewise linear function in which a change in the ratio of the stride height to the walking pitch is divided into a plurality of sections according to the change and is expressed by a linear function related to the walking pitch, and the characteristic classification quadratic function When the correction function is used, the number of sections divided into a plurality according to the change of the characteristic piecewise linear function is three.
  2. 歩数計利用者の身長を設定する設定手段と、前記歩数計利用者の歩行時の歩数を計測する歩数計測手段と、前記歩数計測手段で計測される単位時間当たりの歩数を歩行ピッチとして算出し、前記歩行ピッチを歩行ピッチに関する補正関数の式に代入して得られる結果と前記設定手段に設定された身長とに基づいて歩行速度を算出する演算手段とを備えた歩数計であって、前記補正関数の特性を定めるパラメータが前記設定手段に設定でき、前記歩数計利用者の歩行特性を定める歩行ピッチに関する特性区分線形関数と前記特性区分線形関数に歩行ピッチを乗じて得られる関数を特性区分二次関数とし、前記パラメータは、前記補正関数が直線として定められる場合にあっては、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間で前記特性区分二次関数に回帰分析を施して得られる１つの回帰直線の傾きおよび切片、もしくは前記補正関数が区分線形関数として定められる場合にあっては、前記特性区分線形関数の複数の区間の少なくとも１つを含む区間を複数に分割した再分割区間ごとに前記特性区分二次関数に回帰分析を施して得られる前記再分割区間ごとの回帰直線の傾きおよび切片、並びに隣接区間との区分点、もしくは前記補正関数が前記特性区分二次関数となる場合にあっては、前記特性区分線形関数の区間ごとの直線の傾きおよび切片、並びに隣接区間との区分点、のいずれかであり、かつ、前記特性区分線形関数は、前記歩数計利用者の歩行ピッチに対する歩幅の身長に対する割合の変化を前記変化に応じて複数に区分した区間ごとに歩行ピッチに関する一次関数で表した区分線形関数であり、かつ、前記補正関数が前記特性区分二次関数となる場合にあっては、前記特性区分線形関数の前記変化に応じて複数に区分した区間数は３であることを特徴とする歩数計。 A setting means for setting the height of the pedometer user, a step count measuring means for measuring the number of steps when the pedometer user walks, and a step count per unit time measured by the step count measuring means is calculated as a walking pitch. A pedometer comprising a calculation means for calculating a walking speed based on a result obtained by substituting the walking pitch into an expression of a correction function relating to the walking pitch and a height set in the setting means, A parameter that determines the characteristics of the correction function can be set in the setting means, and a characteristic segmentation linear function relating to the walking pitch that determines the walking characteristics of the pedometer user and a function obtained by multiplying the characteristic segmentation linear function by the walking pitch A quadratic function, and the parameter includes a section including at least one of a plurality of sections of the characteristic piecewise linear function when the correction function is defined as a straight line In the case where the slope and intercept of one regression line obtained by performing regression analysis on the characteristic segmented quadratic function, or when the correction function is defined as a piecewise linear function, a plurality of sections of the characteristic segmented linear function The slope and intercept of the regression line for each subdivision section obtained by performing regression analysis on the characteristic division quadratic function for each subdivision section obtained by dividing the section including at least one into a plurality of subdivision sections, and the division points with adjacent sections Or, when the correction function is the characteristic segmentation quadratic function, the slope of the straight line and the intercept for each section of the characteristic segmentation linear function, and the segmentation point with the adjacent section, and The characteristic segmentation linear function relates to the walking pitch for each section in which a change in the ratio of the stride height to the walking pitch of the pedometer user is divided into a plurality according to the change. If the correction function is the characteristic piecewise quadratic function, the number of sections divided into a plurality according to the change in the characteristic piecewise linear function is A pedometer characterized by being 3.
  3. 前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出する歩数計であって、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であることを特徴とする請求項１に記載の歩数計。 The computing means is further a pedometer for calculating, as exercise intensity, a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, wherein the exercise intensity function is a relationship of exercise intensity to walking speed. Is a function obtained by performing the first operation or the second operation on the current piecewise linear function represented, and the first operation includes a plurality of sections including at least one section of the current piecewise linear function. For each section divided into a new new piecewise linear function composed of a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function, and the second operation is the current piecewise linear function or When the slope of the linear function in the continuous section is gradually non-decreasing, the new section of the new piecewise linear function is a new maximum function that selects the maximum value of the function value of the linear function. Replace with one interval, and when it is gradually non-increasing, replace it with a new one interval as the minimum value function to select the minimum value of the function value, otherwise, subtract one interval from the continuous interval and replace The pedometer according to claim 1, wherein the pedometer is an operation that repeats the second operation until no more can be performed.
  4. 前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出する歩数計であって、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であることを特徴とする請求項２に記載の歩数計。 The computing means is further a pedometer for calculating, as exercise intensity, a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, wherein the exercise intensity function is a relationship of exercise intensity to walking speed. Is a function obtained by performing the first operation or the second operation on the current piecewise linear function represented, and the first operation includes a plurality of sections including at least one section of the current piecewise linear function. For each section divided into a new new piecewise linear function composed of a plurality of regression lines obtained by performing regression analysis on the current piecewise linear function, and the second operation is the current piecewise linear function or When the slope of the linear function in the continuous section is gradually non-decreasing, the new section of the new piecewise linear function is a new maximum function that selects the maximum value of the function value of the linear function. Replace with one interval, and when it is gradually non-increasing, replace it with a new one interval as the minimum value function to select the minimum value of the function value, otherwise, subtract one interval from the continuous interval and replace The pedometer according to claim 2, wherein the pedometer is an operation that repeats the second operation until it becomes impossible.
  5. 前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出し、前記歩行速度と前記運動強度とに歩行時間を乗じて歩行距離とエクササイズとを算出し、前記エクササイズに基礎代謝量を乗じて消費カロリーを算出し、前記歩数計測手段で計測された歩数と併せて前記演算手段で算出された歩行速度、歩行距離、運動強度、エクササイズ、または消費カロリーを表示する表示手段とを備えた歩数計であって、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であり、かつ、前記基礎代謝量は、前記設定手段に設定された身長に加えて設定された体重の値、もしくは前記体重に係数１．０５を乗じた値、もしくは前記設定手段にさらに加えて設定された性別と年齢および前記身長と前記体重とから計算される値、のいずれかであることを特徴とする請求項１に記載の歩数計。 The calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, and calculates a walking distance and exercise by multiplying the walking speed and the exercise intensity by a walking time. Calculating the calorie consumption by multiplying the exercise by the basal metabolic rate, and the walking speed, walking distance, exercise intensity, exercise calculated by the computing means together with the number of steps measured by the step counting means, Or a pedometer comprising a display means for displaying calorie consumption, wherein the exercise intensity function is the first operation or the second operation in the current piecewise linear function in which the relationship of the exercise intensity to the walking speed is expressed. Wherein the first operation is performed on the current piecewise linear function for each section obtained by dividing at least one section of the current piecewise linear function into a plurality of sections. The operation is a replacement with a new new piecewise linear function including a plurality of regression lines obtained by performing a regression analysis, and the second operation is the continuous piece of the current piecewise linear function or the new piecewise linear function. When the slope of the linear function in the interval is gradually non-decreasing, the continuous interval is replaced with one new interval that is the maximum value function for selecting the maximum value of the function value of the linear function. Replace with one new section as the minimum value function for selecting the minimum value of the function value, and if it is neither of them, subtract one section from the continuous section and repeat the second operation until it cannot be replaced. And the basal metabolic rate is a value of weight set in addition to the height set in the setting means, a value obtained by multiplying the weight by a factor of 1.05, or the setting means. Pedometer according to claim 1, characterized in that in addition to the set sex and age and the value calculated from said height and said weight is either.
  6. 前記演算手段ではさらに、前記歩行速度を歩行速度に関する運動強度関数の式に代入して得られる結果を運動強度として算出し、前記歩行速度と前記運動強度とに歩行時間を乗じて歩行距離とエクササイズとを算出し、前記エクササイズに基礎代謝量を乗じて消費カロリーを算出し、前記歩数計測手段で計測された歩数と併せて前記演算手段で算出された歩行速度、歩行距離、運動強度、エクササイズ、または消費カロリーを表示する表示手段とを備えた歩数計であって、前記運動強度関数は、歩行速度に対する運動強度の関係が表された現区分線形関数に第１の操作、または第２の操作を行って得られる関数であり、前記第１の操作は、前記現区分線形関数の区間を少なくとも１つを含んで複数に分割した区間ごとに前記現区分線形関数に回帰分析を施して得られる複数の回帰直線からなる新たな新区分線形関数に置き換える操作であり、前記第２の操作は、前記現区分線形関数もしくは前記新区分線形関数の連続区間を、前記連続区間での線形関数の傾きが漸次非減少のときは、前記連続区間を前記線形関数の関数値の最大値を選出する最大値関数とする新たな１つの区間に置き換え、漸次非増加のときは関数値の最小値を選出する最小値関数とする新たな１つの区間に置き換え、そのいずれでもないときは、前記連続区間から区間を１つ減じ、置き換えが出来なくなるまで前記第２の操作を繰り返す操作であり、かつ、前記基礎代謝量は、前記設定手段に設定された身長に加えて設定された体重の値、もしくは前記体重に係数１．０５を乗じた値、もしくは前記設定手段にさらに加えて設定された性別と年齢および前記身長と前記体重とから計算される値、のいずれかであることを特徴とする請求項２に記載の歩数計。 The calculation means further calculates a result obtained by substituting the walking speed into an expression of an exercise intensity function relating to the walking speed, and calculates a walking distance and exercise by multiplying the walking speed and the exercise intensity by a walking time. And calculating the calorie consumption by multiplying the exercise by the basal metabolic rate, and the walking speed, walking distance, exercise intensity, exercise calculated by the computing means together with the number of steps measured by the step counting means, Or a pedometer comprising a display means for displaying calories burned, wherein the exercise intensity function is a first operation or a second operation based on a current piecewise linear function representing a relationship of exercise intensity to walking speed. Wherein the first operation is performed on the current piecewise linear function for each section obtained by dividing at least one section of the current piecewise linear function into a plurality of sections. The operation is a replacement with a new new piecewise linear function including a plurality of regression lines obtained by performing a regression analysis, and the second operation is the continuous piece of the current piecewise linear function or the new piecewise linear function. When the slope of the linear function in the interval is gradually non-decreasing, the continuous interval is replaced with one new interval that is the maximum value function for selecting the maximum function value of the linear function. Replace with one new section as the minimum value function for selecting the minimum value of the function value, and if it is neither of them, subtract one section from the continuous section and repeat the second operation until it cannot be replaced. And the basal metabolic rate is a value of weight set in addition to the height set in the setting means, a value obtained by multiplying the weight by a factor of 1.05, or the setting means. Pedometer according to claim 2, characterized in that in addition to the set sex and age and the value calculated from said height and said weight is either.
PCT/JP2013/055313 2012-04-20 2013-02-28 Pedometer WO2013157307A1 (en)

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
JP2012110021A JP5237482B1 (en) 2012-04-20 2012-04-20 Pedometer
JP2012-110021 2012-04-20
JP2012-158085 2012-06-27
JP2012158085A JP5180396B1 (en) 2012-06-27 2012-06-27 Pedometer
JP2013-021976 2013-02-07
JP2013021976A JP5249476B1 (en) 2013-02-07 2013-02-07 Pedometer
JP2013-030647 2013-02-20
JP2013030647A JP5291261B1 (en) 2013-02-20 2013-02-20 Pedometer

Publications (1)

Publication Number Publication Date
WO2013157307A1 true WO2013157307A1 (en) 2013-10-24

Family

ID=49383275

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2013/055313 WO2013157307A1 (en) 2012-04-20 2013-02-28 Pedometer

Country Status (1)

Country Link
WO (1) WO2013157307A1 (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2017182705A (en) * 2016-03-31 2017-10-05 京セラドキュメントソリューションズ株式会社 Information processing device, and information processing method
CN111035394A (en) * 2014-09-02 2020-04-21 苹果公司 Body activity and fitness monitor
CN113974568A (en) * 2021-11-09 2022-01-28 重庆火后草科技有限公司 Method for calculating metabolic rate of sleep process based on slope interference removal
US11791031B2 (en) 2019-05-06 2023-10-17 Apple Inc. Activity trends and workouts
US11896871B2 (en) 2022-06-05 2024-02-13 Apple Inc. User interfaces for physical activity information
US11908343B2 (en) 2015-08-20 2024-02-20 Apple Inc. Exercised-based watch face and complications
US11918857B2 (en) 2016-06-11 2024-03-05 Apple Inc. Activity and workout updates
US11931625B2 (en) 2021-05-15 2024-03-19 Apple Inc. User interfaces for group workouts
US11972853B2 (en) 2022-09-23 2024-04-30 Apple Inc. Activity trends and workouts

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002312754A (en) * 2001-04-16 2002-10-25 Tanita Corp Pedometer
JP2006118909A (en) * 2004-10-20 2006-05-11 Matsushita Electric Works Ltd Walking meter
JP2009168792A (en) * 2007-12-21 2009-07-30 Sumitomo Electric Ind Ltd Step computing device, walking distance specifying device, position specifying device, computer program, and step computing method
JP2009301286A (en) * 2008-06-12 2009-12-24 Fujitsu Ltd Portable equipment, stride correction method, information equipment and stride correction program

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002312754A (en) * 2001-04-16 2002-10-25 Tanita Corp Pedometer
JP2006118909A (en) * 2004-10-20 2006-05-11 Matsushita Electric Works Ltd Walking meter
JP2009168792A (en) * 2007-12-21 2009-07-30 Sumitomo Electric Ind Ltd Step computing device, walking distance specifying device, position specifying device, computer program, and step computing method
JP2009301286A (en) * 2008-06-12 2009-12-24 Fujitsu Ltd Portable equipment, stride correction method, information equipment and stride correction program

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111035394A (en) * 2014-09-02 2020-04-21 苹果公司 Body activity and fitness monitor
CN111035394B (en) * 2014-09-02 2023-06-30 苹果公司 Physical activity and fitness monitor
US11798672B2 (en) 2014-09-02 2023-10-24 Apple Inc. Physical activity and workout monitor with a progress indicator
US11908343B2 (en) 2015-08-20 2024-02-20 Apple Inc. Exercised-based watch face and complications
JP2017182705A (en) * 2016-03-31 2017-10-05 京セラドキュメントソリューションズ株式会社 Information processing device, and information processing method
US11918857B2 (en) 2016-06-11 2024-03-05 Apple Inc. Activity and workout updates
US11791031B2 (en) 2019-05-06 2023-10-17 Apple Inc. Activity trends and workouts
US11931625B2 (en) 2021-05-15 2024-03-19 Apple Inc. User interfaces for group workouts
US11938376B2 (en) 2021-05-15 2024-03-26 Apple Inc. User interfaces for group workouts
CN113974568A (en) * 2021-11-09 2022-01-28 重庆火后草科技有限公司 Method for calculating metabolic rate of sleep process based on slope interference removal
CN113974568B (en) * 2021-11-09 2024-03-26 重庆火后草科技有限公司 Slope interference-free method for calculating metabolic rate of sleep process
US11896871B2 (en) 2022-06-05 2024-02-13 Apple Inc. User interfaces for physical activity information
US11972853B2 (en) 2022-09-23 2024-04-30 Apple Inc. Activity trends and workouts

Similar Documents

Publication Publication Date Title
WO2013157307A1 (en) Pedometer
US11417420B2 (en) Optical data capture of exercise data in furtherance of a health score computation
JP5923857B2 (en) Activity meter
US9449365B2 (en) Personalized scaling of graphical indicators
WO2011122203A1 (en) Health management support device, health management support system, and health management support program
EP1972270A1 (en) Method and glucose monitoring system for monitoring individual metabolic response
JP6637693B2 (en) Exercise management method and exercise management device
US20140129177A1 (en) Systems and Methods for Frequency-Based Stride Length Correction in a Pedometer Device
KR102034632B1 (en) A reward system based on walking
JP2014219850A (en) Lifestyle-related diseases improvement support system and control method thereof
CN105493131A (en) Information processing system, program, and information processing method
WO2016088309A1 (en) Advice generation system, advice generation method, and advice generation device
JP5180396B1 (en) Pedometer
JP5249476B1 (en) Pedometer
JP5291261B1 (en) Pedometer
JP5237482B1 (en) Pedometer
JP2002312754A (en) Pedometer
US20170308677A1 (en) Snacking control system, wearable device, snacking control method, and program
JP6639404B2 (en) Weight loss support method, weight loss support program, and weight loss support device
KR101452066B1 (en) Apparatus and method for providing report of body activities
CN107411752A (en) A kind of human body dynamic power monitor
JP2003150717A (en) Lifestyle habit improvement support system
CN115245677A (en) Calculation method and device for heat source consumption, wearable device and storage medium
JP2000321091A (en) Portable electronic equipment
KR20180058956A (en) Samsi seggi walk

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 13778135

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 13778135

Country of ref document: EP

Kind code of ref document: A1