WO2016184418A1 - 体力监测方法和装置 - Google Patents
体力监测方法和装置 Download PDFInfo
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- WO2016184418A1 WO2016184418A1 PCT/CN2016/082746 CN2016082746W WO2016184418A1 WO 2016184418 A1 WO2016184418 A1 WO 2016184418A1 CN 2016082746 W CN2016082746 W CN 2016082746W WO 2016184418 A1 WO2016184418 A1 WO 2016184418A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- 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
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
- A61B5/221—Ergometry, e.g. by using bicycle type apparatus
- A61B5/222—Ergometry, e.g. by using bicycle type apparatus combined with detection or measurement of physiological parameters, e.g. heart rate
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- A—HUMAN NECESSITIES
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- A—HUMAN NECESSITIES
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- A61B5/48—Other medical applications
- A61B5/4869—Determining body composition
- A61B5/4881—Determining interstitial fluid distribution or content within body tissue
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- A—HUMAN NECESSITIES
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- A61B5/6802—Sensor mounted on worn items
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- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
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- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
Definitions
- the present invention relates to an exercise assisting device, and more particularly to a physical force monitoring device capable of displaying a user's physical strength, and capable of issuing a notification reminder under certain circumstances.
- a physical strength monitoring device includes: a sensor module for sensing physiological signals; a user interface for receiving biological information; a storage device for storing biological information and at least one mathematical model; and a processing module for executing at least one mathematical model To operate the following: evaluate anaerobic energy and aerobic energy based on physiological signals and biological information; combine anaerobic energy with aerobic energy and generate physical strength.
- anaerobic energy is related to the accumulation of lactic acid concentration.
- the aerobic energy is related to heat consumption.
- the biological information includes at least one of the following, such as height, weight, age, and gender.
- the sensor module senses at least one of the following: an electrocardiogram signal, heart rate variability, pulse rate, heart rate, breathing pattern, body temperature, blood sugar, blood pressure, glycogen concentration, oxygen concentration, body composition, exercise power, exercise rhythm, speed , altitude and slope.
- the sensor module includes an electrocardiographic sensor capable of sensing a heart rate.
- the user interface includes at least one output device selected from the group consisting of a display screen, a vibrating assembly, or a speaker.
- a belt is included by which the physical strength monitoring device is directly or indirectly fixed to the skin of the user.
- the physical strength monitoring device is fixed to the forehead, wrist, leg or arm of the user by the strap.
- the physical strength value is output together with at least one of the following parameters including heart rate, rate, time, map, temperature, humidity, altitude, calorie expenditure, exercise efficiency, body composition, exercise power, exercise rhythm, speed, altitude, slope gradient,
- the body mass index is either displaced by the maximum motion.
- the user interface outputs a notification when the oxygen-free energy and/or the aerobic energy reaches a threshold.
- the notification is a notification of vibration, a notification of sound, or a notification of visibility.
- the physical strength value can further correspond to a self-inductive fatigue level (RPE) and output at the user interface.
- RPE self-inductive fatigue level
- processing module further evaluates the maximum heat consumption based on the physical strength value and the aerobic energy.
- the displacement information can be provided in real time directly or indirectly.
- processing module further evaluates the maximum motion displacement based on the physical force value and the displacement information.
- the user interface outputs a feasible number of attacks, which can be calculated by the processing module based on the physical strength value or the maximum motion displacement.
- a physical strength monitoring method includes: sensing a physiological signal through a sensor module; receiving biological information from a user interface; and estimating, based on the physiological signal and the biological information, the anaerobic energy and the using a mathematical model stored in the storage module by the processing module Oxygen energy; assessing the physical value based on the oxygen-free energy and the aerobic energy; outputting the physical force value through at least one output device.
- anaerobic energy is related to the accumulation of lactic acid concentration.
- the aerobic energy is related to heat consumption.
- the biological information includes at least one of the following, such as height, weight, age, and gender.
- the sensor module senses at least one of the following: ECG signal, heart rate variability, pulse rate, heart rate, breathing pattern, body temperature, blood sugar, blood pressure, glycogen concentration, oxygen concentration, body composition, exercise power, exercise rhythm, speed , altitude and slope.
- the sensor module includes an electrocardiographic sensor capable of sensing a heart rate.
- the output device is a display screen, a vibration component, or a speaker.
- the physical strength value is output together with at least one parameter including heart rate, rate, time, map, temperature, humidity, altitude, calorie expenditure, exercise efficiency, body composition, exercise power, exercise rhythm, speed, altitude, slope gradient, body
- the mass index is either the maximum motion displacement.
- At least one output device outputs a notification.
- the notification is a notification of vibration, a notification of sound, or a notification of visibility.
- the physical force monitoring method further includes: by the processing module, the physical strength value is corresponding to the level of the RPE; and the level of the RPE is output by the at least one output device.
- the physical force monitoring method further includes evaluating, by the processing module, a maximum heat consumption based on the physical strength value and the aerobic energy.
- the physical force monitoring method further includes obtaining real-time displacement information directly or indirectly from the motion sensor.
- the physical force monitoring method further includes evaluating, by the processing module, a maximum motion displacement based on the physical force value and the displacement information.
- the physical force monitoring method further includes outputting a feasible number of attacks through a user interface, wherein the processing module calculates the feasible number of attacks based on the physical strength value or the maximum motion displacement.
- a physical strength monitoring device includes: a sensor module for sensing physiological signals; a user interface for receiving biological information; a storage device for storing biological information and at least one mathematical model; and a processing module for executing at least one mathematical model To complete the following: evaluate the physical value based on the physiological signal and the biological information; evaluate the exercise assisting information based on the endurance value; send the physical value to the user interface including an output device; and output the physical value through the user interface.
- the processing module further evaluates the maximum calorie expenditure based on the physical strength value and the aerobic energy, wherein the assessment of the aerobic energy is based on the physiological signal and the biological information.
- a motion sensor is included that provides real-time displacement information directly or indirectly, while the processing module further evaluates the maximum motion displacement based on the physical force value and the displacement information.
- the processing module calculates a feasible number of attacks based on the physical strength value or the maximum motion displacement and outputs the feasible number of attacks through the user interface.
- the storage further stores the displacement target, and sends a notification to the user when the maximum motion displacement is lower than the displacement target.
- the output device is a display screen, a vibration component, or a speaker.
- the biological information includes at least one of the following, such as height, weight, age, and gender.
- the sensor module includes an electrocardiographic sensor that senses a heart rate.
- the physical strength value is output together with at least one parameter including heart rate, rate, time, map, temperature, humidity, altitude, calorie expenditure, exercise efficiency, body composition, exercise power, exercise rhythm, speed, altitude, slope gradient, body
- the mass index is either the maximum motion displacement.
- the sensor module senses at least one of the following: ECG signal, heart rate variability, pulse rate, heart rate, breathing pattern, body temperature, blood sugar, blood pressure, glycogen concentration, oxygen concentration, body composition, exercise power, exercise rhythm, speed , altitude and slope.
- the storage module stores the user's biological information
- the processing module processes the information in real time, thereby evaluating the aerobic energy value and the anaerobic energy value, and then the user's physical value.
- the real-time evaluation and output to the user's solution enables users of different physical conditions to obtain reliable physical strength values, so that the user can decide when to increase or decrease the exercise intensity during the exercise.
- Figure 1 is a system block diagram of an exercise assisting device provided by at least one embodiment of the present invention.
- FIGS. 2A and 2B are schematic diagrams of cardiac waveforms caused by signals detected by an electrocardiogram (EKG) signal or sensor, respectively, provided by at least one embodiment of the present invention.
- EKG electrocardiogram
- 3A-3C are schematic illustrations of a typical exercise assisting device provided by an embodiment of the present invention.
- FIG. 4 is a schematic illustration of various exemplary exercise assisting devices provided by another embodiment of the present invention.
- FIG. 5 is a schematic illustration of the corresponding concepts of physical strength and self-inductive grading (RPE).
- Figure 6 is a schematic illustration of the relationship between a typical physical level and the health of a user.
- FIG. 7 is a schematic illustration of a physical strength indicator provided by at least one embodiment of the present invention.
- Figure 8 is a schematic illustration of the correlation between lactic acid concentration and heart rate.
- Fig. 9 is a schematic diagram showing changes in lactic acid concentration during exercise of a user, and correspondence between lactic acid concentration and physical strength.
- FIG. 10 is a flow chart of a method of assessing a body strength value provided by at least one embodiment of the present invention.
- 11 is a schematic illustration of standard conditions for transmitting notifications to a user provided by at least one embodiment of the present invention.
- FIG. 12 is a flow chart of a method of adjusting a physical strength level provided by at least one embodiment of the present invention.
- Figure 13 is a schematic diagram of the physical level automatically matching the typical conditions of Figure 12.
- FIG. 14A and 14B are schematic diagrams showing the relationship between heart rate, lactic acid concentration, and self-inductive fatigue level
- FIG. 14C is a correspondence between physical strength values and self-inductive fatigue levels with respect to lactic acid concentration, in accordance with at least one embodiment of the present invention.
- 15A and 15B are schematic diagrams showing the relationship between the lactic acid concentration and the exercise intensity or the lactic acid concentration and the oxygen consumption.
- Figure 16 is a schematic illustration of a typical application for assessing the user's maximum motion displacement using the user's physical strength and speed of motion.
- 17 is a schematic diagram of a typical application for outputting a user's physical strength value along with a map.
- Figure 18 is a schematic illustration of a typical application for assessing a user's calorie expenditure using the user's physical strength.
- 19 is a method of estimating physical strength values based on physiological data provided by an embodiment of the present invention.
- 20 is a method of assessing anaerobic energy based on physiological data provided by an embodiment of the present invention.
- 21 is a method of assessing aerobic energy based on physiological data provided by an embodiment of the present invention.
- FIG. 23 is a diagram of a method of adjusting an anaerobic assessment setting to assess a physical strength value provided by an embodiment of the present invention.
- 24 is a diagram of a method of adjusting aerobic assessment settings to assess a physical strength value provided by an embodiment of the present invention.
- Figure 25 is a diagram of a method for assessing maximum calorie expenditure provided by an embodiment of the present invention.
- Figure 26 is a diagram of a method for assessing all of the maximum motion displacement provided by an embodiment of the present invention.
- Sports aid 100 Sensor module 101 Processing module 102 User Interface 103 Storage module 104 Sports aid with protective cover 300 tape 301 wristband 401 Indicator light 402 smart phone 403 Upper boundary of the strip 202 Lower boundary of the strip 204 Hollow block 206
- FIG. 1 is a system block diagram of an exercise assisting device (also referred to as a physical force monitoring device) provided by at least one embodiment of the present invention.
- the exercise assisting device 100 includes a sensor module 101, a processing module 102, a user interface 103, and a storage module 104.
- the sensor module 101 includes at least one sensor to sense and measure a physiological signal of the user.
- physiological signals include at least one of the following: electrocardiogram (EKG) signals, heart rate variability, pulse rate, heart rate, breathing pattern, body temperature, body composition, blood glucose, blood pressure, glycogen content, and oxygen content.
- EKG electrocardiogram
- the body composition may include the percentage of fat, water and muscle in the body.
- the processing module 102 is computer hardware, such as a microcontroller or microprocessor having an auxiliary circuit that executes instructions of the computer program by performing basic arithmetic, logic, and input/output motion aids.
- the user interface 103 includes at least one output device and/or at least one input device, or any combination thereof.
- This output may be a display, a rocking component or a speaker, or any combination that indicates the user's physical strength during or after exercise.
- the input may be any human interface, such as a touch screen, a sound receiver or a button that can be used to receive user biometric information such as height, weight, age, gender, etc.
- the user interface 103 can be adapted to send information directly to the sensor module 101, the processing module 102, or the storage module 104. The entered information can be processed by the processing module 102 and then sent to the output to let the user know the current physical condition. For example, BMI values, etc.
- the storage module 104 can be any kind of disk or memory for storing information from the sensor module 101, the processing module 102, or the user interface 103.
- the stored information may be a user's activity history or biometric information, and the activity history or biometric information may be used to calculate the basal blood lactic acid concentration, the basal heart rate, the basal oxygen uptake rate, or any of the above. Combine and use this to further calculate the user's physical strength and the user's initial physical strength.
- processing module 102 receives physiological signals from sensor module 101, processes based on physiological signals and instructions stored in storage module 104, and then provides processed information as a result to user interface 103. Additionally, the processing module 102 can receive instructions from the user interface 103 and execute the input instructions and then run the sensor module 101, with or without instructions stored in the storage module 104.
- the sensor module 101, the processing module 102, the user interface 103, and the storage module 104 can be connected to each other in a wired or wireless manner.
- a wired connection is any tangible contact, such as a cable or conductive wire in a printed circuit board. Any form of wireless transmission when connected wirelessly, such as WiFi, Bluetooth, or radio frequencies that assist in transmission.
- FIGS. 2A and 2B are schematic diagrams of cardiac waveforms of at least one embodiment of the present invention, the cardiac waveform diagram being generated by a signal detected by an electrocardiographic signal or an optical sensor.
- the heart rate monitoring sensor in the sensor module 101 of the exercise assisting device 100 may be an electrocardiogram (EKG) sensor.
- the heart rate monitoring sensor in the sensor module 101 of the exercise assisting device 100 may be an optical sensor. Because optical sensors are susceptible to human factors, such as other heart-related signals and body movements that interfere with real heart rate signals, thus reducing the correctness of heart rate readings, when measuring P, Q, R, at different stages of operation of the heart, ECG sensors are considered superior to optical sensors for S and T waves. Among the signals of the ECG sensor, the interference caused by human factors can be distinguished from the PQRST wave, so the interference caused by the removal of human factors can provide an accurate heart rate reading.
- the user's heart rate can be monitored based on time intervals between specific EKG waveforms.
- the time interval between each T wave or R wave is equivalent to the time of each heartbeat.
- the ECG signal measured by the ECG sensor can filter noise, such as T wave, by identifying the specific characteristics of different waveforms themselves, thus preventing human factors from affecting heart rate measurement.
- 3A through 3C are schematic views of a typical exercise assisting device provided by an embodiment of the present invention.
- the exercise assisting device 300 can be a device having a housing that houses at least one or more of the following: a sensor module 101, a processing module 102, a user interface 103, and a storage module 104.
- the exercise assisting device 300 can also be a device having a housing that houses all of the sensor modules 101, processing modules 102, user interfaces 103 and storage modules 104.
- This exercise assisting device 300 can be part of a wearable device that can be worn on a part of a person's body, such as the chest, wrist, arm, or leg, and that senses and measures physiological signals from the body part of the user.
- the exercise assisting device 300 includes a housing that houses a sensor module 101, a processing module 102, a user interface 103, and a storage module 104.
- the exercise assisting device 300 further includes a strap (i.e., an elastic belt) that can be attached to the user's chest and fix the exercise assisting device 300 in the vicinity of the user's heart.
- the sensor module 101 of the exercise assisting device 300 has at least one electrode (for example, two electrodes are connected to the strap), and can sense the user's ECG signal.
- the user wears the exercise assisting device 300 having the strap 301 on the chest, so that the heartbeat signal of the user's heartbeat can be felt.
- the exercise assisting device 300 further includes a vibrating assembly in the housing that transmits a vibration notification to the user based on changes in the physical value of the user during exercise. Again, it is worth noting that the concept of endurance values will be mentioned below.
- FIG. 4 is a schematic illustration of various types of exercise assisting devices in another embodiment of the present invention.
- the exercise assisting device 100 can be separated into a first device and a second device.
- the first device is configured with wireless communication to communicate with the second device.
- the first device includes at least one sensor module 101, a processing module 102, a user interface 103, and a storage module 104. Based on the cooperation of the first device and the second device, the complete function of the exercise assisting device 100 can be fully realized.
- the first device may be a portion of the wearable device 400 that can be worn on a particular part of the body, such as the chest, wrists, arms, waist or legs, and that senses and measures physiological signals of particular parts of the body.
- the second device can be part of an extension device, such as a wristband, bicycle meter, smart phone, sports watch, fitness equipment, or any combination.
- the extension device mentioned above may be a wristband 401 which includes a user interface capable of displaying a user's physical strength within a range, such as from 100% to 0%.
- the extension device mentioned above may also be an indicator light 402 mounted on the back of the bicycle, which can emit different colors or flashes depending on the physical value of the rider.
- the extension device mentioned above may also be a smart phone 403 capable of accepting and processing information, displaying the user's physical strength in the range of 100% to 0%, and even uploading information to the Internet (optional), such as a social network. Or various types of applications.
- Figure 5 is a schematic diagram of the corresponding concept between physical strength and RPE.
- the correspondence between the physical strength value and the self-inductive fatigue level (RPE) is shown.
- the type of RPE can be the Borg Rating.
- the physical value is the result of measuring the real-time exercise intensity. When the fatigue value, blood lactic acid content (lactic acid content in the blood flow), or real-time exercise intensity is lowered, the physical strength value is restored. On the other hand, when the fatigue value, the blood lactate content (lactic acid content in the blood flow), or the real-time exercise intensity increases, the physical strength value decreases.
- Physical strength can be expressed in a certain range, such as 100% to 0%. Additionally, at least a portion of the physical strength value is linearly or nonlinearly related to the RPE value. For example, for a user using the exercise assist device 100, the RPE represents a medium exercise intensity between 11 and 13. That is to say, at this time, the user feels "easy" level of muscle fatigue and breathing, so the RPE value is equivalent to 100% of the physical value between 11 and 13.
- an RPE value between 15 and 17 indicates a higher exercise intensity. That is to say, the user will feel "heavy" muscle fatigue and breathing, so the RPE value is equivalent to 0% of the physical value between 15 and 17.
- the RPE value is linearly or non-linearly proportional to the heart rate, and thus the physical force value is also linearly or non-linearly proportional to the heart rate.
- the physical strength of each user can be normalized according to the maximum heart rate and the minimum heart rate within a fixed range.
- heart rate corresponds to the RPE value and the physical value and is standardized, other physiological signals can be applied according to the same concept.
- the physical value can be a negative value for the automatic adjustment calculation of the physical level, which will be further explained below.
- Figure 6 is a schematic illustration of the relationship between a typical physical level and the user's physical fitness.
- the physical strength values are divided into 10 levels, SC1 to SC10. Different levels of physical strength correspond to a person's different physical strength and endurance. For users with very little exercise, the initial setting of the physical level can be set to category 1 (SC1), while for professional athletes, the initial setting of the physical level can be set for category 10 (SC10).
- SC1 category 1
- SC10 category 10
- the level of physical strength depends on the biometric information input by the user, and can be modified during the exercise according to the user's reaction, more specifically, according to the change in the user's physical strength value.
- the exercise assisting device 100 includes a default database stored in the storage module 104, and determines the user's physical level based on the user's biological information, such as age, gender, weight, height, and user's routine athletic data ( For example: the physical level information stored in the storage module after the user's last exercise). The user can input or retrieve the biological information or routine exercise data (such as the physical level information of the user's last exercise) through the user interface 103.
- the physical strength level can adapt and adjust according to the changes in the user's physical fitness. That is to say, when the user's physical condition is improved, the physical strength value will correspond to the appropriate RPE value based on the user's current physical strength level, so that the user's physical strength value can be accurately reflected.
- the above-mentioned adjustment of the physical level can also be used as an automatic RPE mechanism.
- Figure 7 is a schematic illustration of a physical strength indicator in a particular embodiment of the invention.
- the physical strength value is represented by a bar having an upper boundary 204 and a lower boundary 202 representing physical strength values of 0% and 100%, respectively.
- a bar having an upper boundary 204 and a lower boundary 202 representing physical strength values of 0% and 100%, respectively.
- another graphic (such as a block 206) represents the current physical strength value that is distinguished from the bar by color, shape, or pattern.
- the block 206 changes shape, color or style as the user's current physical strength increases or decreases.
- Upper boundary 204 may correspond to an anaerobic threshold, which is a threshold at which lactic acid in the blood begins to accumulate as a result of motion.
- the lower boundary 202 corresponds to a threshold value when the user feels fatigue due to the lactic acid generated by the movement reaching a certain concentration. Since each user's endurance to different exercise intensities is different, the threshold of each physical level lower boundary 202 can also be different.
- the physical strength value is expressed in the form of a strip in the present embodiment, the representation of the physical strength value is not limited to the strip, that is, various types of visual patterns are also applicable.
- Figure 8 is a graph showing the correlation curve between lactic acid concentration and heart rate.
- the anaerobic threshold corresponding to the upper boundary 204 mentioned in Fig. 7 can be defined as when the exercise intensity is such that the lactic acid concentration reaches 2-6 mmol per liter (about 1 mmol per liter when the rest is not exercised). ).
- a lactic acid concentration of 4 mmol per liter is defined as a 100% physical value, and any concentration below 4 mmol per liter determines that the user's current physical strength is 100%.
- the above-mentioned definition of the anaerobic threshold may also correspond to 65% to 85% of the maximum heart rate.
- the maximum and minimum heart rate of the user is based on the user's age, gender, state of rest during exercise, height and weight.
- a certain slope of the correlation curve between lactic acid concentration and heart rate can be defined as a physical strength value of 100%, and thus replaces the definition of the aforementioned anaerobic threshold.
- the 100% physical value may correspond to the slope of the curve at a point before the steep slope of the curve, which also corresponds to a concentration of 2 to 6 mmol per liter of lactic acid.
- a concentration of 4 mmol per liter of lactic acid is considered to be a threshold between aerobic and anaerobic exercise.
- Oxygen enters muscle tissue through the user's breathing, and muscle tissue provides the energy needed to maintain activity.
- On the anaerobic movement Because of the high exercise intensity, lactic acid is formed, and the formation of lactic acid causes discomfort and fatigue.
- Figure 9 is a schematic diagram showing changes in lactic acid concentration as a function of exercise time as the user moves, and corresponding changes in physical strength.
- the physical strength value of the user of the corresponding physical strength level is set to 100%.
- the lactic acid concentration increases and the physical strength decreases.
- the user's physical strength reaches 0%. That is to say, the user's self-intentional fatigue value is about 15 to 17, and the user may be advised to choose to reduce the exercise intensity to eliminate the accumulated lactic acid, so the physical strength value is restored from 0% to 100% in the time t1 to t2. It is worth noting that in a sport or game, it is not necessary to recover from 0% to 100%, and recovering from 0% to a certain percentage can make the user perform better in the process of passing or playing.
- the value of the lower boundary 202 is a predetermined value that is lowered according to the aforementioned lactic acid concentration during t1 to t2, such as less than 4 mmol per liter. Regardless of the level of physical strength, the time required for full recovery of different users is similar, for example, the physical strength value from 0% to 100% takes about 8 minutes to 12 minutes.
- Figure 10 is a flow diagram of a method for assessing physical strength values in a particular embodiment of the invention.
- step S101 the exercise assisting device 100 first sets the initial physical strength level and physical strength value of the user based on the biometric information of the user or the physical strength level stored in the exercise assisting device 100.
- the stored physical strength level is related to the physical state of the user during the last exercise.
- step S102 the physiological information of the user is acquired by the sensor module 101.
- the physiological information P t may be the current heart rate, the activity intensity, the oxygen consumption, or a combination of any of them.
- step S103 the difference ( ⁇ S) in the physical strength value is calculated based on the physiological information (P t ), the current physical strength value (S t ), the initial physical strength level, and the biological information.
- step S104 S t and ⁇ S are added to calculate the physical strength value S t+1 of the next time.
- step S105 the exercise assisting device 100 alerts the user when the physical strength value increases or decreases to a certain threshold.
- step S106 according to S t+1 (such as the physical strength level from SC3 to SC4), the physical strength level can be adjusted to a higher physical strength level at the current physical strength level.
- the exercise assisting device 100 adjusts to the initial physical strength level to update the stored physical strength information. It should also be noted that during the user's exercise or competition, the exercise assisting device 100 repeatedly performs steps S102 to S106, so that the automatic RPE mechanism can remain effective.
- 11 is a schematic diagram of conditions for transmitting a notification to a user in at least one embodiment of the present invention.
- the exercise assisting device 100 may transmit a notification to the user when the physical strength value is equal to or nearly equal to 0%, or other predetermined value is not higher than 50% or not lower than 50%. For example, send a notification when the physical strength drops to 60%, 30%, or 0%. In addition, notifications can also be sent when the physical strength returns to 30% or 60%.
- the notification can be in any form as long as the user is made aware of the notification.
- a notification can be a sound, visual or vibrating notification.
- the exercise assisting device 100 issues a notification through the user interface 103 to alert the user that the exercise intensity should be lowered to reduce fatigue or alert other health conditions about the user.
- different physical strength values can be set for different types of notifications. For example, when the physical strength drops from 60% to 30%, 3 short vibration notifications are used; when the physical value drops from 30% to 0% of the physical value, a long vibration notification is used; when the physical value is from A short vibration notification is used when the 0% rise reaches 30% of the physical value or the physical value reaches 30% of the physical value.
- FIG. 12 is a flow chart of a method for adjusting a physical strength level in at least one embodiment of the present invention.
- step S201 when the physical strength value falls to a first threshold (or a predetermined value), for example, a physical value of 0%, a notification is sent to the user.
- step S202 if the user lowers the exercise intensity accordingly and the physical strength value begins to return above the first threshold, the current physical strength level is maintained without adjustment and the method ends.
- step S203 if the user ignores the notification of S202 and continues to move until the physical strength value reaches below the second threshold (or predetermined value), for example, a negative 40% physical value, the physical strength level is adjusted to a higher level.
- the physical level for example, adjusting the physical level from SC3 to SC4.
- step S204 if the user ignores S202 and continues to exercise, the physical strength value remains between the first predetermined value and the second predetermined value, for example, between 0% and minus 40% of the physical strength value, and continues to maintain the first value.
- the time period (a predetermined time), for example, 4 to 6 minutes, also adjusts the physical level to a higher physical level (for example, adjusting the physical level from SC3 to SC4).
- the physical strength value is continuously maintained between the first and second predetermined values, but does not exceed the first time period (a predetermined time), the current physical strength level is maintained without adjustment and the method ends.
- each user's physical strength will increase or decrease with exercise intensity.
- different users of different physical strengths will consume different physical strength values.
- the user's physical strength value of 3 (SC3) will be faster than 0% of the physical strength level 5 (SC5), because the user's physical strength is stronger than the physical value of 3.
- the physical strength level can be automatically adjusted to a higher physical strength level.
- Figure 13 is a schematic diagram showing that the physical strength can be automatically adjusted according to the method flow in Figure 12.
- the physical strength level can be automatically adjusted under these two conditions.
- the initial physical strength level SC3 if the user's physical strength reaches below 0%, and the user ignores the notification and continues to exercise until the physical strength reaches below -40%, the user's physical level is automatically Adjust to SC4.
- FIGS. 14A and 14B are diagrams showing the relationship between the concentration of lactic acid and heart rate and RPE, respectively, in at least one embodiment of the present invention
- Fig. 14C is a schematic diagram showing the correspondence between the physical strength value and the lactic acid concentration and RPE.
- the user's heart rate is positively correlated with the lactic acid concentration, and the relationship between the two can be simulated by a linear regression model, a nonlinear regression model, a piecewise function, and other mathematical models or any combination of the above. Therefore, the concentration of lactic acid involved in the accumulation of lactic acid in the blood can be estimated based on the heart rate of the user.
- the lactic acid concentration is also positively or nearly proportionally related to the RPE value.
- the lactic acid concentration is low, the user feels “easy/simple” in continuous exercise; conversely, when the lactic acid concentration is high, the user feels “heavy/difficult” or even “unsustainable” in continuous exercise.
- the physical strength value is directly related to the lactic acid concentration.
- the physical strength value shown in Fig. 7 can be described as a bar-shaped physical strength indicator. For example, when the lactic acid concentration reaches a predetermined threshold on the left side of FIG. 14C, the physical strength value is determined to be 100% at this time. And as the lactic acid concentration increases with the linear or non-linear mathematical model mentioned above, the physical strength indicator begins to decrease, as indicated by the white and black arrows in Figure 14C.
- 15A and 15B are graphs showing the relationship between the concentration of lactic acid and the intensity of exercise or the concentration of lactic acid and the amount of oxygen consumed.
- the concentration of lactic acid associated with accumulation of lactic acid in blood can be estimated based on physiological signals other than heart rate.
- the sensor module 101 can monitor the user's exercise intensity or oxygen consumption, and the exercise intensity or oxygen consumption is positively correlated with the lactate concentration and can use a linear regression model, a nonlinear regression model, a piecewise function, and other mathematical models. Or simulate in any combination of the above.
- the user's physical strength can be recorded over a period of time, for example, between training, competitions/races, challenges, and the like.
- physical value records can be uploaded to the network for further application, such as expression or communication on a social network.
- the physical value record can be combined with various parameters to meet the user's needs for different applications, such as physical strength and heart rate, speed, time, map, temperature, humidity, altitude, calorie expenditure, exercise efficiency, estimated At least one of the maximum motion displacements, or a combination of any one of them. It is worth noting that the physical value record can be output or exported in real time or after a period of time.
- Fig. 16 is a schematic view showing a typical application method for estimating the maximum motion displacement of the user based on the physical strength value and the moving speed of the user.
- the user can review the history of physical value records to assess changes in physical strength over a distance, speed, terrain, temperature, or weather condition, and then adjust the speed or route of their next exercise. Users can also monitor their physical strength changes over the same route for days or weeks.
- the user's physical strength value is related to the user's speed of movement over a period of time. For example, if the user completes a physical strength value of 10% for a 5 km running exercise, the exercise assisting device 100 can estimate the exercise distance of the user's exercise to exhaust 100% of the physical strength.
- the additional distance associated with the remaining 10% of the physical strength value can be estimated by multiplying the user's instantaneous speed by the physical effort time.
- the extra distance mentioned above refers to the distance estimated by the remaining physical strength percentage, for example, if the remaining estimate is The 10% physical strength value is equivalent to an extra distance of 1 km, and the exercise assisting device 100 can remind the user that 100% of the physical strength is equivalent to a full 6 km running.
- the estimated maximum motion displacement can be applied to the design of the training program.
- a user may have a training program with different distance goals on the first day and the next few days.
- the first day exercise assisting device 100 displays that the user's exercise record distance is 10 kilometers, but the estimated maximum exercise displacement is 11 kilometers, indicating that the estimated distance by the percentage of unused physical strength is 1 km.
- the estimated maximum motion displacement reached 22 km. Therefore, under a reasonable estimate, the user using the exercise assisting device 100 is ready to practice 22 kilometers on the fourth day.
- each user's physical strength can be summarized in a range of 0% to 100%, different users of different physical levels can compare their physical strength records to adjust their exercise.
- a gym instructor can monitor the physical strength of all members of a class and tell each member to adjust his/her amount of exercise accordingly.
- Figure 17 is a schematic diagram of the user's physical strength value outputted together with a map in a specific embodiment of the present invention.
- the physical strength record can be used in conjunction with the GPS data and associated with the map to assess where the user's physical strength is rapidly being consumed, for example, on a steep mountain top.
- the location where the user's physical strength value is rapidly consumed may be beneficial to the store owner of the water or food to evaluate the address of the setting store.
- the location where the user's physical strength value is rapidly consumed may be associated with information captured by some specific devices, such as a video recorder or a camera, so that the user's video can be observed through the Internet along with the user's physical strength.
- FIG. 18 is an application schematic diagram of estimating a user's calorie expenditure by utilizing a user's physical strength value.
- the user's physical strength value can correspond to the user's calorie consumption in a mathematical model. For example, if the user is trained at a steady speed, the steady reduction in physical strength is equivalent to a constant heat consumption.
- the total calorie expenditure during training can be assessed by multiplying the total calorie expenditure by the total time of exercise. If the user increases the exercise load at time t1, the calorie consumption becomes higher. However, the user may not be able to maintain an increased exercise load for a long time, so the total heat consumption after time t1 will also decrease.
- the exercise aid can indicate the correlation between the exercise load (ie, the rate of decrease in physical strength) and the total calorie expenditure, and send a notification to the user to make a reasonable recommendation.
- Exercise load ie, the rate of decrease in physical strength
- 19 is a method of estimating physical strength values based on physiological signals in accordance with an embodiment of the present invention.
- the physical strength value is a combination of an oxygen-free energy value and an aerobic energy value, wherein the physical strength value is positively correlated with the anaerobic energy value and the aerobic energy value, and the positive correlation energy is linearly regression Models, nonlinear regression models, piecewise function models, other mathematical models, or any combination of the above are used for simulation.
- S301 Receive biological information from the user interface 103;
- S305 evaluating, by the processing module 102, the percentage of the anaerobic energy value according to the physiological data
- S307 The percentage of the aerobic energy value is evaluated by the processing module 102 according to the physiological data (P t ) and the biological information;
- the percentage of the physical value is estimated by the processing module 102 based on the percentage of the oxygen-free energy value and the aerobic energy value.
- the biological information can comprise at least one of the following: height, weight, age and sex, and the like.
- the physiological data (P t ) can comprise at least one of the following: EKG signal, heart rate variability, pulse rate, heart rate, breathing pattern, body temperature, blood glucose, blood pressure, glycogen concentration, and Oxygen concentration, etc.
- physiological data ( Pt ) can be saved in storage module 104 for subsequent use or sent to processing module 102 for evaluation of anaerobic energy and aerobic energy.
- the physical strength value (S t %) may correspond to the RPE value by the processing module 102 and output to the user via the user interface 103.
- the anaerobic energy value is associated with the accumulation of lactic acid concentration, which is associated with additional calorie expenditure.
- the physical strength value (S t %) can be estimated based on the accumulation of lactic acid concentration and additional calorie expenditure and using a linear regression model, a nonlinear regression model, a piecewise function, other mathematical models, or any combination thereof. .
- Figure 20 is a diagram of a method for assessing anaerobic energy based on physiological information in accordance with an embodiment of the present invention, wherein the method is the development of step S305 in Figure 19.
- S401 Obtain an anaerobic evaluation setting from the storage module 104, such as an anaerobic energy level (oxygen-free C) and a maximum anaerobic energy value (no oxygen max );
- S405 Obtain physiological data (P t ) from the storage module 104.
- S409 Calculate the percentage of the anaerobic energy value by the processing module 102 using the oxygen-free energy value (oxygen-free t ), the maximum oxygen-free energy value (no oxygen max ), and the minimum oxygen-free energy value (oxygen-free min ) (anaerobic t %).
- the order of S401, S403, and S405 is interchangeable.
- a step S405 in addition to obtaining physiological data (P t) from the storage module 104, but also may be measured by the sensor module 101 acquires physiological data (P t). Therefore, the method of measuring the oxygen-free energy can be used alone without referring to the method in FIG.
- the anaerobic energy level may be the lactic acid dilution rate or the lactic acid production rate.
- the anaerobic energy value may be the accumulation of the user's lactic acid concentration
- the maximum anaerobic energy value (oxygen-free max ) may be the maximum lactic acid concentration that a person can theoretically withstand, wherein the maximum lactic acid concentration Will change as the anaerobic evaluation settings are adjusted.
- oxygen-free max the maximum anaerobic energy value
- a professional athlete can withstand a higher lactic acid concentration than an amateur runner.
- even the same person can withstand different lactic acid concentrations. For example, if a person stops exercising for a while, this person may only be able to withstand lower lactate concentrations than before. Another example is that a person moves very regularly and he may be exposed to higher lactic acid concentrations than before.
- the maximum anaerobic energy value (oxygen-free max ) can be preset to a specific value, and the exercise assisting device 100 is appropriately adjusted to evaluate the physical strength each time the exercise assisting device 100 evaluates the physical strength value (S t %). Value (S t %).
- the adjustment can also be performed after the exercise assisting device 100 is turned off or turned on by the user. The method of adjusting the anaerobic evaluation settings will be introduced later.
- the minimum anaerobic energy value may be a concentration of lactic acid that can be maintained while the user is exercising without a sharp increase.
- the minimum anaerobic energy value (anaerobic min ) as shown in Fig. 8 can be set to 4 mmol/L.
- the minimum anaerobic energy value (anaerobic min ) may be a constant value preset on the exercise assisting device 100 or input by the user using the user interface 103.
- the last recorded oxygen-free energy value (no oxygen t-1 ) may be a value stored in storage module 104 after the last evaluation of the oxygen-free energy value. Assuming that the user first uses the exercise assisting device 100 and does not exercise, the anaerobic t-1 is equal to anaerobic min .
- 21 is a method of estimating aerobic energy based on physiological data in accordance with an embodiment of the present invention, wherein the method is the development of step S307 in FIG.
- S501 Obtaining aerobic evaluation settings, such as an aerobic energy level (aerobic C) and a last recorded aerobic energy value (aerobic t-1 ), from the storage module 104;
- S503 Obtain biological information from the storage module 104.
- S505 Obtain a physiological signal (P t ) from the storage module 104.
- the aerobic energy value is evaluated by the processing module 102 according to the physiological signal (P t ), the biological information, the last recorded aerobic energy value (aerobic t-1 ), and the aerobic energy constant value (aerobic constant).
- Oxygen t The aerobic energy value is evaluated by the processing module 102 according to the physiological signal (P t ), the biological information, the last recorded aerobic energy value (aerobic t-1 ), and the aerobic energy constant value (aerobic constant).
- S509 Calculate the percentage of aerobic energy value (aerobic C) (aerobic t %) by the processing module 102 using an aerobic energy value (aerobic t ) and an aerobic energy level (aerobic C).
- steps S501, S503 and S505 is interchangeable.
- a step S505 in addition to obtaining physiological data (P t) from the storage module 104, but also may be measured by the sensor module 101 acquires physiological data (P t). Therefore, the method of measuring aerobic energy can be used alone without involving the method in FIG.
- the aerobic energy level may be the user's aerobic energy capacity, wherein the aerobic C may be a value pre-set and stored in the storage module 104.
- the percentage of aerobic energy value evaluated by step S509 can indicate the ratio of the aerobic energy value to the oxygen energy capacity.
- the last recorded aerobic energy value may be the aerobic energy value (aerobic t ) stored in the storage module 104 when the aerobic energy was last evaluated. . Assuming that the user first uses the exercise assist device 100 and does not exercise, the aerobic energy value (aerobic t-1 ) is equal to the aerobic energy level (aerobic C).
- the constant value of aerobic energy may be an aerobic energy consumption rate when an ordinary person does not exercise, wherein the rate may be preset in the exercise assisting device 100.
- Constant value It's worth noting that users continue to consume aerobic energy all the time, even when they are asleep. Therefore, when the user moves, the user's aerobic energy consumption will be higher than the aerobic energy constant value, and the user's aerobic energy consumption will change below the aerobic energy constant value when the user recovers. In other words, the extra aerobic energy expenditure is positive when the user is exercising, and the extra aerobic energy expenditure is negative when the user is recovering.
- the aerobic energy can be related to the additional heat consumption, which is the difference between the user's aerobic energy consumption and the aerobic energy constant value. Therefore, in step S507, the aerobic energy value can be evaluated by aerobic C minus the additional calorie expenditure.
- Figure 22 is a specific embodiment of the present invention based on a method for estimating physical strength values (S t %) plus setting adjustments based on physiological data in Figure 19.
- the method of estimating the physical strength value (S t %) in FIG. 19 can be improved via an adjustment including an anaerobic evaluation setting and an aerobic evaluation setting, wherein the anaerobic evaluation setting and the aerobic evaluation setting are performed. It can be updated to improve the accuracy of the assessment of physical strength values (S t %). Since the anaerobic evaluation setting and the aerobic evaluation setting cannot be used to accurately represent the user's true physical condition each time the methods of FIGS. 20 to 21 are performed, the anaerobic evaluation setting and the aerobic evaluation setting can be performed at the anaerobic energy value and The aerobic energy value is updated after evaluation.
- S311 The anaerobic evaluation setting is adjusted by the processing module 102 according to the oxygen-free energy value (oxygen-free t ).
- the aerobic assessment setting is adjusted by the processing module 102 based on the aerobic energy value (oxygen t ).
- step S311 may be performed after step S305, and step S313 may be performed any time after step S307.
- Figure 23 is a diagram of a method for adjusting the anaerobic evaluation setting and then for estimating the physical strength value (S t %), which is a detailed description of step S311 in Figure 22, in accordance with an embodiment of the present invention.
- step S601 Compare, by the processing module 102, whether the oxygen-free energy value (no oxygen t ) is greater than or equal to a function of the maximum oxygen-free energy f (no oxygen max ), if it is to continue to step S603, otherwise proceed to step S607.
- S603 Send a notification to the user through the user interface 103.
- step S605 It is felt by the sensor module 101 whether the user reduces the exercise intensity, and if it is to continue to step S609, otherwise exits.
- the user can set a value to replace the maximum anaerobic energy f (anaerobic cmax ).
- the function of the maximum anaerobic energy can be replaced by a value such as 10 mmol/L. If the anaerobic energy value (oxygen free t ) is estimated to be 12 mmol/L, the exercise assisting device 100 will send a notification to the user.
- the anaerobic threshold and X minutes may be preset and stored in the storage module 104.
- the user can set the anaerobic threshold and X minutes by himself.
- the anaerobic energy value is the lactic acid concentration
- the anaerobic threshold may be 6 mmol/L
- the X minute may be 5 minutes. If the anaerobic energy value (oxygen free t ) is estimated to be 7 mmol/L for 5 minutes, the exercise assisting device 100 will send a notification to the user.
- the anaerobic C + 1 indicates that the anaerobic C is gradually increased by the preset amount, and the predetermined amount may be a constant value or a percentage.
- anaerobic C + 1 can be to increase the rate of lactic acid dilution or to reduce the rate of lactic acid production to 1 mmol/L or 5%.
- the new maximum anaerobic energy can be an anaerobic energy value (no oxygen t ) or a predetermined increment from the maximum anaerobic energy (no oxygen max ) plus.
- the notification in step S603 can be sent to the user in a variety of forms, such as visual, audible, and vibrating, and the like.
- the sensor module 101 can sense whether the user reduces the exercise intensity by the change of the physiological data (P t ).
- the physiological data (P t ) perceived by the sensor module 101 is the heart rate. If the heart rate perceived at time t is lower than the previously recorded heart rate, exercise assisting device 100 may determine that the user reduces the exercise intensity.
- the method of adjusting the anaerobic evaluation setting can be applied to the case where the exercise assisting device 100 underestimates the user's physical strength and endurance.
- the exercise assisting device 100 adjusts the anaerobic evaluation setting according to step S609.
- the adjustment of S609 not only increases the maximum anaerobic energy but also increases the lactic acid dilution rate or decreases the lactic acid production rate for use as an anaerobic evaluation setting in the next round of anaerobic energy evaluation.
- Figure 24 is a diagram of a method for adjusting aerobic assessment settings and then for assessing physical strength values (S t %), in accordance with at least one embodiment of the present invention, wherein such method is detailed in step S313 in Figure 22 .
- the processing module 102 compares whether the aerobic energy value (aerobic t ) is lower than or equal to the minimum aerobic energy threshold, and if yes, proceeds to step S703, otherwise exits;
- S703 Send a notification to the user through the user interface 103.
- step S705 Through the sensor module 101, it is felt whether the user reduces the exercise intensity, and if it is to continue to step S707, otherwise exits;
- the minimum energy threshold may be pre-set and stored in the storage module 104.
- the minimum aerobic energy threshold can be 5% of aerobic C.
- the notification in step S703 can be sent to the user in various forms, such as visual, audible, and vibrating, and the like.
- the sensor module 101 can sense whether the user reduces the exercise intensity by the change of the physiological data (P t ).
- the physiological data (P t ) sensed by the sensor module 101 is the heart rate. If the heart rate perceived at time t is lower than the previously recorded heart rate, such as: P t ⁇ P t-1 , exercise assisting device 100 may determine that the user reduces the exercise intensity.
- aerobic C + 1 indicates that the aerobic C is gradually increased by a predetermined amount, and the predetermined amount may be a constant value or a percentage.
- aerobic C + 1 can be used as a new aerobic energy capacity by increasing 1 or 5% of aerobic C and used for the next round of aerobic energy value assessment.
- the method of adjusting the aerobic evaluation setting can be applied to the case where the exercise assisting device 100 underestimates the user's physical strength and endurance.
- the exercise assisting device 100 adjusts the aerobic evaluation setting according to step S707.
- the adjustment of S707 not only increases the aerobic energy capacity, ie aerobic C, but correspondingly increases the aerobic t-1 , in order to use the anaerobic energy assessment in the next round. Used as an anaerobic evaluation setting.
- FIG 25 is a diagram of a method for assessing maximum calorie expenditure in accordance with an embodiment of the present invention.
- the user's aerobic energy value will continue to be consumed, so the aerobic energy consumption will only increase and will not decrease.
- the evaluation of each aerobic energy value (aerobic t ) can be recorded together with the physical strength value (S t %) and then stored in the storage module 104.
- aerobic t-1 minus aerobic t will be the difference in aerobic energy consumption ( ⁇ aerobic).
- the difference in aerobic energy consumption ( ⁇ aerobic) can be combined with the physical value (S t %) as a set of aerobic energy data (aerobic data).
- the aerobic energy value can be related to the additional calorie consumption, so the aerobic energy consumption difference ([Delta aerobic) can be the difference in calorie consumption from t-1 to t. Therefore, the actual heat consumption at time t will be ⁇ aerobic + aerobic constant.
- the following steps can be used to evaluate the maximum heat consumption achievable by the user through the processing module 102 and the storage module 104:
- each set of aerobic energy data includes a physical strength value (St%) and a time t-1 to a time t Aerobic energy consumption difference ( ⁇ aerobic).
- S807 All the aerobic data satisfying the condition of S805 is saved in the storage module 104.
- S811 The maximum calorie expenditure is estimated by ⁇ (eff_calorie_rate)*last recorded physical strength value (S t %) + total calorie, that is, the sum of the effective calorie consumption rate (eff_calorie_rate) for each set of saved aerobic data from S809 Multiply the last recorded physical value (S t %) in the N sets of aerobic data, and add the total calorie consumption (total heat) to the multiplication result to get the maximum calorie consumption.
- step S803 can be performed at any time between S801 and S811.
- step S803 the total heat consumption (heat total) can be output through the user interface 103, so the user can monitor the heat consumption so far.
- the total heat can be subtracted from the maximum heat consumption and then output to the user, so the user can know how much heat can be consumed before the last recorded physical value is used up.
- the last recorded physical value is the remaining physical strength. .
- the total heat and/or maximum heat consumption can be output to the user in various forms, such as visual, acoustic, and vibration.
- each set of saved aerobic data has its own weighting variable. Assuming that each percentage of physical strength (S t %) consumption requires an equal amount of time, the weighted variable can represent the contribution of aerobic energy expenditure to each percentage of the consumed physical value (S t %). For a particular group of saved aerobic data, the contribution of calorific combustion can be the difference in aerobic energy consumption ( ⁇ aerobic) in the group and the aerobic energy consumption of all stored aerobic data ( ⁇ A ratio between the sum of oxygen).
- the effective heat consumption rate (eff_calorie_rate) is the rate of heat consumption when the physical force is actually consumed.
- the effective heat consumption rate is the amount of heat that the user can burn by consuming each percentage of physical strength.
- Figure 26 is a diagram of a method for assessing maximum motion displacement in accordance with an embodiment of the present invention.
- the sensor module 101 can record each individual force value (S t %) and the motion sensor (not shown) when feeling from time t-1 to t
- the resulting motion displacement value ( ⁇ Dis) is stored in the storage module 104.
- the motion sensor may be part of a sensor module 101, which may be one of the following: a gyroscope, an accelerator, a pedometer, a motion rhythm monitor, a speedometer, a GPS receiver, or a power meter, wherein Motion sensors can also provide real-time displacement information, such as speed, altitude, slope, etc., directly or indirectly. Each displacement value ( ⁇ Dis) can be combined with the physical value (S t %) as a set of motion data (ex_data). The motion sensor can measure the motion power of the user's movement, the rhythm of the movement (eg, the stroke frequency, the pace frequency, etc.), the displacement information, and the like.
- a sensor module 101 may be one of the following: a gyroscope, an accelerator, a pedometer, a motion rhythm monitor, a speedometer, a GPS receiver, or a power meter, wherein Motion sensors can also provide real-time displacement information, such as speed, altitude, slope, etc., directly or indirectly. Each displacement value
- the following steps can evaluate the maximum motion displacement that the user can achieve through the processing module 102 and the storage module 104:
- each set of motion data (ex_data) includes a physical strength value (S t %) and a time value from the time t-1 to the t displacement value ( ⁇ Dis);
- S907 Save motion data that meets the condition of S905 to the storage module 104.
- the effective motion displacement (eff_dis_rate) is calculated by a function of the displacement value ( ⁇ Dis), the physical value (S t %), the physical value of the previous group (S t-1 %), and a weighted variable. );
- S911 The maximum motion displacement is evaluated by ⁇ (eff_dis_rate)* last recorded physical value (S t %) + dis_total, that is, the sum of the effective motion displacement ratios (eff_dis_rate) for each set of saved motion data from S909 Multiply the last recorded physical value (S t %) of the N sets of motion data and add the total motion displacement (dis_total) to the result of the multiplication to obtain the maximum motion displacement.
- step S903 can be performed any time between S901 and S911.
- the total motion displacement (dis_total) can be output through the user interface 103, so the user can monitor the displacement so far. For example, the distance of running, the height of climbing, and so on.
- the user can know how much displacement can be performed before the last recorded physical strength value is used, and the last recorded physical strength is the residual physical strength of the value. This is especially useful for the user because the user can adjust the exercise intensity to achieve the desired motion displacement. For example, the user wants to ride 10 kilometers.
- the exercise assisting device 100 estimates the maximum motion displacement to be 8 kilometers, a notification is sent to the user through the user interface 103.
- the user can slow down to reduce the rate of physical exertion and then ride the remaining physical strength for more than 8 kilometers.
- the maximum motion displacement is evaluated by the exercise assisting device 100 as 12 kilometers, the user can increase the speed of the ride and still reach 10 kilometers.
- the exercise assisting device 100 can estimate the ratio between the rate at which the user consumes the physical strength value and the riding speed of the user, thereby suggesting that the user can ride the speed to achieve the target of 10 kilometers.
- the exercise assisting device 100 can even calculate that the user can launch several attacks (when riding in a team or a smaller combination to speed up the ride to create a gap between the user and other riders) and still get 10 km target. This can be achieved by pre-setting the maximum motion displacement that the user needs to sacrifice.
- the user can use each of the maximum motion displacements of 3 kilometers for each attack.
- the user's maximum motion displacement is estimated to be 17 kilometers, the user can make more than two attacks and still achieve a goal of 10 kilometers without completely consuming all of the user's physical strength.
- the exercise assisting device 100 can evaluate the physical exertion rate or the decrease of the maximum exercise displacement at the time of attack by tracking the user's heart rate, motion, or any motion factor that varies with the user's exercise intensity. .
- the number of available attacks can be output to the user through the user interface 103. Therefore, the user can control his/her athletic activities without difficulty, especially when the user does not want to maintain a constant exercise intensity.
- the total motion displacement and/or the maximum motion displacement may be output to the user in various forms, such as visual, audible, and vibrating.
- each set of saved motion data has its own weighting variable. Assuming that each percentage of the physical value (S t %) is consumed requires an equal amount of time, the weighted variable can represent the contribution of the displacement to each percentage of the physical value (S t %) consumed. For a particular set of saved motion data, the contribution of the displacement may be a ratio between the displacement value ( ⁇ Dis) in the set and the sum of the displacement values ( ⁇ Dis) of all saved motion data.
- the effective motion displacement rate (eff_dis_rate) is the displacement rate achieved by the user when the physical force is actually consumed.
- the effective displacement rate is how much displacement the user can make when the user consumes every percentage of physical strength.
- the sensor module 101 can measure motion information of the user such as athletic power, athletic rhythm, speed, altitude, slope gradient, body composition, and the like.
- the measurements from the sensor module 101 can be correlated to the physical strength values obtained in Figures 10 and 19 using the method.
- the measurement of exercise power can be used to assess the maximum exercise power that a user can exert during or after exercise.
- the measurement of the rhythm of the exercise can be used to determine if the user is moving effectively or providing the user with the most effective exercise rhythm directly through the output device (eg, 60 steps per minute for running, 60 pedaling per minute for the rider, etc.).
- Displacement information can be used to assess the user's response to changes in speed, altitude, slope, etc.
- the processing module 102 can use the measurement of the motion information to assess the endurance and/or athletic power of the user's body.
- the anaerobic evaluation setting in FIG. 23 and/or the aerobic evaluation setting in FIG. 24 can be further adjusted depending on the endurance and/or athletic strength of the user's body.
- the body composition can be used to assess the user's physical energy density. For example, correlating the user's muscle density with anaerobic energy values, and/or aerobic energy values, and/or physical strength values, and the like.
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Abstract
一种体力监测装置(100),包括:传感器模块(101),用来感受生理信号;用户界面(103),用来接收生物信息;储存器(104),用来储存生物信息和至少一数学模型;处理模块(102),用来执行至少一数学模型来操作以下事项:基于生理信号和生物信息来评估无氧能量值和有氧能量值;结合无氧能量和有氧能量并产生体力值。还根据用户的无氧能量值和有氧能量值,提供了一种评估体力值的方法和调整这种评估体力值方法的一种方法。进一步提供了体力级别的评估装置。
Description
本发明涉及的是一种运动辅助装置,具体地,本发明涉及一种能够显示用户体力的体力监测装置,并且在特定的情况下能够发出通知提醒。
专业的运动员、运动热爱者或者那些喜欢运动的人经常在运动的时候评估他们自己的身体状况,从而安排他们自己的体力以完成一项训练或一个比赛。通常,人们在运动之前或者运动过程中会评估他们自己的身体条件和环境因素来调整他们的训练。另外,在运动之后,人们记录并分析他们的体力和耐力作为下次运动的参考。
近来,各种类型的运动辅助装置被研发出来用来实时地评估用户的体力。这些装置在运动过程中能给用户提供他们自己生理上的信号,在运动之后用户可以浏览运动的历史记录,并且能够分享到社交网络上。但是,生理信号的提示,比如心率,经常不能可靠和精准地与用户的体力和耐力相联系。换句话说,在运动过程中仅仅提供生理信号对用户决定什么时候需要增加或减少运动强度(即在马拉松中减慢或者加速)几乎没有帮助。
有鉴于此,有必要提供一种体力监控装置用以辅助运动,无论用户的身体状况的差异,都能可靠地显示他们的体力值。
一种体力监控装置,包括:传感器模块,用来感受生理信号;用户界面,用来接收生物信息;储存器,用来储存生物信息和至少一数学模型;处理模块,用来执行至少一数学模型来操作以下事项:基于生理信号和生物信息来评估无氧能量和有氧能量;结合无氧能量和有氧能量并产生体力值。
进一步,所述无氧能量与乳酸浓度的累积有关。
进一步,所述有氧能量与热量消耗相关。
进一步,所述生物信息包括以下至少一项,比如身高、体重、年纪及性别。
进一步,所述传感器模块感受以下至少一项包括心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔及斜坡坡度。
进一步,所述传感器模块包括能感受心率的心电传感器。
进一步,所述用户界面包括至少一输出装置,选自显示屏、振动组件,或扬声器。
进一步,包括一带子,通过所述带子,所述体力监控设备被直接或间接地固定在用户的皮肤上。
进一步,所述体力监控设备被所述带子固定在用户的前额、手腕、腿部或手臂。
进一步,所述体力值被输出连同以下至少一参数包括心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
进一步,当所述无氧能量和/或所述有氧能量到达一阈值时,用户界面输出一通知。
进一步,所述通知是振动的通知、声音的通知,或可视的通知。
进一步,体力值可以进一步对应到自感劳累等级(RPE),并在用户界面输出。
进一步,所述处理模块进一步基于体力值和有氧能量来评估最大热量消耗。
进一步,包括一运动传感器,可以直接或间接提供实时地位移信息。
进一步,所述处理模块进一步基于体力值和位移信息评估最大运动位移。
进一步,用户界面输出可行的进攻次数,所述可行的进攻次数可以通过处理模块基于体力值或最大运动位移计算。
一种体力监控方法,包括:通过传感器模块感受生理信号;从用户界面接收生物信息;基于生理信号和生物信息,通过处理模块使用至少一储存在储存模块中的数学模型来估算无氧能量和有氧能量;基于无氧能量和有氧能量评估体力值;通过至少一输出装置输出体力值。
进一步,所述无氧能量与乳酸浓度的累积有关。
进一步,所述有氧能量与热量消耗有关。
进一步,所述生物信息包括以下至少一项,比如身高、体重、年纪及性别。
进一步,所述传感器模块感受以下至少一项:心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔及斜坡坡度。
进一步,所述传感器模块包括能感受心率的心电传感器。
进一步,所述输出装置为一显示屏、一振动组件,或一扬声器。
进一步,所述体力值被输出连同至少一参数包括心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
进一步,当所述无氧能量和/或所述有氧能量到达一阈值时,至少一输出装置输出通知。
进一步,所述通知是振动的通知、声音的通知,或可视的通知。
所述体力监控方法进一步包括:通过处理模块,将体力值对应到RPE的等级;通过至少一输出装置输出RPE的等级。
所述体力监控方法进一步包括:通过处理模块基于体力值和有氧能量评估最大热量消耗。
所述体力监控方法进一步包括:从运动传感器中直接或间接地获得实时的位移信息。
所述体力监控方法进一步包括:通过处理模块基于体力值和位移信息评估最大运动位移。
所述体力监控方法进一步包括:通过用户界面输出可行的进攻次数,其中所述处理模块基于体力值或最大运动位移计算所述可行的进攻次数。
一种体力监控设备,包括:传感器模块,用来感受生理信号;用户界面,用来接收生物信息; 储存器,用来储存生物信息和至少一数学模型; 处理模块,用来执行至少一数学模型来完成以下事项:基于生理信号和生物信息来评估体力值;基于耐力值来评估运动辅助信息;发送体力值到包含有一输出装置的用户界面;通过用户界面输出体力值。
进一步,处理模块进一步地基于体力值和有氧能量评估最大热量消耗,其中有氧能量的评估是基于生理信号和生物信息。
进一步,包括运动传感器,所述运动传感器直接或间接提供实时的位移信息,同时处理模块进一步地基于体力值和位移信息评估最大运动位移。
进一步,所述处理模块基于体力值或最大运动位移计算可行的进攻次数并通过用户界面输出所述可行的进攻次数。
进一步,储存器进一步储存位移目标,当最大运动位移低于位移目标时,发送通知给用户。
进一步,所述输出装置为一显示屏、一震动组件,或一扬声器。
进一步,所述生物信息包括以下至少一项,比如身高、体重、年纪及性别。
进一步,所述传感器模块包括感受心率的心电传感器。
进一步,所述体力值被输出连同至少一参数包括心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
进一步,所述传感器模块感受以下至少一项:心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔及斜坡坡度。
由于本发明采用传感器模块感受生理信号和用户界面接收生物信息相结合,储存模块储存用户的生物信息,处理模块实时处理信息,从而评估有氧能量值和无氧能量值,进而对用户的体力值进行实时评估,并输出给用户的方案,能够使不同身体状况的用户都能得到可靠的体力值,从而使用户在运动过程中可以决定什么时候需要增加或减少运动强度。
附图结合文字描述阐述了一个或多个发明的实施方案,用来解释本发明的原理。在任何情况下,在整个图中同样的参考数字用来指代一个具体实施例中相同的或者相似元素,其中包括:
图1是本发明至少一个具体实施例所提供的运动辅助装置的***方框图。
图2A和2B是本发明至少一个具体实施例所提供的分别由心电(EKG)信号或者传感器侦测的信号所引起的心脏波形图的示意图。
图3A~3C是本发明的一个具体实施例所提供的典型的运动辅助装置的示意图。
图4是本发明的另一个具体实施例所提供的各种典型的运动辅助装置的示意图。
图5是体力值和自感劳累分级(RPE)的对应概念的示意图。
图6是典型的体力级别和用户的健康状况之间关系的示意图。
图7是本发明的至少一个具体实施例所提供的体力值指示器的示意图。
图8是乳酸浓度和心率关联性的示意图。
图9是关于用户运动期间乳酸浓度的变化的示意图,以及乳酸浓度与体力值的对应。
图10是本发明的至少一个具体实施例所提供的评估体力值方法的流程图。
图11是本发明的至少一个具体实施例所提供发送通知给用户的标准条件的示意图。
图12是本发明的至少一个具体实施例所提供的调整体力级别方法的流程图。
图13是体力级别能自动符合图12的典型条件的示意图。
图14A和图14B是本发明的至少一个具体实施例所提供的心率,乳酸浓度和自感劳累等级关系的示意图,以及图14C是体力值和自感劳累等级关于乳酸浓度的对应。
图15A和15B是乳酸浓度和运动强度或者乳酸浓度和耗氧量之间关系的示意图。
图16是用用户的体力值和运动速度来评估用户的最大运动位移的典型的应用程序的示意图。
图17是连同地图一起输出用户的体力值的典型的应用程序的示意图。
图18 是利用用户的体力值评估用户的热量消耗的典型的应用程序的示意图。
图19是本发明的一个具体实施例所提供的基于生理数据来评估体力值的方法。
图20是本发明的一个具体实施例所提供的基于生理数据来评估无氧能量的方法。
图21是本发明的一个具体实施例所提供的基于生理数据来评估有氧能量的方法。
图22是本发明的一个具体实施例所提供的基于生理数据评估和设置调整数来评估体力值。
图23是本发明的一个具体实施例所提供的调整无氧评估设置来评估体力值的方法。
图24是本发明的一个具体实施例所提供的调整有氧评估设置来评估体力值的方法。
图25是本发明的一个具体实施例所提供的评估最大热量消耗的方法。
图26是本发明的一个具体实施例所提供的评估全部最大运动位移的方法。
依照惯例,各种描述的图形不是按比例绘制,而是用来强调相关的所揭露出来的特征。如在整个数据和文本引用字符表示元素。
运动辅助装置 | 100 |
传感器模块 | 101 |
处理模块 | 102 |
用户界面 | 103 |
储存模块 | 104 |
具有保护套的运动辅助装置 | 300 |
带子 | 301 |
手环 | 401 |
指示灯 | 402 |
智能手机 | 403 |
条形物的上边界 | 202 |
条形物的下边界 | 204 |
空心块 | 206 |
如下具体实施方式将结合上述附图进一步说明本发明。
本发明在下文中根据附图将做更充分的描述,本发明的具体实施例也会具体地说明。无论如何,本发明也许会在许多不同形式上具体体现出来,不应该被理解为限制于这里所提到的具体表现形式。提供这些具体表现形式便于彻底和完全的披露出来,以及充分地传达本发明的范围给那些熟悉本领域的人。全文中参考数字指代元素。
在这里使用的术语是仅仅为了详细描述具体实施例,而不是限制发明。使用在这里时,不限定个数,除非语境清晰地表明,这将进一步理解术语“包括”,或“有”使用时,指定所规定的特征、区域、整数、步骤、操作、元素,和/或组件的存在,但是并不排除或增加一个或多个其他特征、区域、整数、步骤、操作、元素、组成,和/或其中的组合。
理解术语“和/或”包含任何一个以及所有所涉及到的罗列出来的一个或者更多的条款的组合。虽然条款的第一条、第二条、第三条等也许在这里被用来描述多种元素、组合、区域、零件和/或部分,但是很容易理解这些元素、组合、区域、零件和/或部分不应该被这些条款所限制。这些条款不仅用来区分一个元件、组成、区域、零件和/或部分和另一个元件、组成、区域、层次或部分。因此,以下所讨论的第一个元件、组成、区域、零件或部分应该被称为第二个元件、组成、区域、层次或部分,没有从本发明的教学中分离。
除非另外定义,这里使用的所有的条款(包括技术上的和科学上的条款)同在艺术上的普通技能一样理解所属发明。如这些常用的字典中的定义,进一步理解这些条款应该被理解为与相关的艺术和目前的信息披露一致,而不会被理解为一个理想化或过分拘谨的观念,除非在这里清楚的定义。
说明书将会包括关于本发明的具体实施例和附图1~26。参照将会被做成图片来详细描述本发明,在图里所描述的元素不一定是按规定的比例,通过一些观点和相同的或相似的术语,相同的或相似的元素被命名为相同的或相似的参考数字。
图1是本发明的至少一个具体实施例所提供的一个运动辅助装置(也被称为体力监测装置)的***方框图。
如图1所示,运动辅助装置100包括一个传感器模块101,一个处理模块102,一个用户界面103和一个储存模块104。
传感器模块101包括至少一个传感器来感觉和测量用户的生理信号。比如,生理信号包括至少一个以下所提到的:心电(EKG)信号、心率变异性、脉搏、心率、呼吸模式、体温、体内成分、血糖、血压、糖原含量和含氧量。体内成分也许包括人体内的脂肪、水分和肌肉的百分含量。
处理模块102是计算机硬件,例如一个有辅助电路的微控制器或微处理器通过执行基本的算术、逻辑和输入/输出运动辅助设备的操作来实行电脑程序的指令。
用户界面103包括至少一个输出装置和/或至少一个输入装置,或者任何一种组合。这个输出可能是一个显示、一个摇摆组件或一个扬声器,或任何一种组合,用来指出用户在运动期间或运动过后的体力值。输入可能是任何一个人机界面,比如一个触屏,一个声音接收器或一个按钮,它能用来接收用户的生物信息,比如身高、体重、年纪、性别等。另外,用户界面103可以适用于直接发送信息给传感器模块101,处理模块102或者储存模块104。输入的信息可以被处理模块102加工,然后发送到所述输出,让用户知道当前的身体状况。比如,BMI值,等。
储存模块104可以是任何种类的磁盘或者内存,用来储存来自传感器模块101、处理模块102或者用户界面103的信息。比如,所储存的信息可以是用户的活动历史记录或者生物信息,从活动历史记录或生物信息可以计算用户在静止状态下的基础血液乳酸浓度、基础心率、基础摄氧率,或以上任何一种组合,并借此进一步计算用户的体力值和用户的最初的体力级别。
应该注意的是体力这个术语,是指生物发挥自己并且在一段时间内仍然保持活力的能力。此外,体力值和体力级别的观念将会在下面的段落里提出来。
参阅图1,处理模块102接收来自传感器模块101的生理信号,基于生理信号和储存在储存模块104里的指令进行处理,然后提供已处理的信息作为结果给用户界面103。另外,无论有没有指令储存在储存模块104,处理模块102也能接收来自用户界面103输入的指令,并执行所述输入的指令然后运行传感器模块101。
传感器模块101,处理模块102,用户界面103和储存模块104都能以有线或无线的方式相互连接。有线连接是任何有形的接触,比如,在印刷电路板里的一根电缆或者导电电线。无线连接时任何形式的无线传输,比如,WiFi、蓝牙或协助传输的无线电频率。
图2A和2B是本发明的至少一个具体实施例的心脏波形图示意图,所述心脏波形图示意图是通过心电信号或光学传感器侦测到的信号产生的。
如图2A所示,运动辅助装置100的传感器模块101中的心率监控传感器可以是一个心电(EKG)传感器。如图2B所示,运动辅助装置100的传感器模块101中的心率监控传感器可以是一个光学传感器。由于光学传感器容易受到人为因素的影响,比如其他的心脏相关信号和身体动作会干涉真实的心率信号因此降低心率读数的正确性,所以当在量测心脏不同的运行阶段的P、Q、R、S和T波时,心电传感器被认为优于光学传感器。心电传感器的信号中,属于人为因素造成的干扰可与PQRST波区别开,因此移除人为因素造成的干扰方能提供准确的心率读数。换句话说,用户的心率可以在特定的EKG波形之间基于时间间隔进行监测。比如,在每一个的T波或R波之间的时间间隔相当于每个心跳的时间。另外,心电传感器量测的心电信号可以通过识别不同波形自身的具体特点进而过滤噪音,比如T波,因此能防止人为因素影响心率测量。
图3A到3C是本发明的一个具体实施例所提供的一种典型的运动辅助装置的示意图。
如图3A到图3C所示,运动辅助装置300可以是一个具有外壳的装置,所述外壳容纳以下至少一或多个:传感器模块101,处理模块102,用户界面103和储存模块104。运动辅助设备300也可以是一个具有外壳的装置,容纳所有的传感器模块101,处理模块102,用户界面103和储存模块104。这个运动辅助装置300可以是一个可佩带装置的一部分,可以穿戴在人身体的某个部位,比如,胸部、手腕、手臂,或腿,并且从用户的身体部位感受和测量生理信号。
如图3A所示,运动辅助装置300包括一个外壳,容纳一个传感器模块101,一个处理模块102,用户界面103和储存模块104。如图3B所示,运动辅助装置300还包括一条带子(即弹性皮带),可以将运动辅助装置300捆绑在用户的胸部并将运动辅助装置300固定在用户心脏的附近。另外,运动辅助装置300的传感器模块101至少有一个电极(例如:两个电极连接到带子上),能感受用户的心电信号。如图3C所示,用户将具有带子301的运动辅助装置300穿戴在胸部,因此用户心跳的心电信号能被感受到。此外,运动辅助装置300还包括一个振动组件在外壳里,能根据用户在运动期间体力值的变化发送振动通知给用户。再一次值得注意的是耐力值的概念将会在下文中提及。
图4是本发明的另一个具体实施例中各种类型的运动辅助装置示意图。
如图4所示,运动辅助装置100可以分离为第一装置和第二装置。第一装置配置有无线通信能与第二装置交流。第一装置至少包含有一个传感器模块101,处理模块102,用户界面103和储存模块104。基于第一装置和第二装置的相互配合,运动辅助装置100的完整功能可以完全实现。
第一装置可以是穿戴设备400的一个部分,能穿戴在人身体的特定部位,比如,胸部、手腕、手臂,腰部或腿,并且感受和测量身体特定部位的生理信号。第二装置可以是一个延伸装置的一部分,比如手环、自行车仪表、智能手机、运动手表、健身器材,或任何一种组合。
具体来说,上述提到的延伸装置可以是一个手环401,它包括一个用户界面能显示用户在一个范围内的体力值,比如从100%到0%。上述提到的延伸装置也可以是一个装在自行车后面的指示灯402,能根据骑乘者的体力值发出不同的颜色或闪光。上述提到的延伸装置也可以是一个智能手机403,能接受和处理信息,在100%到0%的范围内显示用户的体力值,甚至能上传信息到互联网上(选择性),比如社交网络或各种类型的应用程序。
图5是体力值和RPE之间对应概念的示意图。
如图5所示,图中显示了体力值和自感劳累等级(RPE)之间的对应关系。另外,RPE的种类可以是伯格自感劳累等级(Borg Rating)。体力值是测量实时运动强度的结果。当疲劳值、血乳酸含量(血流中的乳酸含量)或实时的运动强度降低时,则体力值恢复。另一方面,当疲劳值、血乳酸含量(血流中的乳酸含量)或实时的运动强度增加时,体力值降低。
体力值能在一定的范围内呈现出来,比如100%到0%。另外,至少部分的体力值与RPE数值成线性或非线性相关。比如,对于使用运动辅助装置100的用户来说,RPE在11到13之间表示中等运动强度。也就是说,此时用户会感觉“轻松”级别的肌肉疲劳和呼吸,因此RPE值在11和13之间相当于100%的体力值。
另一方面,对于使用运动辅助装置100的用户来说,RPE值在15到17之间表示较高的运动强度。也就是说,用户会感觉“沉重”的肌肉疲劳和呼吸,因此RPE值在15和17 之间相当于0%的体力值。
列举一个例子来清晰地阐明,当体力值在100%时对应的RPE值为12,而体力值在0%对应的RPE值为16时,用户从体力值为0%恢复到100%的理想时间约为8到12分钟。
此外,把来自心脏的信号作为运动辅助装置100的输入作为例子,RPE数值与心率成线性或非线性比例,因此体力值也与心率成线性或非线性比例。在另一个例子中,,每一位用户的体力值在固定的范围内可以根据最大心率和最小心率进行标准化。
值得注意的是,尽管上述所提到以心率对应RPE数值和体力值并进行标准化,其他的生理信号也能依相同概念加以应用。也值得注意的是体力值可以是一个负值用于体力级别的自动调整计算,将会在下文中进一步解释。
图6是典型的体力级别和用户的身体素质之间关系的示意图。
如图6所示,体力值被分为10个等级,SC1到SC10。不同的体力级别对应一个人不同的体能和耐力。对很少运动的用户来说,体力级别的最初设置可以定于类别1(SC1),而对于专业运动员来说,体力级别的最初设置则可定于类别10(SC10)。
进一步说明,体力级别取决于用户输入的生物信息,并且在运动期间可以根据用户的反应修改,更具体地说是根据用户体力值的改变而修改。比如,运动辅助装置100包括一个默认的数据库储存于储存模块104内,根据用户的生物信息来决定用户的体力级别,所述生物信息比如年纪、性别、体重、身高和用户例行的运动数据(如:在用户最后一次运动过后储存在储存模块的体力级别信息)。用户能通过用户界面103输入或者从其他装置取得所述生物信息或例行运动数据(如:用户最后一次运动的体力级别信息)。
无论体力级别最初的设置(如:根据在运动辅助装置100中的用户生物信息或者已储存的体力级别),当体力值到达一定的阈值,此时用户并没有感到严重疲劳而继续运动,则用户的体力级别自动调整为更高的体力级别。因此,体力级别可以根据用户身体素质的变化自行适应调整。也就是说,当用户的身体条件改善,体力值会基于用户当前的体力级别去对应合适的RPE数值,因此能精准地体现用户的体力值。上述提到的体力级别的调整也可作为自动的RPE机制。
图7是本发明的一个具体实施例中的一种体力值指示器示意图。
如图7所示,体力值以条形物表示,所述体力值具有上边界204和下边界202分别表示0%及100%的体力值。加上另一个图形(如一个块状物206)表示当前的体力值,所述图形通过颜色、形状或样式与所述条形物区别。当用户当前的体力值增加或降低,块状物206改变形状、颜色或样式。
上边界204可对应于无氧阈值,所述无氧阈值是当血液中的乳酸因为运动而开始积累的阈值。下边界202则相当于用户因为运动产生的乳酸到达一定浓度而感到疲劳时的阈值。由于每一位用户对不同运动强度的耐力是不同的,因此每种体力级别下边界202的阈值也可以是不同的。虽然在本实施例中体力值是以条形物的形式表示,但体力值的表示并不限制于条形物,即各种类别的视觉图形也可适用。
图8是乳酸浓度和心率之间相关曲线示意图。
如图8所示,图7所提及的上边界204所对应的无氧阈值可被定义为当运动强度使乳酸浓度达到每升2~6 mmol的时候(休息未运动时大约每升1 mmol)。
例如,乳酸浓度为每升4 mmol 被定义为100%体力值,而任何浓度低于每升4 mmol时则认定用户当下的体力值为100%。
上述提到的无氧阈值的定义也可以与最大心率的65%到85%相对应。此外,用户的最大和最小心率是根据用户的年纪、性别、休息未运动时的状态、身高和体重评估而得。
乳酸浓度和心率之间相关曲线的一定斜率可被定义为100%的体力值,并以此取代前述无氧阈值的定义。比如,100%体力值可对应于曲线陡坡前一个点的曲线斜率,所述100%体力值此時也刚好对应每升2~6 mmol的乳酸浓度。
众所周知,每升4 mmol的乳酸浓度被认为是有氧运动和无氧运动之间的一个阈值。以有氧运动來,氧气是通过用户呼吸而进入肌肉组织中,肌肉组织方能提供维持活动所需的能量。就无氧运动來,因為运动强度高而引起乳酸的形成,而乳酸的形成则会造成不适和疲劳。
图9是一个示意图说明用户运动时乳酸浓度随着运动时间改变,以及相应的体力值变化。
如图9所示,当乳酸溶度在每升2~6 mmol的范围内时,相应体力级别的用户的体力值被设定为100%。当用户连续运动时,乳酸浓度增加而体力值降低。一旦乳酸浓度到达一个阈值,即在时间为t1时乳酸浓度为L1,用户的体力值达到0%。也就是说,用户的自感劳累值大约在15到17,此时可以建议用户选择降低运动强度来消除累积的乳酸,因此体力值在t1到t2时间内从0%恢复到100%。值得注意的是在一个运动或比赛过程中,从0%恢复到100%是不必要的,而从0%恢复到一定的百分比能让用户在运过或比赛的过程表现得更好。
再次参阅图7,下边界202 的值是根据前述的乳酸浓度在t1到t2时间内降低达到的预定值,比如低于每升4 mmol。无论体力级别,不同用户的完全恢复所需的时间是相似的,比如体力值从0%到100%大约需要8分钟到12分钟。
图10是本发明的一个具体实施例中用来评估体力值的一种方法流程图。
如图10所示,在步骤S101,运动辅助装置100首先根据用户的生物信息或储存在运动辅助装置100中的体力级别,设置用户的最初体力级别和体力值。所述储存的体力级别与用户最后一次运动时的体能状态相关。
在步骤S102,通过传感器模块101获取用户的生理信息。生理信息Pt 可以是当前的心率、活动强度、耗氧量或者其中任何的组合。
在步骤S103,根据生理信息(Pt)、当前的体力值(St)、最初的体力级别和生物信息计算体力值的差异(ΔS)。
然后,在步骤S104,将St 和ΔS相加以计算下一时间的体力值St+1。在步骤S105,当体力值增加或降低到某个特定的阈值时,运动辅助装置100会提醒用户。在步骤S106,根据St+1(如体力级别从SC3到SC4),体力级别可维特在当前的体力级别或者调整到更高的体力级别。
应该注意的是运动辅助装置100根据最初体力级别进行调整以更新储存的体力级别的信息。也应该值得注意的是,在用户的运动或比赛期间,运动辅助装置100会反复地执行步骤S102到S106,因此自动的RPE机制能维持有效。
图11是本发明至少一个具体实施例中针对发送通知给用户的条件示意图。
如图11所示,运动辅助装置100会在在体力值等于或接近等于0%时,或者其他预定值不高于50%或不低于50%的情况下发送通知给用户。比如,当体力值下降到60%,30%或0%时发送通知。另外,当体力值恢复到30%或60%时,也可发送通知。
只要能使用户意识到通知,通知可以是任何形式。例如:通知可以是声音,可视的或可振动的通知。 运动辅助装置100通过用户界面103发出通知以提醒用户运动强度应该被降低进而减轻疲劳感或者提醒关于用户的其他健康状况。另外,不同的体力值可以设定不同类型的通知。例如,当体力值从60%下降到30%时,会使用3个短的振动通知;当体力值从30%下降到达0%的体力值时,会使用一个长的振动通知;当体力值从0%上升到达30%的体力值或者体力值从30%到达60%的体力值时,会使用一个短的振动通知。
图12是本发明的至少一个具体实施例中用来调整体力级别的一种方法流程图。
如图12所示,在步骤S201,当体力值下降到第一阈值(或者一个预定值),比如,0%的体力值,发送一个通知给用户。在步骤S202,如果用户相应地降低运动强度并且体力值开始恢复到第一阈值之上,则维持当前的体力级别不作调整并结束方法。
反之,在步骤S203,如果用户忽视S202的通知而继续运动直到体力值到达第二阈值(或预定值)之下,比如,负40%的体力值,则将体力级别被调整到一个更高的体力级别(例如将体力级别从SC3调整到SC4)。
在步骤S204,如果用户忽视S202而继续运动,同时体力值仍然维持在第一预定值和第二预定值之间,比如,在0%到负40%体力值之间,并且持续维持超过第一时间周期(一个预定的时间),比如,4到6分钟,也将体力级别调整到一个更高的体力级别(例如将体力级别从SC3调整到SC4)。另一方面,如果体力值持续保持在第一和第二预定值之间,但并不超过第一时间周期(一个预定时间),则维持当前的体力级别不作调整并结束方法。
在一段时间内,每一位用户的体力值会随着运动强度增加或减少。在同样的时间内,不同体力级别的不同用户会消耗不同的体力值。比如,在同样的条件下体力级别3(SC3)的用户消耗体力值到0%的会快于体力级别5(SC5)的用户,因为体力级别5的用户体力强于体力值3的用户。
因此,如果用户没有适当地设定最初的体力级别,用户可能在体力值达到0%之后继续运动却并没有感到严重的疲劳,而可能因此造成训练或比赛失败的突发状况。因此,依据用户的体能状况调整体力级别方能精确且有效地设定用户的体力级别。根据图12的调整方法,体力级别能被自动地调整为更高的体力级别。
图13是体力值能自动按照图12中的方法流程调整的示意图。
如图13所示,以两个条件为例,在这两个条件下体力级别可以自动调整。在第一个条件下,对于最初体力级别为SC3的用户来说,如果用户的体力值达到0%以下,而用户忽略通知并且继续运动直到体力值到达-40%以下,则用户的体力级别自动调整为SC4。
然后在第二个条件下,对于最初体力级别为SC4的用户,如果用户的体力值到达0%之下,而用户忽略通知并且继续运动,当体力值继续维持在0%和-10%之间超过第一时间周期(如:5分钟),用户的体力级别自动调整为SC5。
图14A和14B是本发明的至少一个具体实施例中乳酸浓度分别与心率及 RPE之间的关系示意图,图14C是体力值与乳酸浓度及RPE的对应示意图。
如图14A所示,一般来说用户的心率是与乳酸浓度为正相关,两者之关系可以用线性回归模型、非线性回归模型、分段函数及其他数学模型或以上任意组合进行模拟。因此,涉及血液中乳酸累积的乳酸浓度能根据用户的心率而估算出来。
如图14B所示,由于心率与RPE数值是正相关或者几乎成比例地有关,因此乳酸浓度也与RPE数值是正相关或者几乎成比例地有关。当乳酸浓度为低浓度时,用户在持续的运动中感觉“轻松/简单”;反之,当乳酸浓度为高浓度时,用户在持续的运动中感觉“沉重/困难”或甚至“无法维持”。
如图14C所示,基于图14A和14B的说明,体力值直接与乳酸浓度相关。此外,如图7所示体力值能被描绘成长条形的体力值指示计。例如,当乳酸浓度到达图14C的左边的预定阈值,此时体力值被认定为100%。而当乳酸浓度随着上述提到的线性或非线性的数学模型增加,体力值指示计开始减少,正如在图14C中以白色和黑色箭头表示。
图15A和15B是乳酸浓度和运动强度之间或乳酸浓度和耗氧量之间的关系示意图。
如图15A和15B所示,与血液中乳酸累积相关的乳酸浓度能根据除了心率以外的其他生理信号被估算出来。例如,传感器模块101能监测到的用户运动强度或耗氧量,而所述运动强度或耗氧量与乳酸浓度成正相关并且可以用线性回归模型、非线性回归模型、分段函数、其他数学模型或以上任何组合进行模拟。
用户的体力值能在一段时间内被记录下来,比如,在训练、竞赛/比赛、挑战等之间。另外,体力值记录能被上传到网络作进一步应用,比如在社交网络上表达或相互交流。进一步地,体力值记录可以与各种参数结合来满足用户对不同应用的需要,例如,体力值能与心率、速度、时间、地图、温度、湿度、高度、热量消耗、运动效率、预估的最大运动位移至少其中一个结合,或者任何一个其中的组合。值得注意的是体力值记录能实时地或在一段时间之后输出或汇出。
图16是依据用户的体力值和运动速度评估用户的最大运动位移的典型应用方法示意图。
首先,用户能回头检视体力值记录的历史来评估自己在一定距离、速度、地形、温度或天气条件下的体力值变化,进而调整他们下一次运动的速度或路线。用户也可以监控自己数天或数周在相同路线的体力值变化来评估体能的进步。
如图16所示,用户的体力值在一时间段内与用户的运动速度相关。比如,如果用户完成一个5公里的跑步运动尚余10%的体力值,运动辅助装置100能估算用户运动耗尽100%体力值的运动距离。
通过用户即时的速度乘以体力消耗时间即可估算与剩余的10%体力值相关的额外距离,上述提到的额外距离指的是以剩下的体力百分比所估算的距离,例如,如果估计剩余的10%体力值相当于额外距离1公里,则运动辅助装置100可以提醒用户100%的体力相当于一个全程6公里的跑步运动。
因此,估计的最大运动位移可以被应用在训练计划的设计中。比如,用户可以有一训练计划,在第一天和接下来的数天中有不同的距离目标。比如,第一天运动辅助装置100显示用户的运动记录距离为10公里,但是估计的最大运动位移为11公里,表示通过未使用的体力百分比所估计的距离为1公里。在第三天,估计的最大运动位移达到22公里。因此在一个合理的预估下,使用运动辅助装置100的用户已准备好在第四天练习22公里。
值得注意的是,由于每位用户的体力值皆可归纳到一个0%到100%的范围,所以不同体力级别的不同用户可以相互比较他们的体力值记录来调整自己的运动量。在另一个例子中,一个健身房教练可以监控一个班级里所有成员的体力值,进而告知每位成员相应地调整他/她的运动量。
图17是本发明的一个具体实施例中用户的体力值连同地图一并输出的示意图。
如图17所示,体力值记录能连同GPS数据一起使用并将上述两者与地图关联,进而评估用户体力值急剧消耗的地点,比如,在一个陡峭的山顶。
上述用户体力值急剧消耗的地点可能有益于水或食物的商店店主评估设置商店的地址。另外,上述用户体力值急剧消耗的地点可与被一些特定设备所捕捉到的信息相联系,比如录像机或一个照相机,因此用户的视频能与用户的体力值一起通过互联网观察到。
图18是通过利用用户的体力值评估用户的热量消耗的应用示意图。
如图18所示,用户的体力值能以数学模型对应到用户的热量消耗。比如,如果用户用一种稳定的速度训练,则体力值的稳定减少相当于恒定的热量消耗。在训练期间总共的热量消耗能通过恒定的热量消耗乘以运动总时间来评估。如果用户在时间t1增加运动负荷,热量消耗变得更高。但是,用户可能无法长时间维持增加的运动负荷,因此在时间t1后的热量总消耗也会随着降低。如果对于用户来说主要的目标是通过最大化的热量燃烧来减重,运动辅助装置能表明运动负荷(即体力值降低速率)和热量总消耗之间的关联性,并且发送通知给用户建议合理的运动负荷。
图19是本发明的一个具体实施例的基于生理信号评估体力值的一种方法。
在本发明的一个具体实施例中,体力值是无氧能量值和有氧能量值的结合体,其中体力值与无氧能量值和有氧能量值成正相关,所述正相关能以线性回归模型、非线性回归模型、分段函数模型、其他数学模型或以上任一组合进行模拟。
如图19所示,以下步骤可以根据生理信号评估体力值:
S301:接收来自用户界面103的生物信息;
S303:通过传感器模块101测量生理数据(Pt);
S305:通过处理模块102根据生理数据评估无氧能量值的百分比;
S307:通过处理模块102根据生理数据(Pt)和生物信息评估有氧能量值的百分比;
S309:通过处理模块102根据无氧能量值和有氧能量值的百分比评估体力值的百分比。
在本发明的一个具体实施例中,只要S301在步骤S307之前,S303在步骤S305和S307之前,在满足以上前提的情况下,步骤S301、S303、S305和S307的顺序是可互换的。
在本发明的一个具体实施例中,生物信息能包含至少一个以下所提到的:身高、体重、年纪和性别等。
在本发明的一个具体实施例中,生理数据(Pt)能包含至少一个以下所提到的:EKG信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度和氧浓度等。每当生理数据(Pt)被测量时,生理数据(Pt)能被保存在储存模块104中作为后续使用或者发送到处理模块102来评估无氧能量和有氧能量。
在本发明的一个具体实施例中,体力值(St%)可以通过处理模块102对应到RPE值,并通过用户界面103输出给用户。
在本发明的一个具体实施例中,无氧能量值与乳酸浓度的积累相关,有氧能量值与额外的热量消耗相关。在这种情况下,可以根据乳酸浓度的累积和额外的热量消耗并使用线性回归模型、非线性回归模型、分段函数、其他的数学模型或者其中任一组合来评估体力值(St%)。
图20是本发明的一个具体实施例的根据生理信息评估无氧能量的一种方法,其中这个方法是图19中步骤S305的展开。
如图20所示,以下步骤可以根据生理数据来评估无氧能量:
S401:从储存模块104获得无氧评估设置,比如无氧能量等级(无氧C)和最大无氧能量值(无氧max );
S403:从储存模块104获得最后一次记录的无氧能量值(无氧t-1);
S405:从储存模块104获得生理数据(Pt);
S407:通过处理模块102根据生理数据(Pt)、无氧评估设置和最后一次记录的无氧能量值(无氧t-1)评估无氧能量值(无氧t);
S409:通过处理模块102使用无氧能量值(无氧t)、最大无氧能量值(无氧max )和最小无氧能量值(无氧min),计算无氧能量值的百分比(无氧t%)。
在本发明的一个具体实施例中,S401、S403和S405的顺序是可以互换的。
在本发明的一个具体实施例中,在步骤S405中,除了从储存模块104中获得生理数据(Pt)外,也可以通过传感器模块101来测量取得生理数据(Pt)。因此,测量无氧能量的方法可以被单独使用而不涉及图19中的方法。
在本发明的一个具体实施例中,无氧能量等级(无氧C)可以是乳酸稀释速率或乳酸产生速率。
在本发明的一个具体实施例中,无氧能量值可以是用户乳酸浓度的积累,最大无氧能量值(无氧max )可以是一个人理论上可以承受的最大乳酸浓度,其中,最大乳酸浓度会随着调整无氧评估设置而改变。比如,一位专业运动员可以承受比一个业余跑者更高的乳酸浓度。另外,甚至同一个人可以承受不同的乳酸浓度。比如,一个人停止运动一段时间,这个人与以前相比可能仅仅能承受较低的乳酸浓度。另一个例子是一个人很规律地运动,他与以前相比可能承受较高的乳酸浓度。因此,最大的无氧能量值(无氧max )可以被预先设定为一个特定的值,并在每次运动辅助装置100评估体力值(St%)时适度调整运动辅助装置100来评估体力值(St%)。或者,也能在运动辅助装置100被用户关掉或打开之后执行所述调整。调整无氧评估设置的方法稍后会被介绍。
在本发明的一个具体实施例中,最小无氧能量值(无氧min)可以是用户运动时能维持而不会急剧增加的乳酸浓度。在这种情况下,如图8所示最小无氧能量值(无氧min)可以被设置为4 mmol/L。最小无氧能量值(无氧min)可以是运动辅助装置100上预先设定或用户使用用户界面103输入的一个恒定值。
在本发明的一个具体实施例中,最后一次记录的无氧能量值(无氧t-1)可以是最后一次评估无氧能量值后储存在储存模块104中的一个值。假设用户第一次使用运动辅助装置100且没有做运动的情况下,所述无氧t-1等于无氧min。
图21是本发明的一个具体实施例的基于生理数据评估有氧能量的一种方法,其中这个方法是图19中步骤S307的展开。
如图21所示,以下步骤根据生理数据评估有氧能量:
S501:从储存模块104中获得有氧评估设置,比如有氧能量等级(有氧C)和最后一次记录的有氧能量值(有氧t-1);
S503:从储存模块104中获得生物信息;
S505:从储存模块104中获得生理信号(Pt);
S507:通过处理模块102根据生理信号(Pt)、生物信息、最后一次记录的有氧能量值(有氧t-1)和有氧能量恒定值(有氧常数)评估有氧能量值(有氧t);
S509:通过处理模块102使用有氧能量值(有氧t)和有氧能量等级(有氧C)来计算有氧能量值占有氧能量等级(有氧C)的百分比(有氧t%)。
在本发明的一个具体实施例,步骤S501,S503和S505的顺序是可以互换的。
在本发明的一个具体实施例中,在步骤S505,除了从储存模块104中获得生理数据(Pt)外,也可以通过传感器模块101来测量取得生理数据(Pt)。因此,测量有氧能量的方法可以被单独使用而不涉及图19中的方法。
在本发明的一个具体实施例中,有氧能量等级(有氧C)可以是用户的有氧能量容量,其中有氧C可以是一个预先设定并储存在储存模块104中的值。有氧C越高,意味着用户的有氧能量容量越高,则身体耐力越好。因此,由步骤S509评估的有氧能量值百分比可以表明有氧能量值占有氧能量容量的比例。
在本发明的一个具体实施例中,最后一次记录的有氧能量值(有氧t-1)可以是上次评估有氧能量时储存于储存模块104中的有氧能量值(有氧t)。假设用户第一次使用运动辅助装置100且没有做运动的情况下,所述有氧能量值(有氧t-1)等于有氧能量等级(有氧C)。
在本发明的一个具体实施例中,有氧能量恒定值(有氧常数)可以是一个普通人没有运动时的有氧能量消耗速率,其中这个速率可以是预先设定在运动辅助装置100中的恒定值。值得注意的是,用户无时无刻都持续地消耗有氧能量,即使在睡着时仍是如此。因此,当用户运动的时候用户的有氧能量消耗量就会高于有氧能量恒定值,当用户恢复的时候用户的有氧能量消耗量的变化会低于有氧能量恒定值。换句话说,当用户正在运动时额外的有氧能量消耗是正数,当用户正在恢复时额外的有氧能量消耗是负数。正如图19所提及的,有氧能量可以与额外的热量消耗有关,其中额外的热量消耗即是用户的有氧能量消耗和有氧能量恒定值之间的差值。因此,在步骤S507中,有氧C减去额外的热量消耗即可评估有氧能量值。
图22是本发明的一个具体实施例,所述实施例是基于图19中根据生理数据评估体力值(St%)再加上设置调整的一种方法。
在本发明的一个具体实施例中,图19中评估体力值(St%)的方法可以经由包括无氧评估设置和有氧评估设置的调整而改善,其中无氧评估设置和有氧评估设置可以被更新进而改善评估体力值(St%)的准确性。由于无氧评估设置和有氧评估设置不能在每次执行图20到21的方法时用来准确地表现用户真实的身体状况,因此无氧评估设置和有氧评估设置可以在无氧能量值和有氧能量值评估之后被更新。
如图22所示,以下步骤可以在图19中描述的方法之后执行。
S311:通过处理模块102根据无氧能量值(无氧t)调整无氧评估设置。
S313:通过处理模块102根据有氧能量值(有氧t)调整有氧评估设置。
在本发明的一个具体实施例中,步骤S311可以在步骤S305之后执行,步骤S313可以在步骤S307之后任何时间执行。
图23是本发明的一个具体实施例的调整无氧评估设置而后可用来估计体力值(St%)的一种方法,其中这种方法是在图22中步骤S311的详细阐述。
如图23所示,以下步骤可以用来调整无氧评估设置而后用于图22中的方法:
S601:通过处理模块102比较是否无氧能量值(无氧t)大于或者等于最大无氧能量f(无氧max)的函数,如果是继续步骤S603,否则继续步骤S607。
S603:通过用户界面103发送一个通知给用户。
S605:通过传感器模块101感受用户是否降低运动强度,如果是继续步骤S609,否则退出。
S607:通过处理模块102比较在X分钟内是否无氧能量值(无氧t)持续大于或者等于无氧阈值,如果是继续步骤S603,否则退出。
S609:通过增加无氧能量等级比如无氧C+ 1,并且无氧能量值(无氧t)将会被用作新的最大无氧能量用于下一轮无氧能量值的评估,以调整t + 1的无氧评估设置。
在本发明的一个具体实施例中,最大无氧能量的函数f (无氧max)如f (无氧cmax) = 2.5*无氧max可以预先设定并保存在储存模块104中 。或者,用户可以自行设定一个值以替换最大无氧能量f (无氧cmax)。比如,当无氧能量值是乳酸浓度,最大无氧能量的函数可以被一个值替换,比如10 mmol/L。如果无氧能量值(无氧t)评估为12 mmol/L,则运动辅助装置100将会发送通知给用户。
在本发明的一个具体实施例中,无氧阈值和X分钟可以被预先设定并保存在储存模块104中。或者,用户可以自行设定无氧阈值和X分钟。比如,当无氧能量值是乳酸浓度时,无氧阈值可以是6 mmol/L, X分钟可以是5分钟。如果无氧能量值(无氧t)被估计为7mmol/L并持续5分钟,则运动辅助装置100将会发送通知给用户。
在步骤S609中,无氧C + 1表示通过预先设定的数量而逐渐增加无氧C,预先设定的数量可以是一个定值或者百分比。例如,无氧C + 1可以是增加乳酸稀释速率或者减少乳酸产生速率到1 mmol/L或5%。对于下一轮无氧能量值评估来说,新的最大无氧能量可以是无氧能量值(无氧t)或者来自最大无氧能量(无氧max)加上的预先设定的增量。
在本发明的一个具体实施例中,在步骤S603中的通知可以以多种形式发送给用户,比如可视的、声音的和振动等等。
在本发明的一个具体实施例中,在步骤S605中,传感器模块101可以通过生理数据(Pt)的改变感受用户是否降低运动强度。比如,通过传感器模块101感受到的生理数据(Pt)是心率。如果在时间t感受到的心率低于之前记录的心率,运动辅助装置100可以确定用户减少运动强度。
调整无氧评估设置的方法可以被应用在运动辅助装置100低估用户体力和耐力的情况。当用户满足S601或S607的条件并且运动辅助装置100没有感受到在生理数据上的任何变化,它表明在运动强度上并未降低,则运动辅助装置100根据步骤S609调整无氧评估设置。在无氧能量值是乳酸浓度的条件下,S609的调整不仅增加最大无氧能量而且增加乳酸稀释速率或降低乳酸产生速率,为了使用在下一轮的无氧能量评估中作为无氧评估设置。
图24是本发明至少一个具体实施例的调整有氧评估设置而后可用来评估体力值(St%)的一种方法,其中在图22中这种方法是步骤S313的详细阐述。
如图24所示,以下步骤可以用来调整有氧评估设置而后用于图22中的方法:
S701:通过处理模块102比较是否有氧能量值(有氧t)低于或者等于最小有氧能量阈值,如果是继续步骤S703,否则退出;
S703:通过用户界面103发送通知给用户;
S705:通过传感器模块101,感受用户是否降低运动强度,如果是继续步骤S707,否则退出;
S707:通过增加有氧能量等级比如有氧c + 1,并且将最后一次记录的有氧能量值(有氧t-1)更新为f (有氧c + 1, 有氧t%),以调整t + 1的有氧评估设置。
在本发明的一个具体实施例中,最小的能量阈值可以是预先设定和储存在储存模块104中。比如,最小的有氧能量阈值可以是有氧C的5%。
在本发明的一个具体实施例中,在步骤S703中的通知可以以多种形式发送给用户,比如:可视的、声音的和振动等等。
在本发明的一个具体实施例中,在步骤S705中,传感器模块101可以通过生理数据(Pt)的变化感受用户是否降低运动强度。比如,传感器模块101感受到的生理数据(Pt)是心率。如果在时间t感受到的心率低于之前记录的心率,比如:Pt < Pt-1,运动辅助装置100可以确定用户降低运动强度。
在步骤S707中,有氧C + 1表示通过一个预先设定的数量而逐渐增加有氧C,预先设定的数量可以是一个定值或者百分比。例如,有氧C + 1可以通过增加1或者有氧C的5%来作为新的有氧能量容量,并用于下一轮有氧能量值评估。对于下一轮有氧能量值评估来说,最后记录的有氧能量值(有氧t-1)可以根据比如有氧t-1=新的有氧能量容量*有氧t%进行调整。
调整有氧评估设置的方法可以被应用在运动辅助装置100低估用户体力和耐力的情况。当用户满足步骤S701的条件并且运动辅助装置100没有感受到生理数据上的任何改变,它表明在运动强度上并未降低,则运动辅助装置100根据步骤S707调整有氧评估设置。在有氧能量值与额外的热量消耗有关的情况下,S707的调整不仅增加有氧能量容量,即有氧C,而且相应地增加有氧t-1,为了使用在下一轮的无氧能量评估中作为无氧评估设置。
图25是本发明的一个具体实施例的用来评估最大热量消耗的一种方法。正如之前所提到的,用户的有氧能量值会一直持续消耗,因此有氧能量消耗只会增加不会减少。于用户使用运动辅助装置100监控体力值(St%)时,每一次有氧能量值(有氧t)的评估可以连同体力值(St%)一起被记录,然后保存在储存模块104中。因此有氧t-1 减去有氧t将是一个有氧能量消耗的差值(Δ有氧)。每一个有氧能量消耗的差值(Δ有氧)可以与体力值(St%)相结合作为一组有氧能量数据(有氧数据)。正如之前提到的,有氧能量值可以与额外的热量消耗相关,所以有氧能量消耗差值(Δ有氧)可以是从t-1 到 t的热量消耗的差值。因此,在时间t的实际热量消耗将是Δ有氧 + 有氧常数。
如图25所示,以下步骤可以通过处理模块102和储存模块104来评估用户可实现的最大热量消耗:
S801:从储存模块104中获得的有氧能量数据(有氧数据)的N组,其中每组有氧能量数据(有氧数据)包括体力值(St%)和从时间t-1到时间t有氧能量消耗差值(Δ有氧)。
S803:以有氧能量消耗的差值(Δ有氧)加上有氧常数的N组总和计算热量总消耗(热量合计);
S805:对于每组有氧数据,比较是否体力值(St%)低于来自前一组的有氧数据的体力值(St-1%);
S807:将所有满足S805条件的有氧数据保存于储存模块104中。
S809:对于每组保存的有氧数据,通过有氧能量消耗差值(Δ有氧)、有氧常数、体力值(St%)、前一组的体力值(St-1%)和一个加权变量的一个函数,计算有效热量消耗率(eff_calorie_rate);
S811:通过∑(eff_calorie_rate) *最后记录体力值 (St%) + 热量合计评估最大热量消耗,也就是说对于来自S809的每组保存的有氧数据,将有效热量消耗率(eff_calorie_rate)的总和乘以N组有氧数据中最后记录的体力值(St%),并加上热量总消耗(热量合计)到乘法运算结果中以得到最大热量消耗。
在本发明的一个具体实施例中,步骤S803可以在S801和S811之间的任何时间被执行。
当用户想知道在体力值(St%)到达0之前总共可以消耗多少热量,则可以运用评估最大热量消耗的方法。
在本发明的一个具体实施例中,在步骤S803中,热量总消耗(热量合计)可以通过用户界面103输出,所以用户能监测到目前为止的热量消耗。另外,热量合计可以从最大热量消耗中被减掉,然后输出给用户,所以用户可以知道在最后记录的体力值用完之前能再消耗多少热量,所述最后记录的体力值即是剩余的体力。
在本发明的一个具体实施例中,热量合计及/或最大热量消耗可以以各种形式被输出给用户,比如视觉的、声音的和振动等。
在本发明的一个具体实施例中,每一组保存的有氧数据都有各自的加权变量。假设体力值(St%)消耗的每一个百分比需要等量的时间,加权变量可以代表有氧能量消耗对消耗的体力值(St%)的每一个百分比的贡献。对于保存的有氧数据中特定的一组,热量燃烧的贡献可以是该组中的有氧能量消耗差值(Δ有氧)与所有保存的有氧数据的有氧能量消耗差值(Δ有氧)的总和之间的一个比率。
在本发明的一个具体实施例中,有效热量消耗率(eff_calorie_rate)是当体力实际被消耗时的热量消耗速率。换句话说,有效热量消耗率是用户消耗每个百分比的体力所能燃烧的热量。
图26是本发明的一个具体实施例的评估最大运动位移的一种方法。当用户使用运动辅助装置100监控体力值(St%)时,传感器模块101可以记录每一个体力值(St%)和运动传感器(未显示于图示)从时间t-1到t时感受到的运动位移值(ΔDis),并保存在储存模块104中。运动传感器可以是传感器模块101组成的一部份,所述运动传感器可以是下面中的一个:陀螺仪、加速器、计步器、运动节奏监控器、速度计、GPS接收器,或功率计,其中运动传感器也可以直接或间接地提供实时地位移信息,比如速度、海拔、斜坡坡度等。每一个位移值(ΔDis)可以与体力值(St%)结合作为一组运动数据(ex_data)。运动传感器可以测量用户运动的运动力量、运动节奏(如:划水频率、步伐频率等)、位移信息等。
如图26所示,以下步骤能通过处理模块102和储存模块104来评估用户可以实现的最大运动位移:
S901:从储存模块104中获得N组运动数据(ex_data),其中每组运动数据(ex_data)包括体力值(St%)和从时间t-1 到 t位移值(ΔDis);
S903:以所有位移值(ΔDis)的总和计算总运动位移(dis_total);
S905:对于每组运动数据,比较是否体力值(St%)低于来自前组运动数据的体力值(St-1%);
S907:保存满足S905条件的运动数据到储存模块104中;
S909:对于每组保存的运动数据,通过位移值(ΔDis)、体力值(St%)、前组的体力值(St-1%)和一个加权变量的函数来计算有效运动位移(eff_dis_rate);
S911:通过∑(eff_dis_rate) * 最后记录的体力值 (St%) + dis_total,评估最大运动位移,也就是说对于来自S909的每组保存的运动数据,将有效运动位移率(eff_dis_rate)的总和乘以N组运动数据的最后记录的体力值(St%),并加上总运动位移(dis_total)到乘法运算的结果中以得到最大运动位移。
在本发明的一个具体实施例中,步骤S903可以在S901和S911之间的任何时间执行。
在本发明的一个具体实施例中,在步骤S903中,总运动位移(dis_total)可以通过用户界面103输出,所以用户能监测到目前为止的位移。比如,跑步的距离、攀登的高度等等。另外,若将总运动位移从最大运动位移中减掉并输出给用户,用户可以知道最后记录的体力值用完之前能再进行多少的位移,所述最后记录的体力即是值剩余体力。这对用户来说特别有用,因为用户可以调整运动强度来实现期望的运动位移。比如,用户想骑行10公里。当运动辅助装置100估计最大运动位移为8公里,并通过用户界面103发送一个通知给用户。因此,用户可以减速来降低体力消耗率,进而用剩余的体力骑行多于8公里。如果最大运动位移被运动辅助装置100评估为12公里,用户可以增加骑行的速度,并且仍然能到达10公里。另外,运动辅助装置100可以根据用户消耗体力值的速率及用户的骑行速度之间的比率,从而建议用户可以骑多快仍然可以实现10公里的目标。此外,运动辅助装置100甚至可以计算用户可以发动几次进攻(当骑行在一个团队或者更小的组合里,以加速骑行的方式让用户和其他骑行者之间形成差距)并且仍然能取得10公里的目标。这可以通过预先设定用户需要牺牲的最大运动位移以实现进攻。比如,用户可以用最大运动位移中的3公里来进行每次的进攻。当用户的最大运动位移评估为17公里,用户可以做多余两次的进攻并且不用完全消耗用户所有的体力仍然取得10公里的目标。或者,当用户实现进攻时,运动辅助装置100可以通过追踪用户的心率、动作,或任何一个随着用户的运动强度而变化的运动因素,进而评估进攻时的体力消耗率或者最大运动位移的减少。通过处理模块102的计算之后,可用的进攻次数可以通过用户界面103输出给用户。因此特别当用户不想维持恒定的运动强度时,用户可以不费力地控制他/她的运动活动。
在本发明的一个具体实施例中,总运动位移及/或最大运动位移可以以各种形式输出给用户,比如视觉的、声音的和振动等等。
在本发明的一个具体实施例中,每一组保存的运动数据都有各自的加权变量。假设体力值(St%)消耗的每一个百分比需要等量的时间,加权变量可以代表位移对体力值(St%)消耗的每个百分比的贡献。对于保存的运动数据中特定的一组,位移的贡献可以是该组中的位移值(ΔDis)与所有保存的运动数据的位移值(ΔDis)的总和之间的一个比率。
在本发明的一个具体实施例中,有效运动位移速率(eff_dis_rate)是当体力实际被消耗时用户实现的位移速率。换句话说,有效位移速率是当用户消耗体力的每个百分比的时候用户能做多少位移。
在本发明的一个具体实施例中,传感器模块101可以测量用户的运动信息比如运动力量、运动节奏、速度、海拔、斜坡坡度、身体组成等等。来自传感器模块101的测量可以与在图10和图19中获得使用方法的体力值相关联。比如,通过运动力量的测量可以评估在运动期间或之后用户能发挥的最大运动力量。运动节奏的测量可以用来确定是否用户正在有效地运动或直接通过输出设备提供给用户一个最有效的运动节奏(如:跑步运动每分钟60步,骑行者每分钟60次踩踏,等)。位移信息可以用来评估用户身体对不同速度、海拔、坡度等变化之间的反应。因此,处理模块102可以使用运动信息的测量来评估用户身体的耐力及/或运动力量发挥。此外,根据用户身体的耐力及/或运动力量发挥可以进一步调整图23中的无氧评估设置及/或图24中有氧评估设置。身体组成可以被用来评估用户的身体能量密度。比如,将用户的肌肉密度和无氧能量值,及/或有氧能量值,及/或体力值等相联系。
之前的描述仅仅是本发明的一个具体实施例,并没有限制本发明的范围。根据所揭露的权利要求和说明书,许多变化和修改仍然在所要求发明的范围内。另外,每一个具体实施例和权利要求没有必须取得公开的所有优势或特征。而且,摘要和题目仅仅用来帮助搜索专利文件,而没有在任何方面限制所要求发明的范围。
Claims (42)
- 一种体力监控装置,包括:传感器模块,用来感受生理信号;用户界面,用来接收生物信息;储存器,用来储存生物信息和至少一数学模型;处理模块,用来执行至少一数学模型来操作以下事项:基于生理信号和生物信息来评估无氧能量和有氧能量;结合无氧能量和有氧能量并产生体力值。
- 如权利要求1所述的体力监控装置,其特征在于:所述无氧能量与乳酸浓度的累积有关。
- 如权利要求1所述的体力监控装置,其特征在于:所述有氧能量与热量消耗相关。
- 如权利要求1所述的体力监控装置,其特征在于:所述生物信息包括以下至少一项:身高、体重、年龄及性别。
- 如权利要求1所述的体力监控装置,其特征在于:所述传感器模块感受以下至少一项包括心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔以及斜坡坡度。
- 如权利要求1所述的体力监控装置,其特征在于:所述传感器模块包括能感受心率的心电传感器。
- 如权利要求1所述的体力监控装置,其特征在于:所述用户界面包括至少一输出装置,选自显示屏、震动组件或扬声器。
- 如权利要求1所述的体力监控装置,进一步包括:一带子,通过所述带子,所述体力监控设备被直接或间接地固定在用户的皮肤上。
- 如权利要求8所述的体力监控装置,其特征在于:所述体力监控设备被所述带子固定在用户的前额、手腕、腿部或手臂。
- 如权利要求1所述的体力监控装置,其特征在于:所述体力值被输出连同以下至少一参数包括心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
- 如权利要求1所述的体力监控装置,其特征在于:当所述无氧能量和/或所述有氧能量到达一阈值时,用户界面输出一通知。
- 如权利要求11所述的体力监控装置,其特征在于:所述通知是振动的通知、声音的通知,或可视的通知。
- 如权利要求1所述的体力监控装置,其特征在于:所述体力值可以进一步对应到自感劳累等级(RPE),并在用户界面输出。
- 如权利要求1所述的体力监控装置,其特征在于:所述处理模块进一步基于体力值和有氧能量来评估最大热量消耗。
- 如权利要求1所述的体力监控装置,进一步包括:一运动传感器,可以直接或间接提供实时地位移信息。
- 如权利要求15所述的体力监控装置,其特征在于:所述处理模块进一步基于体力值和位移信息评估最大运动位移。
- 如权利要求16所述的体力监控装置,其特征在于:用户界面输出可行的进攻次数,所述可行的进攻次数可以通过处理模块基于体力值或最大运动位移计算。
- 一种体力监控方法,包括:通过传感器模块感受生理信号;从用户界面接收生物信息;基于生理信号和生物信息,通过处理模块使用至少一储存在储存模块中的数学模型来估算无氧能量和有氧能量;基于无氧能量和有氧能量评估体力值;通过至少一输出装置输出体力值。
- 如权利要求18所述的体力监控方法,其特征在于:所述无氧能量与乳酸浓度的累积有关。
- 如权利要求18所述的体力监控方法,其特征在于:所述有氧能量与热量消耗有关。
- 如权利要求18所述的体力监控方法,其特征在于:所述生物信息包括以下至少一项包括身高、体重、年纪及性别。
- 如权利要求18所述的体力监控方法,其特征在于:所述传感器模块感受以下至少一项:心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔及斜坡坡度。
- 如权利要求18所述的体力监控方法,其特征在于:所述传感器模块包括能感受心率的心电传感器。
- 如权利要求18所述的体力监控方法,其特征在于:所述输出装置为一显示屏、一震动组件,或一扬声器。
- 如权利要求18所述的体力监控方法,其特征在于:所述体力值被输出连同至少一参数包括心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
- 如权利要求18所述的体力监控方法,其特征在于:当所述无氧能量和/或有氧能量到达一阈值时,至少一输出装置输出通知。
- 如权利要求26所述的体力监控方法,其特征在于:所述通知是振动的通知、声音的通知,或可视的通知。
- 如权利要求18所述的体力监控方法,进一步包括:通过处理模块,将体力值对应到RPE的等级;通过所述至少一输出装置输出RPE的等级。
- 如权利要求18所述的体力监控方法,进一步包括:通过处理模块基于体力值和有氧能量评估最大热量消耗。
- 如权利要求18所述的体力监控方法,进一步包括:从运动传感器中直接或间接地获得实时的位移信息。
- 如权利要求30所述的体力监控方法,进一步包括:通过处理模块基于体力值和位移信息评估最大运动位移。
- 如权利要求31所述的体力监控方法,进一步包括:通过用户界面输出可行的进攻次数,其中所述处理模块基于体力值或最大运动位移计算所述可行的进攻次数。
- 一种体力监控设备,包括:传感器模块,用来感受生理信号;用户界面,用来接收生物信息;储存器,用来储存生物信息和至少一数学模型;处理模块,用来执行至少一数学模型来操作以下事项:基于生理信号和生物信息来评估体力值;基于耐力值来评估运动辅助信息;发送体力值到包含有一输出装置的用户界面;通过用户界面输出体力值。
- 如权利要求33所述的体力监控设备,其特征在于:处理模块进一步地基于体力值和有氧能量评估最大热量消耗,其中有氧能量的评估是基于生理信号和生物信息。
- 如权利要求33所述的体力监控设备,进一步包括运动传感器,所述运动传感器直接或间接地提供实时的位移信息,同时处理模块进一步地基于体力值和位移信息评估最大运动位移。
- 如权利要求35所述的体力监控设备,其特征在于:所述处理模块基于体力值或最大运动位移计算可行的进攻次数并通过用户界面输出所述可行的进攻次数。
- 如权利要求35所述的体力监控设备,其特征在于:储存器进一步储存位移目标,当最大运动位移低于位移目标时,发送通知给用户。
- 如权利要求33所述的体力监控设备,其特征在于:所述输出装置为一显示屏、一震动组件,或一扬声器。
- 如权利要求33所述的体力监控设备,其特征在于:所述生物信息包括以下至少一项包括身高、体重、年纪及性别。
- 如权利要求33所述的体力监控设备,其特征在于:所述传感器模块包括感受心率的心电传感器。
- 如权利要求33所述的体力监控设备,其特征在于:所述体力值被输出连同至少一参数比如心率、速率、时间、地图、温度、湿度、高度、热量消耗、运动效率、身体组成、运动力量、运动节奏、速度、海拔、斜坡坡度、身体质量指数或被最大运动位移。
- 如权利要求33所述的体力监控设备,其特征在于:所述传感器模块感受以下至少一项:心电信号、心率变异性、脉搏、心率、呼吸模式、体温、血糖、血压、糖原浓度、氧浓度、身体组成、运动力量、运动节奏、速度、海拔及斜坡坡度。
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117435907A (zh) * | 2023-08-14 | 2024-01-23 | 北京体育大学 | 一种基于数据分析的体育记录检测方法及装置 |
Families Citing this family (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP6770749B2 (ja) * | 2015-07-17 | 2020-10-21 | Blue Wych合同会社 | 運動能力及び運動の評価システム |
CN107169269A (zh) * | 2017-04-24 | 2017-09-15 | 广东健凯医疗有限公司 | 健康运动能力评估***和方法 |
CN108211307B (zh) * | 2017-05-25 | 2019-11-12 | 深圳市未来健身科技有限公司 | 一种运动训练预警方法及装置 |
CN107510449B (zh) * | 2017-08-16 | 2020-07-28 | 深圳市微克科技有限公司 | 心率分析方法及智能穿戴设备 |
CN107951474A (zh) * | 2017-12-12 | 2018-04-24 | 北京动亮健康科技有限公司 | 基于心率和血压的实时监测的运动心肺测试方法及*** |
US11529087B2 (en) | 2018-04-12 | 2022-12-20 | Nippon Telegraph And Telephone Corporation | Anaerobic threshold estimation method and device |
EP3573071A1 (en) * | 2018-05-23 | 2019-11-27 | Bogumil Zieba | An electrocardiography telemetry system and method |
CN108771535A (zh) * | 2018-05-24 | 2018-11-09 | 合肥智慧龙图腾知识产权股份有限公司 | 一种可以缓解驾驶疲劳的电击手环 |
CN108786074B (zh) * | 2018-06-14 | 2019-06-25 | 浙江大学 | 运动训练负荷监测设备 |
TWI669676B (zh) * | 2018-07-19 | 2019-08-21 | 宏碁股份有限公司 | 運動數據分析方法及其電子裝置 |
CN109529303B (zh) * | 2018-11-09 | 2021-03-12 | 深圳市量子智能科技有限公司 | 一种用户运动能力的确认方法和*** |
JP7423043B2 (ja) * | 2018-11-22 | 2024-01-29 | Blue Wych合同会社 | トレーニング支援システム及びトレーニング支援方法 |
CN109363688A (zh) * | 2018-11-28 | 2019-02-22 | 河南职业技术学院 | 体育教学过程中的体能监控方法及装置 |
CN109589579B (zh) * | 2018-12-05 | 2020-11-13 | 英华达(上海)科技有限公司 | 一种骑行评估方法及*** |
CN109645970B (zh) * | 2018-12-25 | 2021-08-03 | 广州康盛科技有限公司 | 一种戒毒人员的心肺适能测评方法及设备 |
JP7037196B2 (ja) * | 2019-12-27 | 2022-03-16 | タグル株式会社 | アスレチック情報処理システム |
CN111530036B (zh) * | 2020-05-13 | 2021-08-10 | 广东高驰运动科技有限公司 | 跑步运动成绩预测方法及电子设备 |
CN111530037B (zh) * | 2020-05-13 | 2021-10-01 | 广东高驰运动科技有限公司 | 用于评估跑步运动中身体机能反应状态的方法及设备 |
TWI753553B (zh) * | 2020-08-27 | 2022-01-21 | 棋展電子股份有限公司 | 用於團隊活動之穿戴式生理感測系統 |
TWI793927B (zh) * | 2021-12-16 | 2023-02-21 | 國立臺灣師範大學 | 步頻強度監測記錄裝置 |
EP4201306A1 (en) * | 2021-12-23 | 2023-06-28 | Polar Electro Oy | Apparatus, method and computer program product for providing audio guidance during exercise |
CN114618149B (zh) * | 2022-05-17 | 2022-08-02 | 成都尚医信息科技有限公司 | 一种基于不同用户心率和rpe反馈的动作调整*** |
CN117982860A (zh) * | 2022-11-03 | 2024-05-07 | 华为技术有限公司 | Hiit的引导方法、电子设备以及存储介质 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5615685A (en) * | 1994-05-30 | 1997-04-01 | Casio Computer Co., Ltd. | Personal physical fitness measuring apparatus |
CN1291904A (zh) * | 1998-02-26 | 2001-04-18 | 欧姆龙株式会社 | 运动器械、体力评价方法以及搏动计 |
CN2748033Y (zh) * | 2004-07-23 | 2005-12-28 | 日本精密测器株式会社 | 持久性体力评价装置 |
CN102098961A (zh) * | 2008-05-14 | 2011-06-15 | 埃斯潘美国控股有限责任公司 | 身体活动监测器和数据收集单元 |
US20150250417A1 (en) * | 2013-08-19 | 2015-09-10 | bOMDIC Inc. | Stamina monitoring method and device |
Family Cites Families (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FI20025038A0 (fi) * | 2002-08-16 | 2002-08-16 | Joni Kettunen | Menetelmä fysiologisen signaalin analysoimiseksi |
US8157731B2 (en) * | 2002-10-09 | 2012-04-17 | Bodymedia, Inc. | Method and apparatus for auto journaling of continuous or discrete body states utilizing physiological and/or contextual parameters |
CN100409809C (zh) * | 2004-07-21 | 2008-08-13 | 松下电工株式会社 | 体力活动测量*** |
US20060167387A1 (en) * | 2005-01-27 | 2006-07-27 | Horst Buchholz | Physical activity monitor |
JP4500184B2 (ja) * | 2005-02-28 | 2010-07-14 | Npo法人熟年体育大学リサーチセンター | 持久力算出装置、持久力算出方法及びプログラム |
JP2007075172A (ja) * | 2005-09-12 | 2007-03-29 | Sony Corp | 音出力制御装置、音出力制御方法および音出力制御プログラム |
CN100435718C (zh) * | 2005-12-07 | 2008-11-26 | 王国樑 | 配合运动器材以检测使用者心肺耐力的方法 |
JP4971808B2 (ja) * | 2007-01-17 | 2012-07-11 | パナソニック株式会社 | 歩行動作分析装置 |
JP4521040B2 (ja) * | 2008-02-28 | 2010-08-11 | 株式会社シマノ | 消費カロリ測定装置及び消費カロリ測定方法 |
WO2009118645A1 (en) * | 2008-03-27 | 2009-10-01 | Polar Electro Oy | Apparatus for metabolic training load, mechanical stimulus, and recovery time calculation |
FR2947733B1 (fr) * | 2009-07-09 | 2015-01-23 | Ressources Et De Dev Pour Les Entpr S Et Les Particuliers Srdep Soc D | Dispositif d'aide a la pratique d'une seance d'activite physique et appareil d'activite physique equipe d'un tel dispositif |
FR2967565B1 (fr) * | 2010-11-19 | 2012-11-30 | Centre Nat Etd Spatiales | Dispositif d'assistance a l'effort physique permettant de prevoir l'evolution d'un parametre physiologique en fonction d'un itineraire |
CN201958876U (zh) * | 2011-01-25 | 2011-09-07 | 赵杰修 | 高温环境下运动训练移动监控设备 |
CN202497134U (zh) * | 2012-01-13 | 2012-10-24 | 李晓霞 | 一种老年肥胖人群有氧负重健身走锻炼预测减重*** |
JP6037102B2 (ja) * | 2012-04-16 | 2016-11-30 | セイコーエプソン株式会社 | 情報処理装置、電子機器、移動支援情報提供システム及び移動支援情報提供方法 |
CN102750441B (zh) * | 2012-06-01 | 2015-07-01 | 合肥工业大学 | 一种骑自行车所消耗卡路里的计算方法 |
GB2505690B (en) * | 2012-09-07 | 2018-02-07 | Toumaz Healthcare Ltd | A device and method for estimating energy expenditure during exercise |
LU92104B1 (en) * | 2012-11-28 | 2014-05-30 | Iee Sarl | Method and system for determining a ventilatory threshold |
US9731184B2 (en) * | 2013-08-19 | 2017-08-15 | bOMDIC Inc. | Exercise assistive device |
CN104056445B (zh) * | 2014-07-01 | 2017-01-18 | 杭州攻壳科技有限公司 | 一种基于心率和加速度传感器的人体运动分析方法及其装置 |
CN104586377B (zh) * | 2014-12-27 | 2017-04-12 | 深圳市前海安测信息技术有限公司 | 用于预测士兵执行任务能力的检测***和方法 |
-
2016
- 2016-05-19 EP EP16170397.0A patent/EP3158928B1/en active Active
- 2016-05-19 ES ES16170397T patent/ES2901223T3/es active Active
- 2016-05-19 TW TW105115684A patent/TWI603717B/zh not_active IP Right Cessation
- 2016-05-20 JP JP2016101273A patent/JP6366637B2/ja active Active
- 2016-05-20 CN CN201610339437.7A patent/CN106166063B/zh active Active
- 2016-05-20 WO PCT/CN2016/082746 patent/WO2016184418A1/zh active Application Filing
- 2016-05-20 CN CN202010220598.0A patent/CN111387960B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5615685A (en) * | 1994-05-30 | 1997-04-01 | Casio Computer Co., Ltd. | Personal physical fitness measuring apparatus |
CN1291904A (zh) * | 1998-02-26 | 2001-04-18 | 欧姆龙株式会社 | 运动器械、体力评价方法以及搏动计 |
CN2748033Y (zh) * | 2004-07-23 | 2005-12-28 | 日本精密测器株式会社 | 持久性体力评价装置 |
CN102098961A (zh) * | 2008-05-14 | 2011-06-15 | 埃斯潘美国控股有限责任公司 | 身体活动监测器和数据收集单元 |
US20150250417A1 (en) * | 2013-08-19 | 2015-09-10 | bOMDIC Inc. | Stamina monitoring method and device |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117435907A (zh) * | 2023-08-14 | 2024-01-23 | 北京体育大学 | 一种基于数据分析的体育记录检测方法及装置 |
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CN111387960A (zh) | 2020-07-10 |
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