WO2005092193A1 - 負荷体状態判定装置、乗物用シート及びコンピュータプログラム - Google Patents
負荷体状態判定装置、乗物用シート及びコンピュータプログラム Download PDFInfo
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- WO2005092193A1 WO2005092193A1 PCT/JP2005/005147 JP2005005147W WO2005092193A1 WO 2005092193 A1 WO2005092193 A1 WO 2005092193A1 JP 2005005147 W JP2005005147 W JP 2005005147W WO 2005092193 A1 WO2005092193 A1 WO 2005092193A1
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- displacement
- load
- original waveform
- state
- inclination
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Classifications
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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
- A61B5/103—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
- A61B5/1116—Determining posture transitions
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
-
- 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
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/002—Seats provided with an occupancy detection means mounted therein or thereon
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/20—Workers
- A61B2503/22—Motor vehicles operators, e.g. drivers, pilots, captains
-
- 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
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6893—Cars
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/90—Details or parts not otherwise provided for
- B60N2002/981—Warning systems, e.g. the seat or seat parts vibrates to warn the passenger when facing a danger
Definitions
- the present invention relates to a load state determination device, a vehicle seat, and a computer program.
- the present invention relates to various seats such as a vehicle seat used for transportation equipment such as a car, a train, and an aircraft, an office seat, and a seat on which a person sits for inspection or diagnosis in a hospital or the like, or , Futons, mattresses, beddings such as beds, etc., which are provided on the load supporting means originally used for the purpose of supporting a person, and which are in a state of the load actually supported by the load supporting means.
- a load state determination device that can automatically make a determination and is particularly suitable for determining the state of a load supported on a vehicle sheet, a vehicle seat equipped with the load type determination device, and a load state. It relates to a computer program used for the judgment. Background art
- Patent Documents 1 and 2 disclose heartbeat or pulse. There has been proposed a technique for monitoring the state of a living body by analyzing chaos. According to the techniques disclosed in Patent Documents 1 and 2, it is not necessary to attach a powerful device for brain wave measurement to the head, and the biological condition of the driver can be easily evaluated.
- Patent document 1 JP-A-9-308614
- Patent Document 2 JP-A-10-146321
- Patent Documents 1 and 2 both sense the vibration of the body surface accompanying the pulsation of the heart with a pressure sensor mounted on a seat portion of a seat.
- the pressure sensor it is extremely difficult for the pressure sensor to detect only the vibration of the body surface accompanying the pulsation of the person sitting on the seat due to the vibration of the vehicle body during traveling.
- the pressure sensor even if such a pressure sensor attempts to detect the vibration of the body surface caused by pulsation, the pressure sensor also sensitively detects a pressure change due to the vibration of the vehicle body. It is difficult to make a clear distinction between Therefore, the above-mentioned technology does not function correctly unless it is in an environment that is not easily affected by vibration due to external factors, and has a problem in practicality.
- the airbag of an automobile does not need to be deployed when the load on the seat is something other than a person.
- the vehicle In the event of a collision, for example, if the vehicle is deployed in spite of the fact that nothing is on the passenger seat, unnecessary repair costs will be incurred.
- a weight sensor that measures the amount of displacement of a spring that supports urethane foam as a cushioning material and detects weight based on the magnitude of the amount of displacement is attached, sets a predetermined threshold value for weight, and sets the load on the seat.
- the present invention has been made in view of the above points, and simply and quickly analyzes a living body displacement signal collected by a displacement signal collecting sensor from a load body of a load supporting means to quickly evaluate a state of a living body.
- the task is to provide technologies that can be used.
- Another object of the present invention is to provide a technique suitable for easily and accurately determining the state of a load supported on a vehicle seat by reducing the influence of a noise signal due to external vibrations when the vehicle is running. It is an issue.
- the frequency band of a circulatory biological signal such as a pulse wave is concentrated in a frequency band of 10 Hz or less. 0.25-0.33Hz for breathing, 0.83-1.17Hz for heart rate, 0.5-10Hz for pulse wave is there.
- information such as blood vessel stiffness and blood viscosity has been obtained by analysis based on the waveform of the pulse wave, and noise in the frequency band of 10 Hz or more has been dealt with by providing a low-pass filter. ing.
- sampling sites for pulse wave analysis for which it is difficult to suppress the effects of noise in the frequency band below 10 Hz, must be limited.
- Biological signals themselves such as pulse waves and breathing, muscle vibrations due to pulse waves, breathing, body movements, and tremors, or vibrations generated by appropriately superimposing these factors (in the present invention, Both of these are referred to as “living body displacement signals” in that they can be regarded as large and fluctuating vibrations (fluctuation vibrations) peculiar to living organisms. Is distinguished from Therefore, the present inventor has found that when capturing such a biological displacement signal in an environment where vibrations occur such as an automobile, the displacement (amplitude) of the signal data obtained by the displacement signal collection sensor for each arbitrary section is obtained. We focused on using the rate of change (original waveform displacement slope).
- the original waveform of the signal data is greatly displaced due to sudden vibration caused by, for example, unevenness of the road surface
- a plurality of original waveform displacement gradients calculated for each arbitrary section are used and processed for each predetermined time range. Then, the slope of the displacement (amplitude) (average displacement slope) is offset by adding or subtracting the original waveform displacement slope due to the noise signal.
- the original waveform of the displacement (amplitude) of the biological displacement signal for example, even if the amplitude is large, the original waveform displacement gradient of each section in a predetermined time may be small, and conversely, even if the amplitude of the original waveform is small, the original time may be small.
- the original waveform displacement slope of each section in the above is large, but this is because pressure fluctuations due to factors other than floor vibration, that is, pressure fluctuations due to biological displacement signals due to pulse waves and respiration are superimposed. It is. Therefore, the time-series variation of the original waveform displacement gradient is captured, the average displacement gradient from which a large noise signal is removed is obtained, and the slide displacement is calculated under predetermined conditions using the average displacement gradient. It was found that fluctuations (fluctuations) peculiar to low-frequency biological displacement signals, which are difficult to catch in the original waveform, were emphasized, and that the fluctuation tendency of the biological displacement signals could be manifested.
- the living body of the load supported by the load support Displacement signal collecting sensor force capable of collecting a displacement signal
- a load body state determination device that analyzes obtained signal data and determines a state of a load body
- An average displacement gradient calculating means for dividing an original waveform into predetermined time ranges from the signal data obtained from the displacement signal collecting sensor and calculating a rate of change of the signal data in the predetermined time range as an average displacement gradient;
- the change rate of the average displacement inclination for each predetermined sampling time is calculated as the emphasis displacement slope by performing a predetermined number of slide calculations at a predetermined slide lap rate, and obtaining the emphasis displacement slope.
- Emphasizing displacement inclination calculating means for obtaining the time series data of: and state determining means for judging the state of the load from the time series data of the emphasizing displacement inclination obtained by the emphasizing displacement inclination calculating means.
- the load state determination device according to the first aspect, wherein the displacement signal collecting sensor is attached to a load supporting means.
- the average displacement inclination calculating means divides the original waveform into predetermined time ranges from the signal data obtained from the displacement signal collecting sensor, and further includes a plurality of times within the predetermined time range.
- An original waveform displacement slope calculating means for dividing into sections and obtaining a rate of change for each section as an original waveform displacement slope;
- An original waveform displacement slope summing means for summing the respective original waveform displacement slopes obtained by the original waveform displacement slope calculating means
- the original waveform displacement slope calculating means includes an upper-limit envelope, an lower-limit envelope, or a curve substantially parallel to any one of the envelopes of the amplitude of the original waveform; 4.
- the load body state determination device according to claim 3, wherein the interval between the intersections is defined as one section, and the rate of change for each section is determined as the original waveform displacement gradient.
- the sampling time interval used for the slide calculation by the enhanced displacement inclination calculating means is 180 seconds, and the slide lap ratio is 90. / o
- a load body state determination device according to claim 1 is provided.
- the state determination unit includes: a type determination unit that determines a type of the load body; and a mental and physical state determination unit that determines a physical and mental state when the load body is a person.
- the load body state determination device according to claim 1, further comprising at least one of the means.
- the mental and physical state determination means determines that the amplitude of the time series data of the emphasis displacement gradient is relatively larger than the amplitude of the front range or the amplitude of the rear range.
- a load state determination device determines a sleep transition period between an awake state and a sleep state.
- the type determination means determines that the time series data of the emphasis displacement inclination falls within a predetermined range and moves, and exceeds the predetermined range. 7.
- the load body state determination device further comprising means for determining a person when the vehicle is moving with a change in inclination.
- the type determination means when the time-series data of the emphasis displacement slope changes with a slope change exceeding a predetermined range, stores the time series data in advance in the storage unit.
- the load body state determination device further comprising a comparison unit that reads and compares a reference pattern of the time-series data of the emphasized displacement inclination and specifies an individual.
- the load body supporting means is a vehicle seat
- the displacement signal collecting sensor is provided at least at one of a seat cushion, a seed back and a headrest, and the load body is provided.
- the load supporting means is a vehicle seat
- the displacement signal collecting sensor is attached to at least one force point of a seat cushion of the seat, and the displacement signal collecting sensor is provided through a buttock muscle of the load.
- the load body state determination device has a structure for detecting a pressure change due to a biological displacement signal.
- the load supporting means is a vehicle seat
- the displacement signal collecting sensor detects a displacement of a member displaced by a biological displacement signal of the load.
- the load body state determination device has a structure that performs the following.
- the displacement signal collection sensor that detects a displacement amount of a member that is displaced by a biological displacement signal of the load body also functions as a load detection unit that detects a load of the load body.
- a load body state determination device according to claim 12 wherein The invention according to claim 14 provides the load body state determination device according to claim 1, further comprising a load detection unit that detects a load of the load body, separately from the displacement signal collection sensor. .
- a load detecting means for detecting the load of the load body is provided separately from the displacement signal collecting sensor, and the comparing means detects the load of the load body obtained from the load detecting means.
- the load is compared with a reference load stored in a storage unit in advance, and the load is added to a comparison element to determine at least one element of physical size, adult and child, and individual identification.
- the invention according to claim 16 is characterized in that the load detecting means is a displacement detecting mechanism that detects a displacement amount of a member that is displaced by the load of the load, of the load support means.
- the present invention provides a load state determination device.
- the biological displacement signal of the load provided at at least one of the load cushion supporting portion, which is a seat cushion, a seat back, or a headrest, and supported by the load support is provided.
- a displacement signal collecting sensor capable of collecting the displacement of the load body supporting portion caused by the displacement sensor;
- the displacement signal collecting sensor force a load body state determination device that analyzes the obtained signal data and determines the state of the load body;
- a vehicle seat comprising:
- the load body state determination device divides an original waveform into predetermined time ranges from the signal data obtained from the displacement signal collection sensor, and obtains a rate of change of the signal data in the predetermined time range as an average displacement gradient.
- Inclination calculating means
- a change rate of the average displacement inclination for each predetermined sampling time is calculated by sliding a predetermined number of times at a predetermined slide lap rate to obtain an enhanced displacement inclination.
- a state in which the state of the load is determined from the time series data of the emphasis displacement gradient obtained by the emphasis displacement slope computation means.
- the present invention provides a vehicle seat comprising:
- the load supporting portion includes a vibration isolation mechanism having a small panel constant in an equilibrium state, and a cushion mechanism provided to have a panel characteristic close to a panel characteristic of a human muscle.
- the displacement signal collecting sensor is disposed on a seat cushion, and a base cushion material included in the vibration isolation mechanism and a surface layer stretched on a cushion frame and included in the cushion mechanism.
- the vehicle seat is provided between the cushion member and a living body displacement signal via a hip muscle.
- the average displacement inclination calculating means of the load body state determination device classifies the original waveform into a predetermined time range from the signal data obtained from the displacement signal collecting sensor, and An original waveform displacement slope calculating means for further dividing the range into a plurality of sections and obtaining a change rate for each section as an original waveform displacement slope;
- An original waveform displacement slope summing means for summing the respective original waveform displacement slopes obtained by the original waveform displacement slope calculating means
- a total value obtained by the original waveform displacement gradient summing means is set as an average displacement gradient.
- an original waveform displacement inclination calculating means of the load body state determination device an upper limit envelope, a lower limit envelope, or a curve substantially parallel to any one of the envelopes of the amplitude of the original waveform.
- the emphasis displacement inclination performance included in the load body state determination device is provided.
- a sampling time interval used for a slide calculation by the calculation means is 180 seconds, and a slide lap ratio is 90%.
- the state determination means of the load body state determination device includes a type determination means for determining a type of the load body, and a mental and physical state for determining a mental and physical state when the load body is a person. 18.
- the mental and physical condition determining means determines that the amplitude of the time series data of the emphasis displacement gradient is relatively larger than the amplitude of the front range or the amplitude of the rear range.
- 24. The vehicle seat according to claim 23, wherein the vehicle is determined to be in a sleep transition period between an awake state and a sleep state.
- the type determination means determines that the time series data of the emphasis displacement gradient falls within a predetermined range, and determines that the time-series data exceeds the predetermined range.
- the vehicle seat according to claim 23 further comprising means for determining a person when the vehicle is moving with a change in inclination.
- the vehicle seat according to the seventeenth aspect further comprising a load detecting means for detecting a load of the load body.
- the load is compared with a load, and the load is added to a comparison factor to determine at least one of a physical size, an adult and a child, and an individual. A vehicle seat as described.
- a process of analyzing signal data obtained from a displacement signal collecting sensor capable of collecting a biological displacement signal of a load supported by the load supporting means and determining a state of the load is performed by a computer.
- the average displacement inclination calculating step divides an original waveform into predetermined time ranges from signal data obtained from the displacement signal collecting sensor, and further includes a plurality of times within the predetermined time range.
- the step of calculating the displacement slope of the original waveform includes an envelope on the upper limit side, an envelope on the lower limit side, or a curve substantially parallel to any one of the envelopes of the amplitude of the original waveform, and the original waveform.
- the interval between the intersections is defined as one section, and a change rate of each section is obtained as the original waveform displacement gradient.
- the computer program according to claim 28 wherein a sampling time interval used for slide calculation in the enhanced displacement inclination calculation step is 180 seconds and a slide lap ratio is 90%. provide.
- the state determining step is any one of a type determining step of determining a type of the load body and a mental and physical state determining step of determining a mental and physical state when the load body is a person. 29.
- the mental and physical state determining step includes calculating the emphasis displacement inclination.
- the range in which the amplitude of the time-series data is relatively large compared to the amplitude of the preceding range or the amplitude of the following range is determined to be a sleep transition period between the awake state and the sleep state.
- a computer program according to claim 32 is provided.
- the object in the type determination step, when the time series data of the emphasized displacement inclination falls within a predetermined range and changes, the object is determined to be an object, and the slope change exceeding a predetermined range is determined.
- the computer program according to claim 32 further comprising means for determining that a person is in the case of transition.
- the rate of change of the displacement signal data of the load supported by the load supporting means in each arbitrary section of the original waveform is determined as the original waveform displacement gradient, and the rate of change is calculated from the plurality of original waveform displacement gradients.
- the time series data of the average displacement slope for each predetermined time range is obtained, and the time series data of the average displacement slope is calculated by sliding at predetermined sampling times to obtain the emphasis displacement slope.
- the state of the load is determined from the series data.
- the state of the living body for example, awake state, sleep state, is determined from the fluctuation tendency. It is possible to determine the state or the power of the transition state between awakening and sleep (transition transition period).
- the load detecting means when the load is a "person", a living body displacement signal (dynamic load fluctuation) due to body motion is detected, whereas the load is "object”. In the case of " Since such load fluctuation does not occur, the type of the load body can be determined more accurately. Further, when it is determined that the load physical strength S is “person”, it is possible to determine the size of the physique or the distinction between an adult and a child by considering the load detected by the load detecting means.
- FIG. 1 is a perspective view showing a schematic configuration of a sheet to which a load state determination device according to one embodiment of the present invention is attached.
- FIG. 2 is a side view showing a schematic configuration of the sheet.
- FIG. 3 is a plan view showing a schematic configuration of the sheet.
- FIG. 4 is a schematic diagram showing a preferred arrangement position of a displacement signal collecting sensor.
- FIG. 5 is a block diagram showing a schematic configuration of a load body state determination device according to the embodiment.
- FIG. 6 (a)-(c) is a block diagram showing a variation of the state determination means.
- FIG. 7 is a diagram for explaining a calculation method of an average displacement inclination.
- FIG. 8 is a diagram for explaining a slide calculation method.
- FIGS. 9 (a) to 9 (e) are diagrams showing emphasis displacement gradients when sampling time is varied in order to calculate an optimal gradient in a 30-minute sleep experiment.
- FIG. 9 (f) is a diagram showing the peak coefficient.
- FIGS. 10 (a) and 10 (d) are diagrams showing the emphasis displacement slope when the slide lap ratio is varied in time in order to calculate the optimum slope in a 30-minute sleep experiment.
- FIG. 10 (e) shows the crest coefficient.
- FIG. 11 (a) is a diagram showing the frequency analysis results of FIG. 9 (a)-(e), and FIG. 11 (b) is the frequency analysis results of FIG. 10 (a)-(d).
- FIG. 11 (a) is a diagram showing the frequency analysis results of FIG. 9 (a)-(e)
- FIG. 11 (b) is the frequency analysis results of FIG. 10 (a)-(d).
- FIG. 12 is a diagram showing a frequency analysis result of an emphasis displacement slope obtained in a 180-minute sleep experiment, and (a) shows a change in sampling time with a slide lap ratio of 90%. In case (b), the sampling time is set to 180 seconds and the slide lap ratio is changed.
- FIG. 13 is a diagram showing an original waveform of data obtained from a pressure sensor in each of a static state and a dynamic state in Test Example 1.
- FIG. 14 is a diagram showing time-series data of an average displacement inclination calculated by an average displacement inclination calculating means based on the original waveform of FIG.
- FIG. 15 is a diagram showing a time-series change of the emphasis displacement inclination calculated by processing by the emphasis displacement inclination calculating means.
- FIG. 16 is a diagram showing a frequency analysis result of the emphasis displacement inclination of FIG. Garden 17]
- FIG. 17 is a diagram showing an original waveform of a finger plethysmogram measured in an actual vehicle test of Test Example 2.
- FIG. 18 is a diagram showing time-series data of the average displacement gradient in the actual vehicle test of Test Example 2.
- FIG. 19 is a diagram showing time-series data of the emphasis displacement inclination in the actual vehicle test of Test Example 2.
- FIG. 20 is a diagram showing an original waveform of a finger plethysmogram measured in the static sitting test of Test Example 2.
- FIG. 21 is a diagram showing time-series data of the average displacement inclination in the static seating test of Test Example 2.
- FIG. 22 is a diagram showing time-series data of the emphasis displacement gradient in the static sitting test of Test Example 2.
- FIG. 23 is a view showing an original waveform obtained from a pressure sensor in a test for judging a person and an object in Test Example 5.
- FIG. 24 is a diagram showing a time-series change of the emphasis displacement gradient obtained by calculating the original waveform of FIG. 23 by a calculation unit.
- FIG. 25 is a diagram showing a configuration example of a seat cushion of a seat provided with a displacement detection mechanism.
- FIG. 26 is a view on arrow A in FIG. 25.
- FIG. 27 is a diagram showing details of a bracket for fixing a Hall IC.
- FIG. 28 is a diagram showing an example of a displacement detection mechanism in which an excitation coil and a pickup coil are provided on a torsion bar.
- Figure 29 shows a displacement detector equipped with an excitation coil and a pickup coil on a torsion bar It is a figure which shows the other example of a structure.
- FIG. 30 is a graph showing a correlation between a load and an output voltage of a pickup coil.
- FIG. 31 (a) is a graph showing the relationship between the magnitude of vibration and output voltage
- FIGS. 31 (b) and (c) are diagrams for explaining a measuring method.
- FIG. 32 is a block diagram showing a schematic configuration of a load state determining device using a load signal obtained from load detecting means.
- FIG. 33 (a) is a diagram showing time-series data of an emphasis displacement gradient of a finger plethysmogram in Test Example 3, and (b) is an emphasis on a biological displacement signal via a gluteal muscle.
- FIG. 9 is a diagram showing time-series data of displacement inclination.
- FIG. 34 is data showing a comparison between fingertip plethysmogram measured in Test Example 4 and electroencephalogram.
- FIGS. 1 to 3 are schematic configuration diagrams of a state in which a load state determination device 1 according to one embodiment of the present invention is attached to a vehicle seat 100 such as an automobile, which is load support means.
- the load body condition determination device 1 includes a calculation unit 20 that receives and analyzes signal data collected by the displacement signal collection sensor 10.
- a pressure sensor can be used as the displacement signal collection sensor 10. However, since it is used by attaching it to at least one of a seat cushion, a seat back or a headrest, it is necessary to prevent a person from feeling a foreign substance when sitting down.
- a film-shaped piezoelectric element should be used as the pressure sensor. Is preferred.
- the film-like piezoelectric element for example, Tokyo Sensor Co., Ltd., product name: PIEZO FILM LDT series, model number: LDT4-028 K / L can be used.
- the displacement signal collecting sensor 10 can be mounted on at least one of the seat cushion, the seat back, and the headrest as described above.
- the displacement signal collecting sensor 10 may be configured such that only one is disposed near the lower part of the ischial tuberosity. There is a possibility that the sensor will fall out of the detection range of the sensor if it is shifted to the side (sacral posture) .In addition to the sensor placed under the ischial tuberosity, the position shifted forward or backward Further, it is also possible to arrange one or more sensors.
- the living body displacement signal When a living body displacement signal is collected from a seat 100 of an automobile or the like, if the above-described pressure sensor is used, the living body displacement signal can be transmitted to a muscle simply by sitting down without wearing a special measuring device. This is preferable because it can be collected as vibrations of the body surface.
- the biological data such as pulse wave and respiration are included as signal data with less noise. It is preferable to collect the signal itself as a biological displacement signal.
- a known optical fingertip pulse wave meter for collecting fingertip plethysmograms or a measuring instrument for collecting earlobe pulse waves can be used as the displacement signal collecting sensor.
- the structure of the seat 100 is not limited, but each cushion structure of the seat cushion 120 and the seat back 140 has slight muscles generated by human breathing, heartbeat (pulse wave), body movement, and the like. It is preferable that the sensor be capable of transmitting the pressure fluctuation to the displacement signal collecting sensor: L0 and have high performance of a vibration isolation function of the floor vibration.
- FIGS. 1 to 3 show an example of a preferred sheet 100 having such performance.
- the seat cushion 120 of the seat 100 includes a torsion bar 122 at a rear portion of the cushion frame 121, and supports a rear support frame 124 at an arm 123 urged backward by the torsion bar 122,
- a base cushion member 126 is provided between the front support frame 125 and the rear support frame 124.
- a surface cushion member 127 that is stretched with low tension to the cushion frame 121 is provided on the upper portion of the base cushion member 126.
- the base cushion material 126 and the surface cushion material 127 can each be formed of a single cushion material, or can be formed by laminating a plurality of cushion materials as necessary.
- the displacement signal collecting sensor 10 is provided between the base cushion material 126 and the surface cushion material 127. Provided. Since the base cushion material 126 has a structure in which tension is applied by the elastic force of the torsion bar 122, the base cushion material 126 eliminates floor vibration. As a result, the transmission of vibration to the surface cushion member 127 is reduced. On the other hand, since the surface cushioning material 127 is stretched with a low tension on the cushion frame 121, the pressure on the human muscles (particularly, the gluteal muscles) is small when the person sits down, and the blood vessels dilate, contract, breathe or move. It does not interfere with muscle movement caused by such factors. As a result, mixing of external vibration noise into the signal data collected by the displacement signal collection sensor 10 is reduced, and it becomes possible to more accurately collect a pressure fluctuation signal caused by the biological displacement signal.
- the surface cushion material 127 can also form a force such as a two-dimensional net material or a thin urethane material. However, in order to further reduce the pressure on the gluteal muscles and the like, the surface cushion material 127 must be formed of the cushion frame 121. It is preferable that the spring characteristic force when stretched to be close to the spring characteristics of the buttock muscles and the like is as close as possible. As the surface cushioning material 127 having such characteristics, it is preferable that the present applicant use, for example, a three-dimensional knitted fabric having a small reaction force disclosed in JP-A-2002-336076.
- the three-dimensional knitted fabric is formed using, for example, a double Russell knitting machine or the like, and is knitted by reciprocating a connecting yarn between a pair of ground knitted fabrics located at a predetermined interval.
- a two-dimensional net material, a three-dimensional knit, or the like can be used as in the case of the surface cushion material 127.
- the displacement signal collecting sensor has the elasticity of the spring material such as the torsion bar 122 and the damping property of the base cushion material 126 made of a three-dimensional knit or the like. Therefore, as a static panel characteristic, in the equilibrium state where a person is seated, there is almost no increase or decrease of the load within a predetermined displacement range, that is, a vibration isolation mechanism having a so-called zero spring constant range and a cushion frame 121. It is preferably disposed between a cushion mechanism having a spring characteristic that does not compress muscles similar to the panel characteristics, such as the buttock muscles, such as a surface layer material 127 made of a three-dimensional knitted fabric or the like.
- the vibration isolation mechanism having a range of the panel constant of zero is not limited to the one made from the combination of the torsion bar 122 and the base cushion material 126 as in the present embodiment, but is proposed by the present applicant.
- a repulsive force or attractive force of a permanent magnet is combined with an elastic member such as a metal panel. It is also possible to use a seat suspension or the like using an anti-vibration mechanism that has a region where the panel constant is substantially zero at the load mass equilibrium point.
- the base cushion material 126 is stretched between the rear support frame 124 and the front support frame 125, and the surface cushion material 127 covers the base cushion material 126 so as to cover the base cushion material 126. Since the structure is stretched to 121, it is preferable to provide a structure that supplements the restoring force at the time of unloading. In FIG. 1 and FIG.
- a hard auxiliary plate 128 made of a metal plate, a synthetic resin, or the like is arranged below the base sash 126 near the front end from a substantially central portion thereof, and the side frame 121a
- a member in which a cushioning material 131 such as a urethane material and a three-dimensional knit is laminated on the upper surface of the auxiliary plate material 128 is provided.
- An elastic band member 132 made of rubber or the like is disposed in the width direction between the cushioning member 131 and the base cushion member 126, and is supported by a coil spring 133 having one end supported by the side frame 121a.
- one end of the coil spring 134 is hung on a portion of the base cushion material 126 located near both sides of the rear support frame 124, and the other end of the coil spring 134 is positioned in such a direction as to extend obliquely outward and rearward. It is engaged with the auxiliary frame member 135.
- the coil spring 134 disposed rearward generates a tension in the front-rear direction on the base cushion member 126, and a tension crossing the tension direction is generated by the elastic band member 132 and the like, thereby assisting the restoring force.
- the auxiliary plate member 128 is disposed closer to the front of the base cushion member 126, the holding property and the sense of stability in the vicinity of the buttocks are improved, and the posture supporting function is also improved.
- the seat back 140 includes a base cushion material 141 and a surface cushion material (not shown) stretched over the back frame 142 so as to cover the base cushion material 141.
- the base cushion material 141 and the surface cushion material are formed using a three-dimensional knitted fabric or the like, similarly to the material used for the seat cushion 120 described above.
- the upper end of the base cushion material 141 is supported by the coil spring 144 at the upper end of the back frame 142, and the lower end force is supported by the coil spring 145 on the S cushion frame 121. The resilience of the system is ensured.
- the arithmetic unit 20 communicates with the displacement signal collecting sensor 10 described above via a wireless or signal cable. As shown in FIG. 5, they are connected, and as a program, an average displacement inclination calculating means (average displacement inclination calculating step) 21, an emphasis displacement inclination calculating means (emphasized displacement inclination calculating step) 22, and a state judging means (State determination step) 23 is provided.
- the average displacement gradient calculating means (average displacement gradient calculating step) 21 divides the original waveform into predetermined predetermined time ranges (for example, every 5 seconds), and displaces the signal data in the predetermined time range. This is a means for obtaining the average change rate of (amplitude) and obtaining it as the average displacement gradient. By calculating the average displacement gradient, even if a noise signal is included in the original waveform, its influence is reduced.
- the average displacement slope calculating means 21 is not limited in its calculation method as long as it has a powerful function, but it can be easily calculated and can easily cancel the influence of a noise signal. (Original Waveform Displacement Slope Calculation Step) It is preferable to provide a configuration including the original waveform displacement inclination totaling means 21b.
- the original waveform displacement slope calculating means (original waveform displacement slope calculating step) 21a calculates the rate of change of the displacement (amplitude) of each section divided into a plurality of sections within the above-mentioned predetermined time range. Means.
- the number of sections is not limited. For example, one section may be provided between the intersections between the envelope on the upper limit side of the original waveform and the original waveform.
- FIG. 7 illustrates an example thereof, in which each of the intersections P1 and P2, and P2 and P3 between adjacent intersections between the upper-limit envelope of the amplitude and the original waveform is one section between ⁇ 7_ ⁇ 8. .
- the original waveform displacement slope is calculated by calculating the difference between the values of each section between P1 and ⁇ 2, between ⁇ 2 and ⁇ 3, and between ⁇ 7 and ⁇ 8, and the time of each section is tl seconds, t2 seconds Divide and ask.
- the setting of each section is performed by, for example, applying a predetermined threshold value to the magnitude of the displacement (amplitude) of the waveform by the smoothing differentiation method using Savitzky and Golay, and preferably by 70% of the variation width of the waveform. It is also possible to calculate the peak value on the upper limit side and calculate the rate of change between the peak values as the original waveform displacement slope. However, each peak value calculated in this manner actually substantially coincides with the intersection (P1-P8) between the above-described upper limit envelope of the amplitude and the original waveform.
- the interval between adjacent intersections of the lower-limit envelope and the original waveform may be determined as one section, or the upper-limit envelope or the lower-limit envelope may be calculated as one section.
- the interval between adjacent intersections between the substantially parallel curve and the original waveform can be determined as one section.
- the baseline becomes a curve instead of a straight line. If a baseline sway has occurred, a force that cancels the baseline sway and converts it to a straight line is set. A new straight line is set according to the lower limit of the amplitude, and the above-described original waveform displacement gradient is obtained.
- Original waveform displacement gradient totaling means (original waveform displacement gradient totaling step) 21b calculates each of the original waveform displacement gradients obtained by the above-mentioned original waveform displacement gradient calculating means 21a in the predetermined time range. Each time, the sum is set as an average displacement gradient. Therefore, in the case of FIG.
- point P4 is a force S which is a noise signal
- the slope between P3 and P4 is a large positive value
- the slope between P4 and P5 is large
- the emphasis displacement inclination calculating means (emphasis displacement inclination calculation step) 22 uses the value of each average displacement inclination for each predetermined time range obtained from the average displacement inclination calculation means 21 to calculate the average displacement inclination.
- the rate of change of the average displacement slope for each predetermined sampling time of the value is calculated as the emphasized displacement slope by performing slide calculations a predetermined number of times at a predetermined slide wrap rate (see FIG. 8). The slide calculation is performed as follows.
- the emphasis displacement gradient during T seconds (s) is obtained at a slide lap rate of 90%
- the value of each average displacement gradient for each predetermined time range for example, every 5 seconds
- the rate of change between 0 (s) and T (s) is determined by the least squares method or the like.
- the value of the rate of change of the value of the average displacement slope (emphasized displacement slope) obtained first is plotted at the time T (s), and the value of the emphasized displacement slope obtained by the next slide calculation is calculated.
- Values at the time of T + T / 10 (s), and the value of the emphasis displacement slope obtained by the nth slide calculation is plotted at the time of T + n XT / lO (s), and the Obtain time series data.
- the optimal sampling time (T seconds) for performing the slide calculation for obtaining the emphasis displacement inclination is 180 seconds
- the optimal slide lap ratio is 90%. This was obtained from the results of a 30-minute sleep experiment performed on several subjects in the same environment, and finger plethysmograms were collected and analyzed.
- FIG. 9 and FIG. 12 show an example thereof.
- Figure 9 (a)-(e) shows that the sampling time intervals for slope calculation are 60 seconds, 120 seconds, 180 seconds, 240 seconds, and 300 seconds, respectively, and the slide lap rate is 90%.
- This is time-series data of the emphasis displacement slope that is unified
- Fig. 11 (a) shows the frequency analysis result.
- a and b are characteristic signal amplitudes that appear during the transition to sleep onset
- a is the characteristic sleep onset signal amplitude that appeared before the subject fell asleep
- b is It shows the amplitude of the signal in the transition state in which a transition to sleep occurs after the onset of sleep onset appears.
- c indicates the amplitude of a sleep signal when the user enters sleep.
- the subject's state change time (eg, time when he began to dwell, time when he fell asleep, etc.) is measured from the data of the third party's inspection and video shooting. Then, it was determined by collating with the time series data of the emphasis displacement slope.
- the reason for setting the median to 180 seconds is that the frequency of firing of muscle activity commands due to fatigue is mainly due to peripheral reflex mechanisms in the muscle. In other words, the lowering of the excitability of the upper center due to fatigue and the involvement of the peripheral inhibitory reflex mechanism decrease the command of muscle activity. Sexual excitement levels are predicted to be associated with recovery.
- the slide wrap ratio was calculated up to 70% force and 95% in the case of a sampling time interval of 180 seconds. It is omitted because it is less than 70% and the time series signal is sparse.
- the results are shown in FIGS. 10 (a)-(d), and FIG. 11 (b) shows the results of the frequency analysis. From this figure, when the slide lap ratio is 90% and 95%, the noise was small.Referring to the graph of Fig. 10 (e), which shows the crest coefficient, the sensitivity is highest when the slide lap ratio is 90%. Was. For this reason, a time interval of 180 seconds and a slide wrap ratio of 90%, at which the sign signals a, b, and c can be clearly picked up, are the most favorable conditions for extracting information that is characteristic of living organisms.
- the emphasis displacement gradient calculating means 22 calculates the rate of change of each average displacement gradient for 180 seconds by the least square method, and then minimizes the gradient for 180 seconds starting 18 seconds later. Optimally, it is determined by the square method. In other words, if the time interval for performing the tilt calculation is set to 180 seconds and the slide lap ratio is set to 90%, the characteristic of fluctuations (fluctuations) peculiar to the biological displacement signal can be remarkably extracted.
- the frequency band of the biological signal of the circulatory system is concentrated in a frequency band of 10 Hz or less. It is 0.25-0.33Hz for breathing, 0.83-1.17Hz for heart rate, and 0.5-10Hz for pulse waves.
- information such as blood vessel hardness and blood viscosity is obtained by analyzing the waveform of the pulse wave, and noise in the frequency band of 10 Hz or more is provided by providing a low-pass filter.
- sampling sites for pulse wave analysis where it is difficult to suppress the effects of noise in the frequency band below 10 Hz, have been limited.
- biological displacement signals such as pulse waves, respiration, and body movements that are collected in an environment where automobile vibrations are generated are generally vibrations that are excited by an irregular vibration source.
- the state determination means (state determination step) 23 determines the state of the load body based on the time-series data of the emphasis displacement inclination obtained by the emphasis displacement inclination calculation means 22. Specifically, as shown in FIG. 6, when the load is a person, mental and physical condition determination means (a mental and physical condition determination step) 23a for determining the physical and physical condition thereof, and a type for determining the type of the load Judgment means (type judgment step) 23b.
- the mental and physical state determining means 23a determines a range in which the amplitude of the time-series data of the emphasis displacement gradient is relatively large as compared with the amplitude of the front range or the amplitude of the rear range, between the awake state and the sleep state. It is determined that the sleep transition period between the two states is reached. From the experimental results shown in Figs. 9 and 10, the amplitude in the predetermined time range before going to sleep is relatively smaller than the amplitude in the previous range (wake state) or the amplitude in the rear range (sleep state). The characteristic signal which becomes large appears.
- the characteristic signal with the increased amplitude is regarded as a sleep onset signal, and when such a signal occurs, it is determined that the transition to sleep onset occurs. It is preferable that the magnitude of the amplitude when judging the signal as a sign of falling asleep is at the time when the amplitude is at least twice as large as that before or after the range. This is because when the sleep experiment shown in Fig. 9 and Fig. 10 was performed on 32 adult males and females, almost all the amplitudes were more than doubled.
- the maximum Lyapunov exponent which is a chaos index, is also calculated, and the maximum Lyapunov exponent is calculated by a slide calculation using the same method as the above-mentioned emphasized displacement inclination calculating means.
- the time series data of the slope of the maximum Lyapunov exponent is also shown.
- the maximum Lyapunov exponent is considered to mainly indicate changes in the mental state of a person.From the results in Fig. 9 ( There is a relationship that the phase is reversed by 180 degrees between the time series change and the time series change of the slope of the maximum Lyapunov exponent. It is preferable that the time series data of the exponent slope is also calculated and displayed together with the time series data of the emphasis displacement slope, and whether or not such an antiphase state exists is also used as a determination index.
- the type determination means 23b determines that the time series data of the emphasis displacement inclination falls within a predetermined range, and determines that the time series data is an object, and transitions with an inclination change exceeding the predetermined range. If it does, it is judged as a person. As described above, calculating the average displacement inclination and the emphasis displacement inclination As a result, external vibration noise is reduced, and the time-series data of the emphasized displacement gradient is data that captures fluctuations due to the biological displacement signal. For this reason, the time-series data of the emphasis displacement gradient when the load is an “object” and does not generate a biological displacement signal is data that does not cause fluctuation with a very small temporal change.
- a predetermined threshold value is provided, and if the temporal change of the emphasis displacement gradient is within a predetermined range, it is determined to be “object”, and if there is a temporal change exceeding the predetermined range, the biological displacement signal is determined. Therefore, it is determined to be “person”.
- the mental and physical state determining means 23a and the type determining means 23b may be configured to include only one of them depending on the application.
- both cases where a person sits on a seat and where an object is placed occur relatively frequently, and as shown in Fig. 6 (c), It is preferable to include both the state determining means 23a and the type determining means 23b.
- the output unit 24 outputs the result of the state determination unit 23 and transmits the result to a predetermined control unit. For example, when the sleep-predictive signal is detected by the psychosomatic state determination means 23a, the output result is transmitted to the control unit of the appropriate awakening means that stimulates at least one of the five senses to awaken, and operates them. Let it. For example, it is possible to wake up by operating an alarm device or slightly tilting the seat back.
- the type is determined to be “object” by the type determination unit 23b, for example, a signal for canceling the operation is transmitted to the airbag control unit.
- the above-mentioned average displacement inclination calculating means (average displacement inclination calculating step) 21, emphasized displacement inclination calculating means (emphasized displacement inclination calculating step) 22, and state determining means (state determining step) 23
- the computer program of the present invention including the determining means (mental and physical condition determining step) 23a and the type determining means (type determining step) 23b can be provided by being stored in a recording medium.
- a “recording medium” is a medium that can carry a program that cannot take up space by itself, such as a flexible disk, hard disk, CD-ROM, M, (magneto-optical disk), DVD— ROM etc.
- the present invention can be configured by preinstalling or downloading the above-described program on a general-purpose terminal device. It is also possible to do that.
- the seat 100 provided with a pressure sensor as the displacement signal collecting sensor 10 between the base cushion material 126 and the surface cushion material 127 of the seat cushion 120 shown in FIGS.
- a seating experiment was performed for the case where it was installed on the ground (static state) and the case where it was installed on the shaker (dynamic state).
- As the base cushion material 126 a three-dimensional knitted fabric is used, and as the surface cushion material 127, a three-dimensional knitted fabric stretched on a cushion frame with an elongation of less than 5% is used. Other configurations are as described above.
- the subjects were healthy Japanese men in their thirties, and in each of the static and dynamic states, the same subject sat for 30 minutes and collected pressure sensor data.
- the dynamic state at 1.3 Hz, including the over-projection that generates an impact vibration of 2.0 G at the peak-to-peak value of the amplitude, a random sample collected using a wagon vehicle in Michigan, USA Excited by vibration.
- FIG. 13 shows the results.
- FIG. 13 shows the original waveform of the data obtained from the pressure sensor in each of the static state and the dynamic state.
- FIG. 14 shows time-series data of the average displacement inclination calculated by the average displacement inclination calculating means 21 based on the original waveform obtained from the pressure sensor.
- FIG. 15 shows a time-series change of the emphasis displacement inclination calculated by processing by the emphasis displacement inclination calculating means 22.
- the dynamic state data includes external vibration noise.
- the influence of the external vibration noise is reduced by the average displacement gradient calculation means 21.
- the present invention reduces the influence of noise signals due to external vibrations and extracts body surface vibrations (biological displacement signals) through muscles due to pulse waves, respiration, body movements, etc. of occupants of automobiles and the like. It turns out that it is suitable for doing.
- Test Example 1 The same seat as in Test Example 1 was mounted on the front passenger seat of the car, and the subject sat down and ran through the city, but the living body displacement signal was not based on the vibration of the buttocks muscles by the pressure sensor. A meter was installed, and the finger plethysmogram of the subject was collected. Then, the relationship between the time-series data of the emphasis displacement gradient of the finger plethysmogram and the mental and physical condition was examined. An observer got on the rear seat and observed the subject's state change. The subjects were healthy Japanese women in their 30s. The results are shown in FIGS.
- FIG. 17 shows an original waveform of the fingertip plethysmogram
- FIG. 18 shows time-series data of the average displacement gradient
- FIG. 19 shows time-series data of the enhanced displacement gradient.
- the body displacement signal is captured.
- the sleep onset signal unique to the sleep onset period, which shows a change of more than twice the amplitude before and after, occurs.
- points 1 indicated by numbers in the figure were determined to be in the awake state
- points 2 to 4 were determined to be in sleep transition
- points 5 to 6 were determined to be in the sleep state.
- the maximum Lyapunov exponent which is a chaos index, is also calculated and shown as time-series data.
- the time-series data of the maximum Lyapunov exponent is calculated in the same manner as the above-mentioned enhanced displacement slope calculating means.
- the time series data of the slope of the maximum Lyapunov exponent calculated by the slide calculation using the method described in (1). As a result, from around 5400 seconds to around 5600 seconds, an anti-phase relationship was observed between the time series data of the enhanced displacement slope and the time series data of the slope of the maximum Lyapunov exponent, confirming the transition to falling asleep. You.
- Test Example 1 The same seat as in Test Example 1 was set in the laboratory, the subject was seated, and fingertip plethysmograms were collected for 30 minutes, and the relationship between the time-series data of the emphasis displacement gradient and the physical and mental state was examined. This In the test, the observer also observed changes in the state of the subject. The subject was a healthy Japanese man in his twenties. The results are shown in FIGS.
- FIG. 20 shows the original waveform of the fingertip plethysmogram
- FIG. 21 shows the time series data of the average displacement slope
- FIG. 22 shows the time series data of the emphasized displacement slope.
- the amplitude of the time-series data of the average displacement slope in Fig. 21 is not stable, and the mental and physical state changes (such as transition to sleep) occurred at any time, but it is difficult to distinguish.
- looking at the time series data of the emphasis displacement slope in Fig. 22, from around 700 seconds to around 1200 seconds the sleep onset signal unique to the sleep onset transition period, which shows a change of more than twice the amplitude before and after, is seen. It can be seen that it has occurred.
- the maximum Lyapunov exponent which is a chaos index, is also calculated and shown as time-series data.
- the time-series data of the maximum Lyapunov exponent is calculated in the same manner as the above-mentioned enhanced displacement slope calculating means.
- the time series data of the slope of the maximum Lyapunov exponent calculated by the slide calculation using the method described in (1) is shown.
- the anti-phase relationship between the time series data of the intense displacement slope and the time series data of the slope of the maximum Lyapunov exponent was clearly seen, indicating that it was the transition to falling asleep. It is confirmed.
- the test subject was seated in the passenger seat of the car in Test Example 2, and traveled down the Sanyo Expressway, between Miyajima and Iwakuni. A biological displacement signal including a pulse wave was collected.
- a biological displacement signal including a pulse wave was collected.
- the relationship between the time series data of the emphasis displacement tilt and the mental and physical state was examined. An observer got on the rear seat and observed the subject's state change.
- the subjects were healthy Japanese men in their twenties, 168 cm tall, and weighing 85 kg.
- FIG. FIG. 33 (a) shows time-series data of the emphasis displacement inclination of the fingertip plethysmogram
- FIG. 33 (b) shows time-series data of the emphasis displacement inclination of the biological displacement signal via the gluteal muscle.
- the peak is around 650 seconds, and the peak is around 600 to 740, and the peak around 850 is 740 to 920.
- a peak around 980 to 1060 seconds a large change in the amplitude appears around 920 to 1060 seconds, which can be determined as a signal to indicate sleep onset, and sleep changes around 1120 seconds. It can be determined that it has been reached.
- this is compared with the time-series data of the slope of the maximum Lyapunov exponent, an anti-phase relationship is clearly seen in the above range, and it is confirmed that the range is the transition period to falling asleep.
- both peak times (Fig. 33 (a)) (Approximately 650 seconds, 850 seconds, and 980 seconds) It is preferable to determine that the sleep onset signal has occurred at a point in time, and issue a warning.
- the psychosomatic state determined from Fig. 33 (a) was in good agreement with the observation result of the observer.
- the peak is around 680 seconds, the peak is around 670—720 seconds, and the peak is around 810 seconds.
- a large amplitude change appears at around 920-980 seconds compared to the amplitude before and after, which can be judged as a sleep onset signal and around 1120 seconds. It can be determined that sleep has been reached.
- a configuration is adopted in which it is determined that a sleep onset signal has occurred at a point slightly after both peak points in the range where the anti-phase relationship can be seen, and a warning is issued.
- the data in Fig. 33 (b) does not completely match the data in Fig. 33 (a), it can be determined that they show almost the same tendency, and the body displacement through the gluteal muscles Even when a signal is collected, the state of mind and body of a person can be determined with an accuracy comparable to that of a finger plethysmogram. In the case of finger plethysmography, an optical finger plethysmograph etc.
- FIG. 34 shows the time-series data of the slope of the emphasis displacement measured in this experiment for about 30 minutes, the time-series data of the slope of the maximum Lyapunov exponent, the measured EEG waveform, the analysis waveform of the EEG, and the frequency analysis of the analysis waveform. Is shown.
- the measurement result in the electroencephalograph is wave ⁇ in section A is continuously expressed, changes in the intermittent expression waves ⁇ is a ⁇ interval, becomes dominant ⁇ waves in section C, 860 — It was measured that the alpha wave completely disappeared around 900 seconds, and a wave appeared in section D. Based on these results, the judgment at the time of sleep was the time when the ⁇ -wave completely disappeared (around 860-900 seconds), which almost coincides with the judgment based on the emphasis displacement gradient of the fingertip plethysmogram. I understand.
- the electroencephalograph since the ⁇ wave appears in the ⁇ section and the B section, it is defined as the arousal period.
- the state where the ⁇ -wave disappears and the ⁇ -wave dominates is called sleep state.
- the appearance of the spikes becomes intermittent, and then the stage before rapidly shifting to falling asleep, that is, the latter half of the ⁇ section can also determine the first half of the C section as a sign of falling asleep, but at that time a warning is given Even if it is issued, it is too late for a car driver to warn. That is, the state in which the waves appear intermittently is already in a blurred state and quickly falls asleep, so that there is no time to prevent a traffic accident before it occurs.
- the electroencephalograph continuously shows the spikes, and it is judged that it is in the awake period.
- the sleep onset signal (around 450 seconds) showing a displacement amplitude clearly different from the time series before and after was detected, and it was found that the sleep onset signal could be detected earlier than the electroencephalograph. Therefore, the method of determining the physical and mental state based on the emphasized displacement gradient of the biological displacement signal is particularly effective as a warning system for the driver.
- FIG. 24 shows a time series change of the emphasis displacement gradient obtained by calculating the original waveform of FIG.
- the time-series change does not show a large change, but falls within a predetermined change range.
- the value (threshold) in a predetermined range for distinguishing between a person and an object cannot be determined unconditionally because it differs depending on the type and performance of the sensor used, but in general, the time-series change in the emphasis displacement gradient is considered.
- the average value of can be considered to be within the range of 1Z2 or less for humans, preferably within the range of 1Z3 or less.
- the present invention is not limited to the above embodiment.
- the state determination means 23 only determines the mental and physical state of a person or the distinction between a person and an object from the time-series change of the emphasis displacement gradient. Regardless of whether the state is dynamic or static, as shown in Fig. 15, each individual has some features. When the frequency analysis as shown in Fig. 16 was performed, the dynamic state and the static state were almost the same, and not only the time series change of the emphasis displacement gradient but also the frequency analysis were considered. By storing the reference pattern of a certain individual in the storage unit of the computer, it is possible to determine whether the time series change of the newly detected enhanced displacement gradient and the frequency analysis result are close to the reference pattern or not.
- comparison step 23c By activating the comparison means (comparison step) 23c as a program set in the means 23, it is possible to specify an individual (see FIG. 31). Thus, for example, a biological signal when a person is seated on the driver's seat is detected, and it is determined whether or not the result obtained by calculating the emphasis displacement gradient and performing the frequency analysis matches the reference pattern. By providing a control circuit that allows the engine to be started only when they match, the system can be used as a vehicle anti-theft system (see Fig. 31).
- the load state determination device 1 of the present invention can also be configured to include a load detection means for detecting the load of the load.
- a load detection means for detecting the load of the load.
- FIG. 25 This is a configuration in which a displacement detection mechanism serving as a load detection unit is additionally provided.
- the seat cushion 30 shown in FIG. 25 is provided with two brackets 31 on a rear frame 30a which is arranged rearward in the lateral direction (width direction), and supports the torsion bar 32 on the brackets 31, 31.
- the two arms 33, 33 are connected to each other, a support frame 34 is disposed on the arms 33, 33, and a base cushion material 36 such as a three-dimensional knitted fabric is stretched between the support frame 34 and the front end frame 35. It was done.
- the arm 33 and the support frame 34 rotate back and forth due to the elastic force of the torsion bar 32, and are displaced. I do. Therefore, the load can be detected by detecting the displacement of the arm 33.
- Figs. 24 to 27 show a Hall IC 40 as a magnetic sensor and a magnet.
- the one that can be combined with 45 is used.
- three Honoré ICs 40 are arranged at substantially equal intervals on the Hall IC fixing bracket 41 at substantially equal intervals, and the Hall IC fixing brackets 41 are fixed to the rear frame 30a. It is fixed to the side of the bracket 31.
- the magnet 45 is fixed to the side surface of the arm 33 and provided so as to face the Hall IC fixing bracket 41.
- the arm 33 pivots forward when the base cushion material 36 sinks down when a person sits down. Therefore, when the amount of rotation changes, the output voltage of each of the three Hall ICs 40 arranged in a substantially arc shape on which the magnetic field of the magnet 45 acts changes in accordance with the change in the magnetic flux density.
- the correlation between the fluctuation of the output voltage of each Hall IC 40 and the rotation angle of the arm 45 and the correlation between the rotation angle of the arm 45 and the load are defined, and are defined in the same manner as in the above embodiment.
- a bracket 41 for fixing a Hall IC is provided on the side surface of the bracket 31, and a magnet 45 is provided on the side surface of the arm 33.
- the facing portion of the Hall IC bracket 41 with respect to the magnet 45 shifts as the arm 33 rotates.
- the Hall IC 40 has high directivity, and thus it may be difficult to detect a magnetic field. Therefore, when the magnet 45 is fixed to the side surface of the arm 33, a plurality of holes are provided on the hole IC bracket 41 fixed to the side surface of the bracket 31 according to the rotation range of the arm 33 (magnet 45). Ho It is preferable that the IC 40 be provided in a substantially arc shape.
- a gear mechanism such as a worm wheel that rotates with the displacement of the arm 33 is provided, and a magnet 45 is attached to an arbitrary portion of the gear mechanism to amplify the rotation angle of the arm 33. This is preferable because it can increase the load detection accuracy.
- a strain gauge (not shown) attached to the torsion bar 32 and directly measuring the strain of the torsion bar 32 can be used as the displacement detecting mechanism.
- the excitation coil 200 and the pickup coil (secondary coil) 210 are wound around the torsion bar 32, an induced current is passed through the excitation coil 200 by the AC power supply 220, and the excitation coil 200 is obtained from the pickup coil 210.
- a displacement detection mechanism for measuring the induced voltage generated. Since the stress generated in the torsion bar 32 due to the load of the load changes, the induced voltage changes.
- FIG. 30 is a graph showing the correlation between the static load and the output voltage of the pickup coil. As shown in FIG.
- FIG. 31A is a graph showing the relationship between the magnitude of vibration and the output voltage. This is shown in Fig. 31 (b) t, which is shown by J; U (this, torsion no-ku 500) [The connected arm 510 ⁇ The 40 kg weight 520 is suspended, and as shown in Fig. 31 (c), The excitation voltage and the pickup coil were wound around the torsion bar 500 (not shown), the excitation frequency was set to 50 Hz, and the sampling time was measured. Was measured as 10 ⁇ s, and as is clear from Fig. 31 (a), the voltage change became smaller as it attenuated, indicating that the change in vibration could be detected.
- the arrangement of the excitation coil 200 and the pickup coil provided in the torsion bar 32 is not limited, but the pickup coil is separated from one end and the other end of the torsion bar as shown in FIG. It is preferable to wind two pickup coils 210, 211. Since the torsion bar 32 is twisted around one end, there is a stress difference between the one end and the other end, and the output voltage changes due to this stress difference. However, when an external input is applied to the torsion bar 32, a motion generated from the seat structure, such as play, also acts.
- the load signal obtained from the load detecting means is configured to be input to the arithmetic unit 20.
- the type determining means 23b of the state determining means (step) 23 determines whether or not there is a load variation, and if the load varies in a time series, a body motion is generated. Therefore, it can be determined that the person is a person, and the accuracy of the determination result is improved.
- the load based on the load signal is taken into consideration, compared with the reference load stored in the storage unit in advance, and the size of the physique is determined. It is possible to distinguish adults and children or identify individuals. This is especially effective when distinguishing between adults and children.
- identifying individuals discrimination as to whether they are the same person
- a load detecting means such as a displacement detecting mechanism using the above-described excitation coil can detect a dynamic load fluctuation due to body motion means that if this is time-series data, The fluctuation of the living body due to the body motion, which is one of the signals, can be shown.
- the load detection means can be used as the displacement signal collection sensor of the present invention instead of a pressure sensor which is not provided as having a function separate from the pressure sensor.
- a vehicle seat used for transportation equipment such as an automobile, a train, and an aircraft is taken as an example of the load body support means.
- the present invention is also applicable to seats or the like on which a person sits at the time of inspection diagnosis or the like, or beddings such as futons, mattresses, and beds.
- it is suitable for use in vehicle seats because it reduces the influence of noise and can accurately determine the physical and mental state and the distinction between people and things.
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- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Heart & Thoracic Surgery (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Medical Informatics (AREA)
- Biomedical Technology (AREA)
- Physics & Mathematics (AREA)
- Biophysics (AREA)
- Mechanical Engineering (AREA)
- Aviation & Aerospace Engineering (AREA)
- Transportation (AREA)
- Psychology (AREA)
- Child & Adolescent Psychology (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Psychiatry (AREA)
- Hospice & Palliative Care (AREA)
- Educational Technology (AREA)
- Developmental Disabilities (AREA)
- Social Psychology (AREA)
- Anesthesiology (AREA)
- Physiology (AREA)
- Dentistry (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Cardiology (AREA)
- Seats For Vehicles (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Chair Legs, Seat Parts, And Backrests (AREA)
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2006511461A JP4637098B2 (ja) | 2004-03-25 | 2005-03-22 | 負荷体状態判定装置、乗物用シート及びコンピュータプログラム |
US10/598,956 US7496457B2 (en) | 2004-03-25 | 2005-03-22 | Load body state judging device, vehicle seat and computer program |
EP05727075A EP2113198B1 (en) | 2004-03-25 | 2005-03-22 | Load body state judgment device, vehicle seat, and computer program |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2004-089263 | 2004-03-25 | ||
JP2004089263 | 2004-03-25 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2005092193A1 true WO2005092193A1 (ja) | 2005-10-06 |
Family
ID=35055942
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2005/005147 WO2005092193A1 (ja) | 2004-03-25 | 2005-03-22 | 負荷体状態判定装置、乗物用シート及びコンピュータプログラム |
Country Status (5)
Country | Link |
---|---|
US (1) | US7496457B2 (ja) |
EP (1) | EP2113198B1 (ja) |
JP (1) | JP4637098B2 (ja) |
CN (1) | CN100475143C (ja) |
WO (1) | WO2005092193A1 (ja) |
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US8104832B2 (en) | 2007-02-14 | 2012-01-31 | Delta Tooling Co., Ltd. | Seat including a torsion bar |
WO2008099537A1 (ja) | 2007-02-14 | 2008-08-21 | Delta Tooling Co., Ltd. | 生体信号分析装置、シート及び生体信号分析方法 |
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WO2010134525A1 (ja) | 2009-05-19 | 2010-11-25 | 株式会社デルタツーリング | 飲酒検知システム及びコンピュータプログラム |
US9149231B2 (en) | 2009-05-19 | 2015-10-06 | Delta Tooling Co., Ltd. | Alcohol-drinking detecting system and computer program |
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US10136850B2 (en) | 2009-10-14 | 2018-11-27 | Delta Tooling Co., Ltd. | Biological state estimation device, biological state estimation system, and computer program |
WO2011102208A1 (ja) | 2010-02-18 | 2011-08-25 | 株式会社デルタツーリング | 生体状態推定装置及びコンピュータプログラム |
WO2012057331A1 (ja) | 2010-10-29 | 2012-05-03 | 株式会社デルタツーリング | 生体状態推定装置及びコンピュータプログラム |
US9622708B2 (en) | 2010-10-29 | 2017-04-18 | Delta Tooling Co., Ltd. | Biological body state estimation device and computer program |
JP2012239480A (ja) * | 2011-05-14 | 2012-12-10 | Delta Tooling Co Ltd | 生体状態推定装置及びコンピュータプログラム |
RU2592246C2 (ru) * | 2011-09-04 | 2016-07-20 | Дельта Тулинг Ко., Лтд. | Приспособление для обнаружения биологических сигналов |
JP2013052108A (ja) * | 2011-09-04 | 2013-03-21 | Delta Tooling Co Ltd | 生体信号検出機構 |
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US9456770B2 (en) | 2012-12-14 | 2016-10-04 | Delta Tooling Co., Ltd. | Device for determining biological state during driving and computer program |
JP2016101323A (ja) * | 2014-11-28 | 2016-06-02 | テイ・エス テック株式会社 | 状態判定システム |
US20180312166A1 (en) * | 2017-04-28 | 2018-11-01 | Nxp B.V. | Vibration sensor |
US10464569B2 (en) * | 2017-04-28 | 2019-11-05 | Nxp B.V. | Vibration sensor |
JP2020532455A (ja) * | 2017-08-29 | 2020-11-12 | タクチュアル ラブズ シーオー. | センサーを備える車両部品 |
Also Published As
Publication number | Publication date |
---|---|
CN1933780A (zh) | 2007-03-21 |
US20070299636A1 (en) | 2007-12-27 |
CN100475143C (zh) | 2009-04-08 |
US7496457B2 (en) | 2009-02-24 |
EP2113198A4 (en) | 2011-03-09 |
JPWO2005092193A1 (ja) | 2008-02-07 |
EP2113198B1 (en) | 2012-07-11 |
EP2113198A1 (en) | 2009-11-04 |
JP4637098B2 (ja) | 2011-02-23 |
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