WO2023120064A1 - 疲労推定装置、疲労推定システム、及び疲労推定方法 - Google Patents

疲労推定装置、疲労推定システム、及び疲労推定方法 Download PDF

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Publication number
WO2023120064A1
WO2023120064A1 PCT/JP2022/044024 JP2022044024W WO2023120064A1 WO 2023120064 A1 WO2023120064 A1 WO 2023120064A1 JP 2022044024 W JP2022044024 W JP 2022044024W WO 2023120064 A1 WO2023120064 A1 WO 2023120064A1
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Prior art keywords
fatigue
subject
estimation
posture
fatigue level
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English (en)
French (fr)
Japanese (ja)
Inventor
一輝 橋本
正貴 小野
崇 佐藤
洋介 井澤
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Panasonic Intellectual Property Management Co Ltd
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Panasonic Intellectual Property Management Co Ltd
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Priority to JP2023569219A priority Critical patent/JP7762887B2/ja
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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—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/107—Measuring physical dimensions, e.g. size of the entire body or parts thereof
    • 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

Definitions

  • the present disclosure relates to a fatigue estimation system for estimating a subject's degree of fatigue, a fatigue estimation device used in the estimation system, and a fatigue estimation method.
  • Patent Document 1 discloses a fatigue determination device that determines the presence or absence of fatigue and the type of fatigue based on force measurement and bioelectrical impedance measurement. .
  • the present disclosure provides a fatigue estimating device and the like for estimating the degree of fatigue with higher accuracy.
  • a fatigue estimation device includes a position acquisition unit that acquires information about the position of a body part of a subject, and estimates the posture of the subject based on the information acquired by the position acquisition unit.
  • a subjective acquisition unit that acquires the subjective fatigue level felt by the subject; and the duration of the posture estimated by the posture estimation unit, using the acquired subjective fatigue level as a starting fatigue level.
  • a fatigue estimation unit for estimating the subject's fatigue level based on, calculating parameters for determining an estimation formula from the received subjective fatigue level, and applying the calculated parameters to the estimation formula and a fatigue estimating unit that estimates the degree of fatigue of the subject using the fatigue estimation unit.
  • a fatigue estimation system includes an information output device that outputs information about the position of a body part of a subject, and based on the information output by the information output device, the posture of the subject a posture estimating unit that estimates a first receiving unit that receives input of the subjective fatigue level felt by the subject; and a fatigue level starting from the subjective fatigue level that has received the input.
  • a fatigue estimating unit for estimating the fatigue level of the subject based on the duration of the posture obtained by calculating a parameter for determining an estimation formula from the received subjective fatigue level, and calculating the calculated parameter
  • a fatigue estimation method acquires information about positions of body parts of a subject, estimates the posture of the subject based on the acquired information, The input of the subjective fatigue level is received, the parameter for determining the estimation formula is calculated from the received subjective fatigue level, the input is used as the starting point fatigue level, and the estimated fatigue level is Based on the duration of the posture, the fatigue level of the subject is estimated using the estimation formula to which the calculated parameters are applied.
  • a fatigue estimation device or the like according to one aspect of the present disclosure can estimate fatigue with higher accuracy.
  • FIG. 1A is a first diagram for explaining estimation of fatigue level according to the embodiment.
  • FIG. 1B is a second diagram for explaining estimation of fatigue level according to the embodiment.
  • FIG. 1C is a third diagram for explaining estimation of fatigue level according to the embodiment.
  • FIG. 2A is a block diagram showing the functional configuration of the fatigue estimation system according to the embodiment;
  • FIG. 2B is a diagram explaining determination of an estimation formula according to the embodiment.
  • FIG. 3A is a flowchart showing a fatigue level estimation method according to the embodiment.
  • FIG. 3B is a sub-flow chart detailing some steps according to an embodiment.
  • 4A is a diagram showing a subject standing still in Posture A.
  • FIG. 4B is a diagram showing a subject standing still in Posture B.
  • FIG. 5A is a first diagram illustrating accumulation of estimated fatigue level of a subject according to the embodiment.
  • FIG. 5B is a second diagram illustrating accumulation of estimated fatigue level of the subject according to the embodiment.
  • FIG. 6 is a first diagram showing a display example of estimation results according to the embodiment.
  • FIG. 7 is a second diagram showing a display example of estimation results according to the embodiment.
  • FIG. 8 is a diagram for explaining posture estimation according to a modification of the embodiment.
  • each figure is a schematic diagram and is not necessarily strictly illustrated. Moreover, in each figure, the same code
  • FIG. 1A is a first diagram for explaining estimation of fatigue level according to the embodiment.
  • FIG. 1B is a second diagram for explaining estimation of fatigue level according to the embodiment.
  • FIG. 1C is a third diagram for explaining estimation of fatigue level according to the embodiment.
  • the fatigue estimation system 200 uses an image output by imaging the subject 11 using the imaging device 201 to estimate the fatigue level of the subject 11. It is a system that The imaging device 201 is not limited in its form as long as it is a camera that captures the subject 11 and outputs an image, and as shown in FIG. Alternatively, it may be a camera mounted on a PC, a smartphone, a tablet terminal, or the like operated by the subject 11 .
  • the subject is in a posture of sitting on the chair 12 and working with a work target placed on the desk surface 13 a of the desk 13 .
  • the degree of fatigue of the subject 11 is estimated based on the fatigue accumulated by taking a static posture with a fixed posture among the fatigue of the subject 11 .
  • this estimates the fatigue accumulated by the load on at least one of muscles and joints and deteriorating blood flow (hereinafter also referred to as decreased blood flow) due to a fixed posture.
  • the subject 11 is in a static posture, sitting, lying down or standing still for at least a certain period of time.
  • the fixed period is, for example, a minimum period during which fatigue can be estimated in the fatigue estimation system 200, such as several tens of seconds or several seconds. Such a period is determined depending on the processing capability of the imaging device 201 and the estimating device 100 (an example of the fatigue estimating device, see FIG. 2A described later) that configure the fatigue estimating system 200 .
  • Examples of subjects 11 who take such a stationary posture include desk workers in offices, drivers who steer moving bodies, people who perform muscle strength training using a load in a stationary posture, residents of facilities such as hospitals, airplanes, and the like. passengers and crew members.
  • An image captured and output by the imaging device 201 is processed by the estimation device 100, and the posture of the subject 11 is estimated as shown in FIG. 1B.
  • the estimated posture of the subject 11 is output as a rigid body link model 11a as an example.
  • the straight skeletons are connected by joints indicated by black dots, and the posture of the subject 11 can be reproduced by the positional relationship between the two skeletons connected by one joint.
  • the posture is estimated by image recognition, and is output as the rigid body link model 11a based on the positional relationship between the joints and the skeleton.
  • the estimated rigid body link model 11a By applying the estimated rigid body link model 11a to the musculoskeletal model 11c shown in FIG.
  • the amount of load applied to at least one of the muscles and joints of each body part is calculated as an estimated value. Since the estimated value of the load on at least one of the muscles and joints of each body part is accumulated as the duration of the stationary posture increases, calculation using the estimated value of the load and the duration The degree of fatigue due to the object person 11 maintaining a still posture is calculated by .
  • “at least one of muscles and joints” is also expressed as “muscles and/or joints.”
  • the degree of fatigue based on the estimated value of the blood flow of the subject 11 in addition to the estimated value of the load applied to the muscles and/or joints.
  • an example of estimating the fatigue level of the subject 11 using the estimated values of the load on the muscles and the load on the joints will be mainly described. It is also possible to estimate the degree of fatigue of the subject 11 with higher accuracy.
  • the fatigue level of the subject 11 can also be estimated using an estimated value of any one of the amount of load on the muscles of the subject 11, the amount of load on the joints, and the amount of blood flow.
  • the fatigue estimation system 200 estimates at least one of the amount of load on the muscles of the subject 11, the amount of load on the joints, and the amount of blood flow based on the duration of the posture. to estimate The fatigue estimation system 200 estimates the degree of fatigue of the subject 11 based on the estimated value of at least one of the estimated muscle load, joint load, and blood flow of the subject 11 .
  • the estimated value of the load amount may be simply referred to as the load amount or the estimated value.
  • the load is replaced with the blood flow, a large load is replaced with a decrease in blood flow, and a small load is replaced with an increase in blood flow.
  • the blood flow is information for quantifying the blood flow that deteriorates when the subject 11 maintains the posture.
  • the blood flow may be obtained as an absolute numerical value at the time of measurement, or may be obtained as a relative numerical value between two different time points.
  • the degree of deterioration of the blood flow of the subject 11 can be estimated from the posture of the subject 11 and the relative numerical values of the blood flow at two points of time when the posture starts and ends.
  • the blood flow rate of the subject can be calculated simply from the posture of the subject 11 and the duration of the posture. can be estimated.
  • the musculoskeletal model 11c described above is used to estimate at least one of the load on the muscles, the load on the joints, and the blood flow from the posture of the subject 11. Therefore, as a method for estimating the load on muscles, the load on joints, and the blood flow, it is possible to apply a method using actual measurement data in addition to the musculoskeletal model 11c described above.
  • This measured data is a database constructed by accumulating measured values of load on muscles, load on joints, and blood flow, which are measured for each posture, in association with the posture.
  • the fatigue estimation system 200 in this case, by inputting the estimated posture of the subject 11 into the database, the measured values of the load on the muscles, the load on the joints, and the blood flow in the corresponding posture are obtained. can be obtained as output.
  • the actual measurement data may be constructed using actual measurement values for each individual in consideration of individual differences in the subject 11, and statistical analysis or machine learning is performed for big data obtained from an unspecified number of subjects. It may be qualified and constructed so as to match each subject 11 by analysis processing such as.
  • FIG. 2A is a block diagram showing the functional configuration of the fatigue estimation system according to the embodiment
  • the fatigue estimation system 200 in the present disclosure includes an estimation device 100, an imaging device 201, a timer device 202, a pressure sensor 203, a reception device 204, a display device 205, and a recovery device 206.
  • Estimation apparatus 100 includes first acquisition section 101, second acquisition section 102, third acquisition section 103, fourth acquisition section 104, posture estimation section 105, first calculation section 106, and second calculation section. 107 , a fatigue estimation unit 108 , an instruction unit 110 and an output unit 109 .
  • the first acquisition unit 101 is a communication module that is connected to the imaging device 201 and acquires an image of the subject 11 from the imaging device 201 . That is, the first acquisition unit 101 is an example of a position acquisition unit.
  • the connection between the first acquisition unit 101 and the imaging device 201 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the second acquisition unit 102 is a communication module that is connected to the clock device 202 and acquires time from the clock device 202 .
  • the connection between the second acquisition unit 102 and the timing device 202 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the third acquisition unit 103 is a communication module that is connected to the pressure sensor 203 and acquires pressure distribution from the pressure sensor 203 .
  • the connection between the third acquisition unit 103 and the pressure sensor 203 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the fourth acquisition unit 104 is connected to the reception device 204, and is a communication module that acquires the subjective fatigue level, which is the subjective fatigue level felt by the subject 11, and the personal information of the subject 11 from the reception device 204. is. That is, the fourth acquisition unit 104 has both the function of the subjective acquisition unit and the function of the personal information acquisition unit.
  • the connection between the fourth acquisition unit 104 and the reception device 204 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the posture estimation unit 105 is a processing unit realized by executing a predetermined program using a processor and memory.
  • the posture of the subject 11 is estimated by the processing of the posture estimation unit 105 based on the image acquired by the first acquisition unit 101 and the pressure distribution acquired by the third acquisition unit 103 .
  • the first calculation unit 106 is a processing unit realized by executing a predetermined program using a processor and memory. Based on the estimated posture of the subject 11 and the personal information acquired by the fourth acquisition unit, the amount of load applied to each muscle and/or joint is calculated by the processing of the first calculation unit 106 .
  • the second calculation unit 107 is a processing unit realized by executing a predetermined program using a processor and memory. Through the processing of the second calculation unit 107, the amount of recovery from fatigue in each muscle and/or joint is calculated based on the estimated amount of change in the posture of the subject.
  • the fatigue estimation unit 108 is a processing unit realized by executing a predetermined program using a processor and memory. Fatigue estimation section 108 uses the posture estimated by posture estimation section 105 and the time acquired by second acquisition section 102 to estimate the degree of fatigue of subject 11 based on the duration of the posture estimated. presume.
  • the fatigue estimation unit 108 estimates the fatigue level of the subject 11 based on the duration of the posture estimated by the posture estimation unit 105. At this time, based on the subjective fatigue level received as input, An estimation formula used for estimating the fatigue level of the subject 11 is determined, and the fatigue level of the subject 11 is estimated according to the determined estimation formula.
  • the fatigue estimation unit 108 uses the subjective fatigue level and personal information acquired by the fourth acquisition unit 104 to determine the estimation formula. More specifically, the fatigue estimating unit 108 uses a candidate formula selection model in which the relationships between personal information and candidate formulas that are candidates for the estimation formula are learned in advance by machine learning. The fatigue estimation unit 108 obtains output candidate formulas by inputting the acquired personal information into the candidate formula selection model.
  • the candidate formula is, for example, a function whose coefficients are indeterminate.
  • Candidate formulas are any functions such as linear functions, quadratic functions, exponential functions, and logarithmic functions clustered from the personal information of the subject 11 in terms of fatigue easiness, fatigue level increase timing, etc. and one function selected from a combination of two or more functions.
  • the fatigue estimation unit 108 determines an estimation formula by applying parameters calculated from the obtained subjective fatigue level to the obtained candidate formula.
  • a parameter is a numerical value corresponding to an unknown coefficient in a candidate formula.
  • the fatigue estimation unit 108 determines the estimation formula by applying the calculated parameters as the coefficients of the candidate formula.
  • the current estimated fatigue level based on the estimation formula currently determined and used for estimating the fatigue level is used.
  • the fatigue estimation unit 108 changes the parameters of the estimation formula used so that the current estimated fatigue level becomes the acquired numerical value of the subjective fatigue level. Then, after the new estimation formula is determined, estimation of the fatigue level is started so that the fatigue level increases or decreases with the acquired subjective fatigue level as a starting point.
  • FIG. 2B is a diagram explaining determination of an estimation formula according to the embodiment.
  • FIG. 2B shows a schematic graph of fatigue levels estimated in the present embodiment along time series.
  • the solid-line graph in the figure indicates the numerical value of the degree of fatigue actually output from the estimation device 100, and the broken-line graph indicates the numerical value of the virtual fatigue degree for explanation.
  • the figure shows the transition of the fatigue level from the start of estimation at the first time point T1 to the second time point T2.
  • candidate formulas of quadratic functions are selected from the personal information of the subject 11 .
  • the coefficient (parameter) of the quadratic function (broken line graph on the left side of the paper) connecting the degree of fatigue at the first time point T1 and the degree of fatigue of the black dots shown as (b) is newly calculated.
  • the degree of fatigue estimated in the period from when the subjective fatigue level is acquired and a new estimation formula is determined to the second time point T2 is based on the determined estimation formula, starting from the fatigue level of the black dots shown as (b). , the fatigue level is closer to the fatigue level felt by the subject 11 .
  • the estimation formula has a difference in transition of the degree of fatigue felt by the subject 11, as shown at the second time point T2 or the like, the gap is more likely to expand as time passes.
  • the estimation apparatus 100 may include a device capable of storing (accumulating) information (not shown) such as a semiconductor memory, an optical disk, or a magnetic disk, and may store parameters calculated in the past as a parameter log. .
  • the fatigue estimation unit 108 uses the parameters calculated in the past included in the parameter log, the subjective fatigue level and the current estimated fatigue level based on the estimation formula currently determined and used to estimate the fatigue level.
  • a parameter for determining the estimation formula may be calculated as an average value of the calculated numerical values.
  • the fatigue estimation unit 108 multiplies and adds a weighting factor so that the weight increases as the elapsed time decreases. By doing so, parameters for determining the estimation formula may be calculated.
  • the fatigue estimation unit 108 can calculate parameters for determining a new estimation formula by adding these numerical values after being multiplied by weighting factors. The sum of the weighting factors is set to 1.00.
  • the instruction unit 110 is a processing unit realized by executing a predetermined program using a processor and memory.
  • the instruction unit 110 is connected to the display device 205 and instructs the subject 11 to input the subjective fatigue level in the first cycle.
  • the connection between the instruction unit 110 and the display device 205 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the instruction unit 110 generates an image including an instruction content such as "Please input the fatigue level that the subject 11 is currently feeling” in order to input the subjective fatigue level of the subject 11, and outputs the image to the display device 205. By doing so, the image is displayed.
  • the subject 11 can cause the fatigue estimation system 200 to receive the input of the subjective fatigue level by inputting the subjective fatigue level to the reception device 204 according to the displayed image. Then, the estimation device 100 can acquire the subjective fatigue level by the fourth acquisition unit 104 .
  • the reception device 204 always receives input of the subjective fatigue level from the subject 11. That is, the subjective fatigue level input from the subject 11 is accepted in a cycle (second cycle) within the cycle (first cycle) of the instruction from the instruction unit 110 displayed in the first cycle.
  • the fourth acquisition unit 104 acquires the subjective fatigue level in the second period within the first period. The more frequently the subjective fatigue level is acquired, the more accurate the estimation of the subject's 11 fatigue level by the fatigue estimation unit 108 can be. Therefore, the estimating apparatus 100 acquires the subjective fatigue level input in accordance with the instruction from the instruction unit 110 in the first period at a minimum, while the subjective fatigue level input by the subject 11 at an arbitrary timing is configured to obtain. If the subject 11 does not input any subjective fatigue level, the first cycle and the second cycle match.
  • the instruction unit 110 In addition to the instruction via the display device 205, the instruction unit 110 generates a voice including the instruction content such as "Please input the degree of fatigue you are currently feeling” via a sound output device (not shown). By playing back, the target person 11 may be instructed to input the subjective fatigue level.
  • the output unit 109 is a communication module that is connected to the display device 205 and the recovery device 206 and outputs the content based on the fatigue level estimation result by the estimation device 100 to the display device 205 and the recovery device 206 .
  • the connection between the output unit 109 and the display device 205 or the recovery device 206 is performed by wire or wirelessly, and the method of communication performed through the connection is not particularly limited.
  • the imaging device 201 is a device that captures an image of the subject 11 and outputs an image, and is realized by a camera.
  • an existing camera such as a security camera or a fixed-point camera may be used in the space where the fatigue estimation system 200 is applied, or a dedicated camera may be newly provided.
  • Such an imaging device 201 is an example of an information output device that outputs an image as information about the position of the body part of the subject 11 . Therefore, the information to be output is an image, and is information including the positional relationship of the body parts of the subject 11 projected on the imaging device.
  • the clock device 202 is a device that measures time and is implemented by a clock.
  • the clock device 202 can transmit time to the connected second acquisition unit 102 .
  • the time measured by the timer 202 may be absolute time or relative elapsed time from a starting point.
  • the timing device 202 can be realized in any form as long as it can measure the time between two points of time when the target person 11 is detected to be still and when the degree of fatigue is estimated (that is, the duration of the stationary posture). good.
  • the pressure sensor 203 is a sensor having a detection surface, and measures the pressure applied to each of the unit detection surfaces that divide the detection surface into one or more. The pressure sensor 203 thus measures the pressure for each unit detection surface and outputs the pressure distribution on the detection surface. The pressure sensor 203 is provided so that the subject 11 is positioned on the detection surface.
  • the pressure sensors 203 are provided on the seat surface and the backrest of the chair on which the subject 11 sits. Further, for example, the pressure sensor 203 may have a marker attached on the detection surface, and the subject 11 may be guided onto the detection surface by a display such as "Please sit on the marker.” Further, by guiding the subject 11 onto the detection surface of the pressure sensor 203 provided on a part of the floor in this manner, the pressure sensor 203 may output the pressure distribution of the subject 11 on the floor. good. Since the pressure distribution is used for the purpose of improving the accuracy of estimating the degree of fatigue, the fatigue estimation system 200 may be implemented without the pressure sensor 203 if sufficient accuracy is ensured.
  • the reception device 204 is a user interface that receives input of the personal information of the subject 11, and is realized by an input device such as a touch panel or keyboard.
  • the personal information includes at least one of age, sex, height, weight, muscle mass, stress level, body fat percentage, exercise proficiency level, information on attendance, and vital information.
  • the age of the target person 11 may be a specific numerical value, or may be an age group divided by 10 years such as teens, 20s, and 30s. The age range may be divided into two divisions based on a predetermined age, such as age and older, or other age groups.
  • the gender of the subject 11 is one suitable for the subject 11, which is selected from two of male and female.
  • the height and weight numerical values of the height and weight of the target person 11 are respectively accepted.
  • the muscle mass the muscle composition ratio of the subject 11 measured using a body composition meter or the like is accepted.
  • the stress level of the subject 11 is selected by the subject 11 himself/herself from options such as high, medium, and low as the degree of subjective stress felt by the subject 11 .
  • the body fat percentage of the subject 11 is the ratio of the body fat weight to the body weight of the subject 11, and is expressed, for example, as a percentage of 100.
  • the subject's 11 exercise proficiency may be quantified by a score obtained when the subject 11 executes a predetermined exercise program, or may be the status of the exercise that the subject 11 usually engages in.
  • the former is quantified by, for example, the time required to perform ten spins, the time required to run 50 meters, the flight distance of a long throw, and the like.
  • the latter is quantified by, for example, how many days a week you exercise or how many hours you exercise.
  • the information about the attendance of the target person 11 is used, for example, as the number of consecutive days of work since the most recent vacation (if the target person is a student, it can be read as the number of consecutive days of school attendance or consecutive number of days of kindergarten attendance).
  • the vital information of the subject 11 is, for example, numerical values such as heart rate, respiration rate, blood pressure, body temperature, blood saturated oxygen concentration, and the like.
  • the reception of personal information functions as a personal information acquisition unit
  • the fatigue estimation system 200 may be realized without the function as the information acquisition unit.
  • the display device 205 is a device for displaying the content based on the fatigue level estimation results output by the output unit 109 .
  • the display device 205 is provided as an example of the presentation device, and another example of the presentation device is a sound output device that allows the target person to listen to the content based on the fatigue level estimation result by voice. may be provided.
  • the presentation device may be realized by any device as long as it can present the estimated fatigue level to the subject.
  • the display device 205 displays an image showing the content based on the result of estimating the degree of fatigue using a display panel such as a liquid crystal panel or an organic EL (Electro Luminescence) panel. The contents displayed by the display device 205 will be described later. Further, if the fatigue estimation system 200 is configured to only reduce the degree of fatigue of the subject 11 using the recovery device 206 for the subject 11, only the recovery device 206 may be provided, and the display device 205 Not required.
  • the recovery device 206 is a device that reduces the degree of fatigue of the subject 11 by promoting the subject's 11 blood circulation. Specifically, the recovery device 206 changes the arrangement of each part of the chair 12 by applying voltage, pressurizing, vibrating, heating, or the like, or by a mechanism provided in the chair 12, so that the sitting subject 11 Actively change the posture of As a result, the recovery device 206 changes the load on at least one of the muscles and joints of the subject 11 and promotes blood circulation. From the viewpoint of the blood flow, by promoting the blood circulation in this way, the influence of the deterioration of the blood flow due to the subject 11 being in a still posture is reduced, and the degree of fatigue is recovered. The recovery device 206 is pre-applied or contacted to the appropriate body part of the subject 11, depending on the configuration of the device.
  • the fatigue estimation system 200 is configured to display only the fatigue level estimation result to the subject 11, only the display device 205 is required, and the recovery device 206 is not essential.
  • FIG. 3A is a flowchart showing a fatigue level estimation method according to the embodiment. Also, FIG. 3B is a sub-flow chart showing details of some steps according to the embodiment.
  • the fatigue estimation system 200 first acquires the personal information of the subject 11 (step S101). Acquisition of personal information is performed by the target person 11 himself/herself or an administrator or the like who manages the fatigue level of the target person 11 by inputting to the reception device 204 .
  • the input personal information of the subject 11 is stored in a storage device or the like (not shown), and is read out and used when estimating the degree of fatigue.
  • the fatigue estimation system 200 detects the subject 11 using the imaging device 201 (step S102). Detection of the subject 11 is performed by determining whether or not the subject 11 has entered the angle of view of the camera, which is the imaging device 201 .
  • the target person 11 may be a specific target person 11, or may be a person from among an unspecified number of people who enters the angle of view of the camera. When the target person 11 is selected from an unspecified number of people, the input of personal information may be omitted. Further, when detecting a specific target person 11, a step of specifying the target person 11 by image recognition or the like is added.
  • the target person 11 inputs personal information, grasps the detection area by the imaging device 201, and enters the detection area to estimate the fatigue level. Therefore, image recognition or the like is not required, and the degree of fatigue is estimated by adding personal information.
  • step S102 When the fatigue estimation system 200 determines that the target person 11 has not been detected (No in step S102), it repeats step S102 until the target person 11 is detected.
  • the image output by the imaging device 201 is acquired by the first acquisition unit 101 (step S103, an example of an acquisition step).
  • the estimation device 100 estimates the posture of the subject 11.
  • the posture estimation unit 105 estimates the posture of the subject 11 based on the acquired image and pressure distribution (posture estimation step S106).
  • the pressure distribution is used, for example, when biased pressure is applied, to correct the estimated pose to form that bias.
  • the first calculator 106 calculates the amount of load on each muscle and/or joint of the subject 11 from the posture estimation result.
  • the personal information obtained in advance is used to correct and calculate the load amount (step S107).
  • the estimation of the posture of the subject 11 is as described with reference to FIG. 1B, and the calculation of the amount of load is as described with reference to FIG. 1C, so detailed description thereof will be omitted.
  • peak values may be based on the subject's 11 gender. Also, if the sex of the subject 11 is male, the amount of load may be small, and if the sex of the subject 11 is female, the amount of load may be large. Alternatively, the smaller the height and weight of the subject 11, the smaller the load, and the larger the height and weight, the larger the load.
  • the load amount may be reduced as the composition ratio of the subject 11 has a large muscle mass, and the load amount may be increased as the composition ratio of the muscle mass of the subject 11 is small.
  • the load amount may be increased as the number of consecutive working days of the target person 11 increases.
  • the vital information of the subject 11 may increase the load amount as the numerical value thereof deviates from the median value of the reference values.
  • the duration of the stationary posture of the subject 11 is measured based on the time acquired by the second acquisition unit 102 (step S108).
  • the fatigue estimating unit 108 adds the load amount calculated above each time the duration time passes by the unit time, and estimates the degree of fatigue of the subject 11 at this point (fatigue estimation step S109).
  • the processes of step S108 and fatigue estimation step S109 are continued until the target person 11 is released from the stationary state. Specifically, it is determined whether or not the stationary state has been released, depending on whether or not the orientation estimated by the orientation estimation unit 105 has changed from a static orientation (step S110).
  • the fatigue estimation step S109 will be described in detail using FIG. 3B.
  • the fatigue estimation unit 108 determines whether or not the subjective fatigue level has been acquired (S109a).
  • the fatigue estimation unit 108 refers to the parameter log and acquires parameters calculated in the past (S109b).
  • the fatigue estimation unit 108 calculates new parameters based on the obtained subjective fatigue level and parameters calculated in the past (S109c).
  • the fatigue estimation unit 108 inputs the personal information to the candidate formula selection model and causes the candidate formula to be output (S109d).
  • the fatigue estimation unit 108 determines a new estimation formula by applying the newly calculated parameters to the output candidate formula (S109e).
  • the fatigue estimation unit 108 estimates the fatigue level of the subject 11 using the newly determined estimation formula (S109f).
  • the fatigue estimation unit 108 determines that the subjective fatigue level is not acquired (No in S109a), without determining a new estimation formula (skipping S109b to S109e), the subject 11 Fatigue level is estimated (S109f).
  • step S110 if it is not determined that the stationary state has been released (No in step S110), the process returns to step S108, measures the duration, proceeds to fatigue estimation step S109, adds the amount of load, and calculates the static posture. is continued, the degree of fatigue of the subject 11 is accumulated. That is, the fatigue estimating unit 108 repeats step S108 and fatigue estimating step S109, so that the slope corresponding to the calculated load amount (when the function is a curve function, it is interpreted as the slope of the tangent line) with respect to the duration time.
  • the fatigue level of the subject 11 is estimated using the increasing function of the fatigue level (corresponding to the above estimation formula).
  • the fatigue level of the subject 11 is initialized (set to 0) at the start timing of the stationary posture, which is the starting point.
  • the posture estimation unit 105 calculates the amount of change in posture from the original stationary state posture to the current posture.
  • the amount of change in posture is calculated for each individual muscle and/or joint, similar to the amount of load described above.
  • the second calculation unit 107 calculates a recovery amount, which is the degree of recovery from fatigue, based on the amount of change in posture (step S111).
  • the change time which is the time during which the posture of the subject 11 continues to change, is measured (step S112).
  • the relationship between the recovery amount and the change time is the same as the relationship between the load amount and the duration time, and the recovery amount of the subject 11 is integrated as long as the posture change continues. That is, the fatigue estimating unit 108 estimates the fatigue level of the subject 11 by subtracting the recovery amount each time the unit time elapses at the timing when the posture of the subject 11 changes (step S113). It should be noted that, in the recovery of the fatigue level, similarly to the fatigue estimation step S109, a new estimation formula may be determined based on the subjective fatigue level and the personal information to estimate the fatigue level.
  • steps S111, S112, and S113 are continued until the posture of the subject 11 is stationary. Specifically, it is determined whether or not the posture estimated by posture estimation section 105 is a static posture (step S114). If the subject 11 is not detected still (No in step S114), return to step S111 to calculate the amount of recovery, proceed to step S112 to measure the change time, and proceed to step S113 to subtract the amount of recovery. Then, as long as the posture change is continued, the fatigue level of the target person 11 is accumulated so as to recover.
  • the fatigue estimating unit 108 repeats steps S111, S112, and S113 so that the slope corresponding to the calculated recovery amount (when the function is a curve function, the slope of the tangent line and the solution
  • the fatigue level of the subject 11 is estimated using the decreasing function of the fatigue level (corresponding to the above estimation formula) having ). Since the recovery amount of the fatigue level depends on the amount of change in posture, the greater the amount of change in posture, the greater the fatigue level of the subject 11, which decreases per unit time.
  • step S114 if the subject 11 is detected to be stationary (Yes in step S114), the process returns to step S105, and the posture and fatigue level are estimated again for a new stationary posture.
  • the fatigue estimation system 200 since the fatigue level of the subject 11 is calculated in consideration of the duration time in the stationary posture based on the image, the burden on the subject 11 is small, and more accurate The degree of fatigue of the subject 11 can be estimated.
  • FIG. 4A is a diagram showing a subject standing still in Posture A.
  • FIG. 4B is a diagram showing the subject standing still in posture B. As shown in FIG.
  • a subject 11 shown in FIGS. 4A and 4B is in a stationary posture in a seated position on a chair 12, similar to that shown in FIG. 1A.
  • FIGS. 4A and 4B there are actually tables, PCs, etc., which are not shown, but only the subject 11 and the chair 12 are shown here.
  • the stationary posture of the subject 11 shown in FIG. 4A is posture A in which the load on the shoulders is relatively large.
  • the stationary posture of the subject 11 shown in FIG. 4B is posture B in which the load on the shoulders is relatively small.
  • FIG. 5A is a first diagram illustrating accumulation of estimated fatigue level of a subject according to the embodiment. Also, FIG. 5B is a second diagram for explaining the accumulation of the subject's fatigue level estimated according to the embodiment.
  • posture A is a posture with a larger load than posture B. Therefore, for example, in certain muscles of the subject 11 (here, muscles related to shoulder movement), the load amount of posture A (slope of the straight line of posture A) is greater than the load of posture B (slope of the straight line of posture B). is also big. Therefore, in the posture A, the target person 11 accumulates (accumulates) a larger degree of fatigue in a shorter time than in the case of standing still in the posture B.
  • the degree of fatigue of the subject 11 is a positive slope increasing function is estimated as the accumulation (addition) of the degree of fatigue by , and the accumulation (addition) turns to recovery (decrease) at the change point where the subject 11 begins to change the posture.
  • the degree of fatigue of the subject 11 is determined by a decreasing function with a negative slope corresponding to the amount of change in posture. It recovers (decreases) by the amount shown as the width of change.
  • the fatigue level of the subject 11 is an increasing function with a positive slope corresponding to the load amount of the posture B, and is estimated as accumulation (addition) of the fatigue level. be done.
  • the degree of fatigue of the subject 11 is estimated in which accumulation and recovery are reflected depending on whether the posture of the subject 11 is stationary or changed.
  • FIG. 6 is a first diagram showing a display example of estimation results according to the embodiment.
  • FIG. 7 is a second diagram showing a display example of estimation results according to the embodiment.
  • the result of estimating the degree of fatigue of the subject 11 can be displayed using the display device 205 and fed back.
  • a display device 205 integrally displays a doll simulating the subject 11 and fatigue levels of the subject 11's shoulders, back, and main parts.
  • the fatigue level of the shoulder is indicated as "stiff shoulder”
  • the fatigue of the back is indicated as “back pain”
  • the fatigue of the lower back is indicated as "low back pain”.
  • the fatigue levels of the subject 11 at three locations are displayed at once, and the fatigue levels at these three locations are estimated from images captured at once. That is, the estimating apparatus 100 detects muscles and/or joints in each of a plurality of body parts including a first part (eg, shoulder), a second part (eg, back), and a third part (eg, waist) of the subject 11. , the degree of fatigue is estimated from one posture of the subject 11 . Therefore, even if the posture of the subject 11 is constant, the degree of fatigue accumulated in muscles and/or joints differs for each body part. can be estimated.
  • a first part eg, shoulder
  • a second part eg, back
  • a third part eg, waist
  • the load amount is calculated for each muscle and/or joint of the subject 11. Therefore, if there is no processing resource limitation, each muscle and/or joint fatigue can be estimated. Therefore, there is no limit to the number of body parts whose fatigue levels are estimated from images captured at one time, and the number may be one, two, or four or more.
  • the estimating device 100 calculates the load amount for each of a plurality of body parts, and calculates the degree of fatigue (the degree of stiff shoulders) of the first part based on the load amount calculated for the first part in one posture of the subject 11. , the fatigue level of the second part (the above-mentioned back pain level) due to the load amount calculated at the second part, and the fatigue level of the third part (the above-mentioned low back pain level) due to the load amount calculated at the third part, can be estimated.
  • the fourth acquisition unit 104 obtains the subjective fatigue level of each body part of the subject 11 as the subjective fatigue level. Get the entered information, including:
  • the subjective fatigue level is the fatigue level of the first part of the body part of the subject 11, the fatigue level of the second part different from the first part, and the first part and the second part Including the degree of fatigue of the third part different from.
  • the fatigue estimating unit 108 calculates a first parameter for determining a first estimation formula that is an estimation formula for the first part from the fatigue level of the first part included in the subjective fatigue level that has received the input, The degree of fatigue of the first portion is estimated using a first estimation formula to which the calculated first parameter is applied.
  • the fatigue estimation unit 108 calculates a second parameter for determining a second estimation formula, which is an estimation formula for the second part, from the fatigue level of the second part included in the received subjective fatigue level. , the fatigue level of the second portion is estimated using a second estimation formula to which the calculated second parameter is applied.
  • the fatigue estimating unit 108 calculates the third parameter for determining the third estimation formula, which is the estimation formula for the third part, from the fatigue level of the third part included in the received subjective fatigue level. , the degree of fatigue of the third portion is estimated using a third estimation formula to which the calculated third parameter is applied.
  • the degree of stiff shoulders is estimated from the amount of load on the trapezius muscle
  • the degree of back pain is estimated from the degree of fatigue of the latissimus dorsi muscle
  • the degree of low back pain is estimated from the amount of load on the lumbar paraspinal muscles.
  • one fatigue level may be estimated from the load of one muscle and / or joint, but one fatigue level is estimated from the combined load of a plurality of muscles and / or joints.
  • the degree of stiff neck that is, one degree of shoulder fatigue
  • the degree of stiff neck may be estimated from the average value of the loads of the trapezius muscle, the levator scapula muscle, the rhomboid muscle, and the deltoid muscle.
  • a more realistic fatigue degree can be obtained by weighting the amount of load on the muscles and/or joints that have a particularly large effect on the degree of fatigue of the relevant body part. Estimates may be made.
  • the degree of fatigue estimated in this way may be indicated as a relative position on a reference meter with a minimum value of 0 and a maximum value of 100 as shown.
  • a reference value is provided at a predetermined position on the reference meter.
  • Such a reference value is set to the relative position (or before and after) of the degree of fatigue at which subjective symptoms such as pain may occur in a general subject 11 quantified in advance by an epidemiological survey or the like. Therefore, different reference values may be set according to the degree of fatigue of each body part.
  • the display device 205 may display a warning to the target person 11 as an estimation result when the estimated fatigue level of the target person 11 reaches the reference value.
  • the reference value here is an example of the first threshold.
  • the display device 205 may display a specific coping method such as "Recommend taking a break" as shown in the drawing.
  • the display device 205 when the estimated fatigue level of the target person 11 reaches the reference value, displays the current estimated fatigue level of the target person 11 for the target person 11.
  • a recommended posture with less load on the body part that reaches the reference value may be displayed.
  • the reference value here is an example of the second threshold, and may be the same as or different from the first threshold.
  • the displayed recommended posture may be accompanied by specific notes such as "put your weight on the back of the chair” and "sit deeply on the seat” together with the doll that assumes that posture.
  • the fatigue estimation system 200 actively activates the subject 11. It is also possible to consider a configuration that recovers the degree of fatigue of the user. Specifically, the recovery device 206 shown in FIG. 2A operates to recover the fatigue level of the subject 11 .
  • the specific configuration of the recovery device 206 is as described above, so a description thereof will be omitted.
  • the reference value here is an example of the third threshold, and may be the same as or different from either the first threshold or the second threshold.
  • the fatigue estimation system 200 in the present embodiment includes the imaging device 201 (information output device) that outputs information about the position of the body part of the subject 11, and based on the information output by the information output device a posture estimation unit 105 that estimates the posture of the subject 11; a fourth acquisition unit 104 (subjective acquisition unit) that acquires the subjective fatigue level felt by the subject 11; A fatigue estimation unit 108 that estimates the fatigue level of the subject 11 based on the duration of the posture estimated by the posture estimation unit 105, and a parameter for determining the estimation formula from the acquired subjective fatigue level A fatigue estimation unit 108 that estimates the fatigue level of the subject 11 using an estimation formula that uses the calculated parameters, and a display device 205 (presentation device) that presents the estimated fatigue level of the subject 11. Prepare.
  • Such a fatigue estimation system 200 can have the same effects as the estimation device 100 described later.
  • an information output device for example, an imaging device 201 that outputs information about the position of the body part of the subject 11, and information (for example, an image) output by the information output device.
  • An estimation device 100 that estimates the posture and estimates the degree of fatigue of the subject 11 based on the estimated posture and the duration of the posture.
  • the information output device is the imaging device 201 that captures an image of the subject 11 and outputs an image as information about the position of the body part, and the estimation device 100 outputs the image based on the image output by the imaging device 201.
  • the posture of the subject 11 may be estimated.
  • Such a fatigue estimation system 200 can estimate the degree of fatigue of the subject 11 using the image output by the imaging device 201 .
  • the posture of the subject 11 estimated from the output image is used. Specifically, the amount of load on the muscles, the amount of load on the joints, and the deterioration of blood flow due to the maintenance of a certain static posture are calculated from the duration of time spent in the static posture in which the posture of the subject 11 is still. Accumulation of fatigue accompanying such as is quantified as a degree of fatigue.
  • the degree of fatigue of the subject 11 is calculated based on the image, taking into account the duration of the stationary posture, so that the burden on the subject 11 is reduced, and more accurate It is possible to estimate the degree of fatigue of the subject 11 in a static posture.
  • the estimating apparatus 100 calculates the amount of load on at least one of the muscles and joints of the subject 11 used to maintain the estimated posture using the musculoskeletal model 11c, and increases the degree of fatigue with respect to the duration.
  • the fatigue level may be estimated using a function, and in the increasing function used for estimating the fatigue level, the greater the calculated load amount, the greater the fatigue level that increases per unit time.
  • the load amount for at least one of individual muscles and joints is calculated using the musculoskeletal model 11c.
  • the degree of fatigue of the subject 11 can be easily estimated by an increasing function whose slope is the amount of load calculated in this manner. Therefore, it is possible to easily estimate the degree of fatigue of the subject 11 with higher accuracy.
  • the estimating apparatus 100 calculates the load amount of at least one of muscles and joints in each of two or more body parts including the first part and the second part among the body parts of the subject 11, In one posture of 11, at least a first fatigue level of the first part based on the load amount calculated for the first part and a second fatigue level of the second part based on the load amount calculated for the second part are calculated. can be estimated.
  • the degree of fatigue for two or more body parts of the subject 11 with one imaging. There is no need to perform measurements for estimating fatigue levels for each body part, and the fatigue levels of a plurality of body parts can be estimated quickly and substantially simultaneously.
  • the degree of fatigue estimated substantially at the same time makes it possible to easily specify the body part of the subject 11 that is likely to get fatigued, which is effective when devising a coping method for recovering from the degree of fatigue. Therefore, it is possible to quickly and effectively estimate the degree of fatigue of the subject 11 .
  • the estimation apparatus 100 estimates the fatigue level using a decreasing function of the fatigue level with respect to time, and the decreasing function used for estimating the fatigue level has a large amount of change in posture.
  • the degree of fatigue that decreases per unit time may be increased as much as possible.
  • the load on at least one of the muscles and joints is changed, and the recovery of the fatigue level by improving the blood flow is reflected in the estimated fatigue level. be done. Therefore, it is possible to more accurately estimate the degree of fatigue of the target person 11 in relation to the position of the body part of the target person 11 in the still posture.
  • the fatigue estimation system 200 further includes a display device that displays a warning to the target person 11 as an estimation result when the fatigue level of the target person 11 estimated by the estimation device 100 reaches the first threshold. 205 may be provided.
  • the target person 11 and the like can know from the warning displayed on the display device 205 that the fatigue level of the target person 11 has reached the first threshold.
  • the target person 11 can reduce the possibility of suffering from poor physical condition, injury, accident, etc. due to fatigue by coping with the accumulated fatigue level according to the displayed warning. Therefore, the degree of fatigue estimated with higher accuracy is used to suppress the discomfort caused by the fatigue of the subject 11 .
  • the fatigue estimation system 200 may be triggered by the fact that the degree of fatigue of the subject 11 estimated by the estimation device 100 has reached the second threshold, and the load on the subject 11 may be more than the posture.
  • a display device 205 that displays a few recommended postures may be provided.
  • the target person 11 and the like can cope with the fatigue level of the target person 11 that has reached the second threshold by using the recommended posture displayed on the display device 205 .
  • the recommended posture By changing to the recommended posture, it is expected that the degree of fatigue of the subject 11 will recover, so that the subject 11 can suppress accumulation of fatigue without being particularly conscious of it. Therefore, the degree of fatigue estimated with higher accuracy is used to suppress the discomfort caused by the fatigue of the subject 11 .
  • the fatigue estimation system 200 further accelerates the blood circulation of the subject 11 when the fatigue level of the subject 11 estimated by the estimation device 100 reaches the third threshold.
  • a recovery device 206 may be provided to reduce the degree of fatigue of the.
  • the recovery device 206 since the recovery device 206 is expected to recover the degree of fatigue of the subject 11, the subject 11 can suppress the accumulation of fatigue without being particularly conscious of it. Therefore, the degree of fatigue estimated with higher accuracy is used to suppress the discomfort caused by the fatigue of the subject 11 .
  • the fatigue estimation system 200 further includes a pressure sensor 203 that outputs a pressure distribution indicating the distribution of pressure applied on the sensing surface, and the estimation device 100 detects the pressure distribution output by the pressure sensor 203. Based on this, the estimated posture of the subject 11 may be corrected, and the load amount for maintaining the corrected posture may be calculated.
  • the pressure distribution output by the pressure sensor 203 can be used to estimate the posture of the subject 11 . Therefore, the posture of the subject 11 can be estimated with high accuracy by correcting the pressure distribution. Therefore, the degree of fatigue of the subject 11 can be estimated with higher accuracy.
  • the fatigue estimation system 200 further includes personal information including at least one of age, sex, height, weight, muscle mass, stress level, body fat percentage, and exercise proficiency level of the subject 11. Equipped with a receiving device 204 that receives input, the estimating device 100 may correct the load amount based on the personal information received by the receiving device 204 when calculating the load amount for maintaining the estimated posture. good.
  • the personal information received by the receiving device 204 can be used to calculate the amount of load. Therefore, the load amount in the stationary posture can be calculated with high accuracy by correction using the personal information. Therefore, the degree of fatigue of the subject 11 can be estimated with higher accuracy.
  • the estimation apparatus 100 includes the first acquisition unit 101 (position acquisition unit) that acquires information about the position of the body part of the subject 11, and the information acquired by the position acquisition unit.
  • a posture estimating unit 105 that estimates the posture of the subject 11 based on, a fourth acquiring unit 104 (subjective acquiring unit) that acquires the subjective fatigue level felt by the subject 11, and the acquired subjective fatigue level as a starting point
  • a fatigue estimation unit 108 for estimating the fatigue level of the subject 11 based on the duration of the posture estimated by the posture estimation unit 105, and for determining the estimation formula from the acquired subjective fatigue level and a fatigue estimating unit 108 that calculates parameters and estimates the degree of fatigue of the subject 11 using an estimation formula to which the calculated parameters are applied.
  • Such an estimation device 100 can acquire the subjective fatigue level and apply parameters calculated based on the acquired subjective fatigue level to the estimation formula used to estimate the fatigue level.
  • the determined estimation formula is applied with a parameter that makes the estimation result approach the subjective fatigue level, so it is possible to estimate and output the estimation result that is closer to the fatigue level felt by the subject 11. . Therefore, from the viewpoint of being close to the fatigue level felt by the subject 11, it is possible to estimate the fatigue level with higher accuracy.
  • the fatigue estimation unit 108 accumulates parameter logs containing parameters calculated in the past in order to determine the estimation formula from the subjective fatigue degree acquired in the past, and the accumulated parameter logs and newly acquired A parameter for determining the estimation formula may be calculated from the subjective fatigue level.
  • the fatigue estimation unit 108 may calculate a parameter for determining an estimation formula from a newly acquired subjective fatigue level as an average value of previously calculated parameters included in the parameter log.
  • the average value of the parameter calculated in the past that is, the average value of the parameter calculated in the past and the temporary parameter calculated from the newly acquired subjective fatigue level is calculated as a new parameter. can be done.
  • the fatigue estimating unit 108 multiplies each parameter calculated in the past included in the parameter log by a weighting factor so that the weight increases as the elapsed time decreases, and adds the newly acquired subjective A parameter for determining the estimation formula may be calculated from the degree of fatigue.
  • an individual including at least one of age, sex, height, weight, muscle mass, stress level, body fat percentage, exercise proficiency level, information on attendance, and vital information of the subject 11
  • Another function of the fourth acquisition unit 104 that acquires information is provided, and the estimation formula is the candidate that is output by inputting the acquired personal information of the subject 11 into the candidate formula selection model.
  • the parameters calculated by the fatigue estimator 108 may be applied to the formula and determined.
  • candidates for the estimation formula can be selected from the personal information of the subject 11.
  • the personal information includes information closely related to the tendency of fatigue susceptibility.
  • As a candidate formula selection model by inputting personal information into a trained model that has undergone machine learning etc. of the correlation between personal information and the tendency of susceptibility to fatigue (here, as a candidate formula for the estimation formula), It is possible to select a candidate formula for determining a reasonable estimation formula based on personal information.
  • an instruction unit 110 is further provided for instructing the subject 11 to input the subjective fatigue level in the first cycle, and the subjective acquisition unit acquires the subjective fatigue level in the second cycle within the first cycle.
  • the subjective fatigue level includes the fatigue level of the first part of the body part of the subject 11 and the fatigue level of the second part different from the first part
  • the fatigue estimation unit 108 uses the acquired subjective fatigue level From the fatigue level of the included first part, calculate the first parameter for determining the first estimation formula, which is the estimation formula related to the first part, and use the first estimation formula to which the calculated first parameter is applied.
  • the degree of fatigue of the second portion may be estimated using a second estimation formula to which the second parameter is applied.
  • the subjective fatigue level is obtained, and the first parameter calculated based on the fatigue level of the first part can be applied to the first estimation formula used for estimating the fatigue level of the first part. Since the determined first estimation formula applies the first parameter such that the estimation result approaches the subjective fatigue level of the first part, It is possible to estimate and output a close estimation result.
  • the second parameter calculated based on the degree of fatigue of the second portion can be applied to the second estimation formula used for estimating the degree of fatigue of the second portion. Since the determined second estimation formula applies the second parameter such that the estimation result approaches the subjective degree of fatigue of the second part, It is possible to estimate and output a close estimation result. That is, for two or more different parts of the subject 11 (including the first part and the second part), each individually according to the tendency of the subject's 11 susceptibility to fatigue, more accurate and site-specific It becomes possible to estimate the degree of fatigue.
  • a first acquisition unit 101 that acquires information about the positions of body parts of the subject 11, and a posture estimation unit 105 that estimates the posture of the subject 11 based on the information acquired by the first acquisition unit 101. and a fatigue estimation unit 108 that estimates the degree of fatigue based on the duration of the posture estimated by the posture estimation unit 105 .
  • Such an estimation device 100 can estimate the degree of fatigue of the subject 11 using information such as acquired images.
  • the posture of the subject 11 estimated from the acquired image or the like is used. Specifically, the load on at least one of the muscles and joints and the deterioration of blood flow due to the maintenance of a constant static posture from the duration of time elapsed in the static posture in which the posture of the subject 11 is static. The accumulation of fatigue associated with this is quantified as the degree of fatigue. In this way, since the estimation device 100 calculates the fatigue level of the subject 11 in consideration of the duration of the static posture, it is possible to more accurately estimate the fatigue level of the subject 11 in the static posture. can.
  • the method of estimating fatigue in the present embodiment acquires information about the positions of the body parts of the subject 11, estimates the posture of the subject 11 based on the acquired information, Obtain the subjective fatigue level of the body, calculate the parameters for determining the estimation formula from the obtained subjective fatigue level, use the acquired subjective fatigue level as the starting fatigue level, and based on the estimated posture duration, The degree of fatigue of the subject 11 is estimated using an estimation formula to which the calculated parameters are applied.
  • an acquisition step (step S103 or the like) of acquiring information about the positions of body parts of the subject 11, and a posture estimation step S106 of estimating the posture of the subject 11 based on the information acquired in the acquisition step. and a fatigue estimation step S109 for estimating the degree of fatigue based on the duration of the posture estimated in the posture estimation step S106.
  • Such a fatigue estimation method has the same effects as the estimation device 100 described above.
  • the processing executed by a specific processing unit may be executed by another processing unit.
  • the order of multiple processes may be changed, and multiple processes may be executed in parallel.
  • the fatigue estimation system or estimation device in the present disclosure may be realized by a plurality of devices each having a part of a plurality of components, or may be realized by a single device having all of the plurality of components. good. Also, some of the functions of a component may be implemented as functions of another component, and each function may be distributed among the components in any way.
  • the present disclosure includes any form having a configuration in which substantially all of the functions that can realize the fatigue estimation system or the estimating device of the present disclosure are provided.
  • each component may be realized by executing a software program suitable for each component.
  • Each component may be realized by reading and executing a software program recorded in a recording medium such as a hard disk or a semiconductor memory by a program execution unit such as a CPU or processor.
  • each component may be realized by hardware.
  • each component may be a circuit (or integrated circuit). These circuits may form one circuit as a whole, or may be separate circuits. These circuits may be general-purpose circuits or dedicated circuits.
  • the posture of the subject is estimated from the image using the rigid link model generated by image recognition, the load amount is calculated from the estimated posture of the subject, and based on the load amount and the duration time.
  • the method of estimating the degree of fatigue is not limited to this. Any existing method may be used as a method of estimating the posture of the subject from the image, and any existing method may be used as a method of estimating the amount of load from the posture of the subject.
  • FIG. 8 is a diagram explaining posture estimation according to a modification of the embodiment.
  • the posture of the subject 11 is estimated using a sensor module 207 including a position sensor 207a and an electric potential sensor 207b.
  • a plurality of sensor modules 207 are attached to the subject 11 here, but the number of sensor modules 207 attached to the subject 11 is not particularly limited. Only one sensor module 207 may be attached to the subject 11 .
  • the mounting style of the sensor module 207 is not particularly limited, and any style may be used as long as the position of a predetermined body part of the subject 11 can be measured.
  • the subject 11 is equipped with a plurality of sensor modules 207 by wearing a costume to which a plurality of sensor modules 207 are attached.
  • the sensor module 207 is a device that is attached to a predetermined body part of the subject 11 and outputs information indicating the result of detection or measurement in conjunction with the predetermined body part. Specifically, the sensor module 207 outputs the position sensor 207a that outputs the position information regarding the spatial position of the predetermined body part of the subject 11, and the potential information that indicates the potential at the predetermined body part of the subject 11. It has a potential sensor 207b. Although the figure shows the sensor module 207 having both the position sensor 207a and the potential sensor 207b, the potential sensor 207b is not essential if the sensor module 207 has the position sensor 207a.
  • the position sensor 207a in such a sensor module 207 is an example of an information output device that outputs position information as information relating to the position of the body part of the subject 11. Therefore, the information to be output is positional information, and is information including relative or absolute positions of predetermined body parts of the subject 11 . Also, the information to be output may include, for example, potential information.
  • the potential information is information including the value of potential measured at a predetermined body part of the subject 11 . Position information and potential information will be described in detail below together with the position sensor 207a and the potential sensor 207b.
  • the position sensor 207a detects a spatial relative position or an absolute position of a predetermined body part of the subject 11 to which the sensor module 207 is attached, and outputs information on the spatial position of the predetermined body part as a detection result. It is a vessel.
  • the information about the spatial position includes information that can identify the position of the body part in the space as described above and information that can identify the change in the position of the body part due to body movement.
  • the information about the spatial position includes information indicating the positions of the joints and the skeleton in space and changes in the positions.
  • the position sensor 207a is configured by combining various sensors such as an acceleration sensor, an angular velocity sensor, a geomagnetic sensor, and a range sensor. Since the position information output by the position sensor 207a can approximate the spatial position of a predetermined body part of the subject 11, the posture of the subject 11 can be estimated from the spatial position of the predetermined body part.
  • the electric potential sensor 207b is a detector that measures the electric potential at a predetermined body part of the subject 11 to which the sensor module 207 is worn and outputs information indicating the electric potential of the predetermined body part, which is the measurement result.
  • the potential sensor 207b is a measuring instrument that has a plurality of electrodes and measures a potential generated between the plurality of electrodes using an electrometer.
  • the potential information output by the potential sensor indicates the potential generated at a predetermined body part of the subject 11, and since the potential corresponds to the action potential of the muscle at the predetermined body part, the activity of the predetermined body part is detected. It is possible to improve the estimation accuracy of the posture of the subject 11 estimated from the potential or the like.
  • the fatigue estimation system in this modified example estimates the degree of fatigue of the subject 11 using the posture of the subject 11 estimated as described above. It should be noted that the processing after estimating the posture of the subject 11 is the same as in the above-described embodiment, and thus the description thereof is omitted.
  • the information output device is attached to a predetermined body part of the subject 11, and outputs position information about the spatial position of the predetermined body part as information about the position of the body part of the subject 11.
  • the position sensor 207a outputs, and the estimation apparatus 100 estimates the posture of the subject 11 based on the position information output from the position sensor 207a.
  • the fatigue level of the subject 11 can be estimated using the position information output by the position sensor 207a.
  • the posture of the subject 11 estimated from the output information is used.
  • the accumulation of fatigue caused by maintaining a constant static posture is quantified as the degree of fatigue based on the duration of time elapsed in the static posture in which the posture of the subject 11 is static.
  • the degree of fatigue of the subject 11 is calculated in consideration of the duration of the stationary posture. It is possible to estimate the degree of fatigue of the subject 11 in a stationary posture with less burden and with higher accuracy.
  • the increasing function and decreasing function are described as linear functions, but the present invention is not limited to this.
  • the increasing function may be a curvilinear function as long as the fatigue level increases with time.
  • the decreasing function may be a curvilinear function as long as it is a function that decreases the degree of fatigue over time.
  • the estimation device described above uses the load on muscles, the load on joints, and the blood flow estimated from the posture of the subject to estimate the degree of fatigue of the subject. As described above, it is also possible to correct the estimated value using the value measured using the measuring device to achieve more accurate estimation of the degree of fatigue. Specifically, the estimating device acquires a measured value corresponding to the estimated value, which is a measured value based on the measurement result of measuring the subject by the measuring device.
  • the detection device is, for example, an electromyograph, a muscle hardness meter, a pressure gauge, a near-infrared spectrometer, etc., and obtains measured values regarding the amount of load on muscles, the amount of load on joints, and the blood flow by measurement. can be done.
  • an electromyograph can estimate muscle movement corresponding to the potential based on the potential measured by potential measurement. That is, a value obtained by estimating the muscle movement can be obtained as a measurement value. Since the value obtained by estimating the movement of the muscle can be converted into the amount of load on the muscle, the estimated value of the amount of load on the muscle can be corrected by the measured value.
  • the correction here is, for example, taking the average value of the estimated value and the measured value, selecting one of the estimated value and the measured value, and applying the estimated value to the correlation function between the estimated value and the measured value. and so on.
  • a muscle hardness meter can estimate muscle hardness from the stress when pressure is applied to the muscle. Since the estimated muscle hardness value can be converted into the amount of load on the muscle, it can be used to correct the estimated value in the same manner as described above.
  • the pressure gauge can obtain a measured value of what kind of pressure is applied to the body part of the subject. Such pressure parameters can be input into the musculoskeletal model. By inputting additional parameters such as pressure, the estimation accuracy of the musculoskeletal model is improved, and the estimated value estimated using the musculoskeletal model can be corrected with higher accuracy.
  • a near-infrared spectrometer can obtain spectroscopic measurement values of the subject's blood flow.
  • the estimated value may be corrected by combining the blood flow rate measured by the infrared spectrometer.
  • the measured blood flow may be used when the estimated blood flow has low reliability.
  • the fatigue estimation system described in the above embodiment may be used to configure a fatigue factor identification system that identifies the subject's fatigue factors.
  • Conventional devices or systems for estimating the degree of fatigue as "degree of stiff shoulder” and “degree of low back pain” use muscles and joints (that is, factors It was difficult to identify the posture that Therefore, by using the fatigue estimation system according to the present disclosure, the above problem can be addressed.
  • body parts where fatigue is likely to accumulate are identified as fatigue factor parts in the static posture taken by the subject.
  • the fatigue factor identification system may simply identify the fatigue factor part in one static posture taken by the subject, and the estimated amount in the fatigue factor part most among the plurality of static postures taken by the subject You may also identify the fatigue factor posture with many
  • a recommended posture that replaces the specified fatigue-causing posture may be presented, and a fatigue degree recovery operation using a recovery device may be performed on the fatigue-causing portion in the fatigue-causing posture.
  • the fatigue factor identification system includes the fatigue estimation system described in the above embodiment and a storage device for storing information on the estimated degree of fatigue.
  • a storage device may be implemented using, for example, a semiconductor memory or the like, and each main storage unit or the like constituting the fatigue estimation system may be used. good too.
  • the present disclosure may be implemented as a fatigue estimation method executed by a fatigue estimation system or an estimation device.
  • the present disclosure may be implemented as a program for causing a computer to execute such a fatigue estimation method, or may be implemented as a computer-readable non-temporary recording medium in which such a program is recorded. .
  • REFERENCE SIGNS LIST 11 subject 11a rigid body link model 11c musculoskeletal model 12 chair 13 desk 13a desk surface 100 estimation device (fatigue estimation device) 101 first acquisition unit (position acquisition unit) 102 second acquisition unit 103 third acquisition unit 104 fourth acquisition unit (subjective acquisition unit, personal information acquisition unit) 105 posture estimation unit 106 first calculation unit 107 second calculation unit 108 fatigue estimation unit 109 output unit 110 instruction unit 200 fatigue estimation system 201 imaging device (information output device) 202 clock device 203 pressure sensor 204 reception device 205 display device (presentation device) 206 recovery device 207 sensor module 207a position sensor 207b potential sensor

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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002224072A (ja) * 2001-02-02 2002-08-13 Mazda Motor Corp 筋疲労評価装置、筋疲労評価方法並びに当該方法を実行するコンピュータプログラム並びに当該コンピュータプログラムを格納した記憶媒体
JP2008023127A (ja) * 2006-07-21 2008-02-07 Sharp Corp 生体情報推定装置及びそれを搭載した電子機器
JP2016538898A (ja) * 2013-10-09 2016-12-15 レスメッド センサー テクノロジーズ リミテッド 疲労モニタリング及び管理システム
WO2018003221A1 (ja) * 2016-07-01 2018-01-04 ソニー株式会社 情報処理装置、情報処理方法及びプログラム
JP2018025517A (ja) * 2016-08-12 2018-02-15 セイコーエプソン株式会社 情報出力システム、情報出力方法、及び情報出力プログラム
CN109528205A (zh) * 2018-11-15 2019-03-29 歌尔科技有限公司 一种提示方法、装置、头戴设备及计算机可读存储介质
JP2021043480A (ja) * 2019-09-06 2021-03-18 株式会社日立製作所 仮眠補助システム、および、仮眠補助用プログラム
WO2021112096A1 (ja) * 2019-12-06 2021-06-10 パナソニックＩｐマネジメント株式会社 疲労推定システム、推定装置、及び疲労推定方法
WO2021241348A1 (ja) * 2020-05-28 2021-12-02 パナソニックＩｐマネジメント株式会社 疲労推定システム、疲労推定方法、及び、プログラム

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002224072A (ja) * 2001-02-02 2002-08-13 Mazda Motor Corp 筋疲労評価装置、筋疲労評価方法並びに当該方法を実行するコンピュータプログラム並びに当該コンピュータプログラムを格納した記憶媒体
JP2008023127A (ja) * 2006-07-21 2008-02-07 Sharp Corp 生体情報推定装置及びそれを搭載した電子機器
JP2016538898A (ja) * 2013-10-09 2016-12-15 レスメッド センサー テクノロジーズ リミテッド 疲労モニタリング及び管理システム
WO2018003221A1 (ja) * 2016-07-01 2018-01-04 ソニー株式会社 情報処理装置、情報処理方法及びプログラム
JP2018025517A (ja) * 2016-08-12 2018-02-15 セイコーエプソン株式会社 情報出力システム、情報出力方法、及び情報出力プログラム
CN109528205A (zh) * 2018-11-15 2019-03-29 歌尔科技有限公司 一种提示方法、装置、头戴设备及计算机可读存储介质
JP2021043480A (ja) * 2019-09-06 2021-03-18 株式会社日立製作所 仮眠補助システム、および、仮眠補助用プログラム
WO2021112096A1 (ja) * 2019-12-06 2021-06-10 パナソニックＩｐマネジメント株式会社 疲労推定システム、推定装置、及び疲労推定方法
WO2021241348A1 (ja) * 2020-05-28 2021-12-02 パナソニックＩｐマネジメント株式会社 疲労推定システム、疲労推定方法、及び、プログラム

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