JP6946622B2 - Stress judgment device, stress judgment method, and stress judgment program - Google Patents

Description

The present invention relates to, for example, a stress determination device for estimating chronic stress related to a measurement target.

Patent Document 1 discloses a stress state estimation device that estimates a stress state in a subject based on body movement data measured with respect to the subject. The stress state estimation device measures the body movement of the subject and creates measurement information representing the measured body movement. The stress state estimation device calculates a feature amount representing a feature related to measurement information, and estimates the stress state by applying a relationship model representing the relationship between the feature amount and the stress state to the calculated feature amount. do. When the stress state actually felt by the subject is input with respect to the measurement information, the stress state estimation device recursively calculates the relationship model based on the input stress state.

Patent Document 2 discloses a measuring device that estimates the level of psychological stress based on cardiovascular signals measured with respect to a subject. The measuring device calculates the standard deviation of the RR interval in the cardiovascular signal, and calculates the feature amount representing the feature related to the calculated standard deviation. The measuring device estimates the level of psychological stress according to the magnitude of the calculated feature value.

Japanese Unexamined Patent Publication No. 2003-290176 Special Table 2016-50016

However, it is difficult to accurately estimate the future chronic stress of the measurement target by using either of the devices disclosed in Patent Document 1 and Patent Document 2. The reason for this is that both Patent Document 1 and Patent Document 2 determine the chronic stress that the measurement target is currently receiving.

Therefore, one of the objects of the present invention is to provide a stress determination device or the like capable of estimating the degree of chronic stress in the future.

In order to achieve the above-mentioned object, in one aspect of the present invention, the stress determination device is used.
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and the stress information that represents the degree of stress when the psychological burden is received during the first period Stored chronic stress information storage means and
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the psychological burden estimation means for calculating the degree of the psychological burden with respect to the first measurement target, and the psychological burden estimation means.
A psychological burden accumulating means for calculating cumulative burden information representing a numerical value obtained by accumulating the degree of the psychological burden calculated based on the measurement information measured in the second period with respect to the first measurement target.
By applying the second chronic stress estimation model to the cumulative burden information, a second chronic stress estimation means for estimating the degree of stress received by the first measurement target during the second period is provided.

Further, as another viewpoint of the present invention, the stress determination method is
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and the stress information that represents the degree of stress when the psychological burden is received during the first period Using an information processing device that can read and write to the stored chronic stress information storage means,
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the degree of the psychological burden on the first measurement target was calculated, and the calculation was performed based on the measurement information measured in the second period with respect to the first measurement target. By calculating the cumulative burden information representing the cumulative numerical value of the degree of the psychological burden and applying the second chronic stress estimation model to the cumulative burden information, the first measurement target is measured in the second period. Estimate the degree of stress that is received.

In addition, as another viewpoint of the present invention, the stress determination program is
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and stress information that represents the degree of stress when the psychological burden is received during the first period A computer that can read and write to the stored chronic stress information storage means,
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the psychological burden estimation function for calculating the degree of the psychological burden on the first measurement target and the psychological burden estimation function
A psychological burden accumulation function that calculates cumulative burden information representing a numerical value that accumulates the degree of the psychological burden calculated based on the measurement information measured in the second period with respect to the first measurement target, and a psychological burden accumulation function.
By applying the second chronic stress estimation model to the cumulative burden information, a second chronic stress estimation function for estimating the degree of stress received by the first measurement target during the second period is realized on the computer. Let me.

Further, the same purpose is realized by a computer-readable recording medium for recording the program.

According to the stress determination device and the like according to the present invention, the degree of future chronic stress can be estimated.

It is a block diagram which shows the structure which the stress estimation system which concerns on 1st Embodiment of this invention has. It is a flowchart which shows the flow of the learning process in the stress estimation system which concerns on 1st Embodiment. It is a flowchart which shows the flow of the estimation process in the stress estimation system which concerns on 1st Embodiment. It is a figure which shows an example of the structure which a pressure distribution sensor has, and an example of the place where the pressure distribution sensor is installed. It is a figure which shows an example of the structure which a wristband-shaped heart rate sensor has. It is a figure which conceptually represents an example of the psychological burden training information stored in the psychological burden information storage part. It is a figure which conceptually represents an example of the 1st chronic stress training information stored in the 1st chronic stress information storage part. It is a figure which conceptually represents an example of the 2nd chronic stress estimation model stored in the 2nd chronic stress information storage part. It is a block diagram which shows the structure which the stress estimation system which concerns on 2nd Embodiment of this invention has. It is a flowchart which shows the flow of processing in the stress estimation system which concerns on 2nd Embodiment. It is a figure which conceptually represents an example of schedule information. It is a figure which conceptually represents an example of the item burden information stored in the item burden information storage part. It is a block diagram which shows the structure which the stress estimation apparatus which concerns on 3rd Embodiment of this invention has. It is a flowchart which shows the flow of processing in the stress estimation apparatus which concerns on 3rd Embodiment. It is a block diagram which shows the structure which the stress estimation apparatus which concerns on 4th Embodiment of this invention has. It is a flowchart which shows the flow of processing in the stress estimation apparatus which concerns on 4th Embodiment. It is a block diagram which shows schematic the hardware configuration example of the calculation processing apparatus which can realize the stress estimation apparatus which concerns on each embodiment of this invention.

For the purpose of facilitating the understanding of the present invention, the techniques used in the present invention and the problems to be solved by the present invention will be described in detail.

An example of a technique for estimating an acute stress will be described. Hereinafter, the degree of psychological burden or the presence or absence of psychological burden will be collectively referred to as "psychological burden".

The psychological burden on the measurement target (for example, the subject, hereinafter simply referred to as “target”) is estimated based on, for example, the value of the feature amount representing the characteristics related to the posture of the measurement target. The feature quantity representing the feature related to the posture represents, for example, the degree to which the center of pressure in the pressure distribution generated according to the posture of the measurement target (hereinafter, the center of pressure is referred to as "pressure center") varies with time. The degree of variation (for example, the standard deviation SD, which will be described later with reference to Equation 10 and the like). The psychological burden on the measurement target is estimated, for example, by applying a machine learning technique such as a self-organizing map to a numerical value representing a temporal transition of the degree of variation (degree) of the pressure center.

The psychological burden on the measurement target is determined, for example, based on the value of the feature amount for a specific frequency band in the heartbeat of the measurement target. When the psychological burden on the measurement target is determined based on the ratio of the specific frequency band, the psychological burden can be estimated while eliminating individual differences between the measurement targets. The method of measuring the heartbeat includes, for example, a method of directly measuring the pulse wave of the measurement target using a heartbeat sensor, or a method of measuring the heartbeat of the measurement target using a pressure sensor installed in a chair on which the measurement target sits. There are methods for measuring.

The psychological burden (stress) on the measurement target is the electrical skin reaction (GSR) measured from the measurement target, brain waves, facial expressions, eye movements, pupil diameter, number of blinks, voice tone, speaking style, accelerometer. It can be estimated based on the value of the feature amount representing the feature such as the movement, gesture, and behavior of the body of the measurement target measured by using.

Stress in a measurement object is related to the balance between sympathetic nerve activity in the measurement object and parasympathetic nerve activity in the measurement object. The balance between sympathetic and parasympathetic activity is related to the ratio of low frequency components (LF) to high frequency components (HF) in the pulse wave measured from the object being measured.

The Mayer wave detected in relation to the pulse wave represents a phenomenon in which systolic blood pressure fluctuates in a cycle of about 10 seconds (that is, a low frequency component of about 0.1 hertz). The stimulation generated by the Mayer wave reaches the cardiovascular center via baroreceptors such as the carotid sinus, and then suppresses the sinus node via the efferent tract (cardiac vagus nerve system or sympathetic nervous system). Therefore, the Mayer wave reflects the activity of the cardiac vagus nerve system (cardiac parasympathetic nervous system) and the activity of the cardiovascular sympathetic nervous system. The high-frequency component also reflects the activity of the cardiac vagus nerve system (cardiac parasympathetic nervous system). The reason for this is that the extension stimulus of the pulmonary pressure receptor during exhalation suppresses the cardiac vagus nerve via the cardiovascular center, and the respiratory stimulus with a cycle of 9 times per minute (that is, 0.15 hertz) or more is the cardiac vagus nerve. This is because it is transmitted to the sinus node via.

From the above facts, the degree of sympathetic activity is determined by the integrated value of the power spectral density of the low frequency component (0.05 Hz to 0.15 Hz) of the heartbeat and the high frequency component (0.15 Hz to 0.45 Hz). ) Divided by the integrated value of the power spectral density (that is, the ratio to LF / HF). The degree of parasympathetic activity is expressed using the integral value of the power spectral density of the high frequency component (0.15 Hz to 0.45 Hz).

Further, the fluctuation of the heart rate of the measurement target (SDNN) also decreases when the psychological burden of the measurement target increases, and can be a characteristic amount of the psychological burden.

The psychological burden on the measurement target is the pulse wave measured from the measurement target, electrical skin reaction (GSR), brain wave, facial expression, eye movement, pupil diameter, number of blinks, voice tone, speaking style, accelerometer. It can be estimated based on the value of the feature amount representing the feature such as the movement, gesture, and behavior of the body of the measurement target measured by using.

Next, an example of a technique for estimating chronic stress will be described.

Chronic stress in a measurement target (hereinafter referred to as “chronic stress”) is measured by a questionnaire survey or the like continuously conducted on the measurement target. However, since the questionnaire survey is an extra task for the measurement target, it may be one of the causes of giving a psychological burden or chronic stress to the measurement target.

Chronic in the measurement target, for example, based on the value of the correlation dimension D2 (described later with reference to Equation 9 and the like) regarding the time series data representing the heartbeat of the measurement target without conducting a questionnaire survey on the measurement target. Stress can also be estimated. In other words, the correlation dimension D2 is an example of a feature amount that may be able to measure chronic stress in the measurement target while reducing the psychological burden and chronic stress on the measurement target. As a method of measuring the heartbeat of the measurement target, for example, a method of directly measuring the pulse wave using a heartbeat sensor or a pressure sensor installed in a chair on which the measurement target is sitting is used to measure the heartbeat of the measurement target. There are methods such as indirect measurement. However, there are individual differences between the psychological burden given from the outside of the measurement target and the influence of the psychological burden on the chronic stress of the measurement target.

In summary, the measurement target is based on measurement information such as body movement data of the measurement target estimated from the pressure distribution measured using the pressure distribution sensor and biological information data of the measurement target measured using the biometric information sensor. Chronic stress or accumulation of psychological burden can be estimated. However, there are individual differences in the relationship between the accumulation of psychological burden and chronic stress. Therefore, for the purpose of accurately predicting chronic stress based on the accumulation of psychological burden, it is necessary to predict chronic stress while taking the individual differences into consideration.

In a subject, which is an example of a measurement target, chronic stress results from the accumulation of psychological burden. However, as for whether or not the psychological burden causes chronic stress, as a result of individual differences (individual differences), there are also individual differences in the degree to which chronic stress causes mental illness in the measurement target.

Based on the chronic stress in the measurement target, it is possible to urge the measurement target to take a vacation / rest. When the chronic stress in the measurement target becomes high to some extent, the measurement target is urged to reduce the stress such as urging a vacation (or rest). However, even if the measurement target is urged to take a rest, it is not always possible to take a rest at the timing when the rest is urged. The subject continues to feel chronic stress when he / she is unable to rest. In this case, the inability to take the urged rest while being urged to rest may itself cause chronic stress for the measurement subject.

In addition, chronic stress is constantly monitored, the degree of increase in chronic stress is estimated, and the effect of each schedule experienced by the measurement target on the increase in chronic stress is recorded, and the psychological load is recorded. It is difficult to adjust the schedule using the relationship between each of these schedules and the degree of increase in chronic stress without measuring. This is because chronic stress is derived not only from the psychological load caused by the work given to the measurement target, but also from all psychological loads including the past memories recalled by the measurement target. Therefore, statistical processing (linear regression, etc. if the relationship between chronic stress and psychological load is used) is performed between the psychological load and the content of the schedule, and between the chronic stress and the psychological load, respectively. ) Needs to be clarified, and if the relationship between the contents of the schedule and chronic stress is clarified by statistical processing, the accuracy will be lost.

It is possible to encourage the subject to rest based on the psychological burden. However, in the measurement target, even if the person experiences a psychological burden to some extent, the chronic stress may remain at a very low level. Therefore, when a rest is urged based on the psychological burden, the reminder is performed. May be too early for the object to be measured. Similarly, the timing at which rest is urged based on psychological burden has increased to the extent that chronic stress causes mental illness, which may be too late for the subject to be measured. Therefore, in order to reduce the chronic stress in the measurement target, it is necessary to urge the measurement target to reduce the stress at an appropriate timing.

For example, according to a technique for predicting chronic stress based on the accumulation of psychological burden on a measurement target that is at risk of leading to chronic stress as a result of the accumulation of psychological burden due to work, planned vacation (or rest) Can give advice on. However, as described above, there are individual differences between the measurement targets as to whether or not the accumulation of psychological burden on the measurement target leads to chronic stress. For example, the individual difference is the difference in the tolerance of each measurement target to stress, the difference in whether or not the measurement target has a habit of reducing chronic stress, and the difference in the degree of chronic stress reduced according to the habit. And so on. In addition, the habit of reducing chronic stress also changes for a single measurement object.

However, although the techniques disclosed in Patent Document 1 and Patent Document 2 can estimate the chronic stress at the time of measurement, it cannot estimate how the chronic stress changes after the time of measurement. ..

The inventor has found the above-mentioned problems and has derived means for solving the problems. Hereinafter, a system according to an embodiment of the present invention that can solve such a problem will be described in detail with reference to the drawings.

<First Embodiment>
The configuration of the stress estimation (determination) system 101 according to the first embodiment of the present invention will be described in detail with reference to FIG. FIG. 1 is a block diagram showing a configuration of the stress estimation system 101 according to the first embodiment of the present invention.

The stress estimation system 101 according to the first embodiment of the present invention includes a stress estimation (determination) device 102, a measurement unit 103, and an output device 104.

The stress estimation device 102 according to the first embodiment includes an input unit 105, a first chronic stress estimation unit 106, a psychological burden estimation unit 107, a psychological burden accumulation unit 108, and a second chronic stress estimation unit 109. It has a chronic stress determination unit 110, a first chronic stress learning unit 111, a psychological burden learning unit 112, and a second chronic stress learning unit 113. The stress estimation device 102 may further include a first chronic stress information storage unit 114, a psychological burden information storage unit 115, and a second chronic stress information storage unit 116.

The measuring unit 103 measures information about a measurement target such as a subject (hereinafter, referred to as “measurement information”). The measuring unit 103 is, for example, a pressure distribution sensor (described later with reference to FIG. 4), an acceleration sensor, a skin surface conductivity sensor, a pulse wave sensor, and a biometric information sensor. The measuring unit 103 is a wristband-shaped wearable device having at least one of a pulse wave sensor, an acceleration sensor, a skin surface conductivity sensor, a heartbeat sensor, and the like (described later with reference to FIG. 5). It may be. Further, the measuring unit 103 need only have at least one sensor capable of measuring information about the measurement target, and is not limited to the above-mentioned example. The measurement information measured by the measurement unit 103 is information that may be related to the psychological burden on the measurement target or chronic stress. Here, a sensor which is an example of the measuring unit 103 will be described.

The pressure distribution sensor will be described with reference to FIG. FIG. 4 is a diagram showing an example of the structure of the pressure distribution sensor and an example of the place where the pressure distribution sensor is installed.

The pressure distribution sensor (pressure distribution sensor 125 to pressure distribution sensor 127) is a pressure detection cell (for example, pressure detection cell 121, pressure detection cell) that measures pressure in a predetermined area at a plurality of measurement points in a predetermined area. 122). The pressure distribution sensor may estimate, for example, the heartbeat of the measurement target to be measured or the movement of the measurement target based on the change in the measured pressure.

For convenience of explanation, the pressure measured at a plurality of measurement points in a predetermined region is referred to as "pressure distribution". Further, measuring the pressure at a plurality of measurement points in a predetermined region is referred to as "measuring the pressure distribution". That is, the pressure distribution sensor measures the pressure distribution.

The pressure distribution sensor is installed, for example, on the seat surface 124 of the chair on which the measurement target sits (the backrest 123 of the chair, the front of the chair, or the like. The pressure distribution sensor 127 installed in front of the chair is, for example, The pressure distribution on the sole of the foot of the measurement target sitting on the chair is measured. The pressure distribution sensor 126 installed on the seat surface 124 of the chair is, for example, the pressure distribution on the buttocks of the measurement target, which is often worked in the sitting position. The pressure distribution sensor 125 installed on the backrest 123 of the chair can measure, for example, the pressure on the back of the object to be measured.

Heart rate can also be measured by a pressure distribution sensor. In this case, in addition to the PPG method described later, there is also a method of estimating the heartbeat based on a minute pressure change on the skin surface caused by the movement of blood vessels due to a pulse wave such as a wrist. As illustrated in FIG. 5, such a sensor may be a wristband-shaped heart rate sensor 131 worn on the wrist or the like to be measured. FIG. 5 is a diagram showing an example of the structure of the wristband-shaped heart rate sensor 131.

When the pressure distribution sensor is the pressure distribution sensor 126 installed on the seat surface 124 of the chair and the wristband-shaped heartbeat sensor 131, the heartbeat sensor 131 measures the movement of the measurement target more accurately. be able to.

The accelerometer measures the acceleration associated with the movement of the object to be measured. The acceleration sensor is attached to, for example, the wrist of a measurement target that often moves, and measures the acceleration in the movement of the measurement target. Acceleration represents information that may be related to the psychological burden or chronic stress in the object being measured.

The skin surface conductivity sensor is mounted on the surface of the skin to be measured, and the conductivity is measured at the mounted portion. Conductivity represents information that may be related to the psychological burden and chronic stress of the object being measured.

To measure the heartbeat, a sensor attached to the end of the body such as a limb (PPG method, a method of estimating the heartbeat based on the pressure change on the skin surface as described above, or a method of detecting acceleration derived from a pulse wave. Etc.), the method of estimating from the pulse wave measured from, the seat surface 124 of the chair or the like on which the measurement target sits, the seat surface pressure distribution sensor installed on the backrest, etc., the minute vibration derived from the heartbeat of the subject's body is detected. From the method of detecting and estimating the heartbeat, the seat surface 124 of the chair on which the measurement target sits, the seat surface pressure distribution sensor installed on the backrest, etc., the vibration due to the pulse wave at the end of the body of the subject is estimated, and further. The above-mentioned method of estimating the heartbeat, the method of directly acquiring the myocardial electrocardiogram (so-called "electrocardiogram") with an electrocardiograph attached to the chest (near the heart) of the measurement target, and the electric signals simultaneously acquired from the fingers of both hands, etc. Methods for estimating the myocardial myocardial behavior of the myocardium, etc., but are not limited to these.

The configuration of the measuring unit 103 may be determined according to the situation regarding the measurement target. When the measurement target is unfamiliar with wearing a wearable device, the measurement target is a wristband-shaped sensor (a wristband by the pressure distribution sensor illustrated in FIG. 5, other acceleration sensor, skin surface conductivity sensor, etc. Wearing a wristband such as a PPG type pulse wave sensor) may be a psychological burden. When the measurement target often performs work in a sitting position such as operating a computer or driving a car, the measurement unit 103 is, for example, a pressure distribution installed on the seat surface 124 of the chair on which the measurement target sits. It has a sensor 126 (exemplified in FIG. 4). Further, when the measurement target often moves and is accustomed to wearing a wearable device, the measuring unit 103 may be, for example, a wristband-shaped wearable device (list by the pressure distribution sensor illustrated in FIG. 5). It has a band, other accelerometers, skin surface conductivity sensor, wristband such as PPG type pulse wave sensor), and also has a pressure distribution sensor 126 (exemplified in FIG. 4) installed on the seat surface 124 of the chair. You may. When the measuring unit 103 has sensors installed at a plurality of places, according to the measuring unit 103, for example, even if some information cannot be measured, the measurement information that can be measured can be measured. Information that cannot be measured can be estimated based on.

The measurement unit 103 is not limited to the above-mentioned example, as long as it can acquire information that may be related to chronic stress in the measurement target or information that may be related to the psychological burden in the measurement target. ..

The stress estimation device 102 determines the degree of chronic stress in the measurement target and rest (or vacation) in the measurement target based on the measurement information measured with respect to the measurement target by the measurement unit 103 having the sensor as described above. ) Is estimated. The stress estimation device 102 only needs to be able to input the measurement information measured by the measurement unit 103, and can be realized by using, for example, a function of a general-purpose information processing device, a dedicated device, a mobile terminal, or the like. The stress estimation device 102 can be realized by using, for example, a computer used by the measurement target, software stored in a mobile terminal or the like, or the like.

The output device 104 outputs the rest timing, the degree of stress, etc. calculated by the stress estimation device 102. The output device 104 is, for example, a device such as a display or a speaker. The output device 104 is not limited to the above-mentioned example.

Next, the processing in the stress estimation system 101 according to the first embodiment of the present invention will be described in detail. The processing in the stress estimation system 101 is roughly classified into an estimation process for estimating chronic stress and a learning process for creating information (training information, estimation model, etc.) that is the basis of the estimation process. The learning process in the stress estimation system 101 according to the first embodiment will be described with reference to FIG. 2, and then the estimation process in the stress estimation system 101 according to the first embodiment will be described with reference to FIG. do. FIG. 2 is a flowchart showing the flow of learning processing in the stress estimation system 101 according to the first embodiment. FIG. 3 is a flowchart showing a flow of estimation processing in the stress estimation system 101 according to the first embodiment.

For convenience of explanation, the estimation process and the learning process will be described separately, but the stress estimation system 101 may execute the estimation process and the learning process in parallel or in pseudo-parallel. ..

In the learning process shown in FIG. 2, the input unit 105 inputs the measurement information measured by the measurement unit 103 (step S101). The measurement information represents information about the measurement target. The input unit 105 may store the input measurement information in the measurement information storage unit (not shown). The input unit 105 further inputs the degree of chronic stress or the degree of psychological burden acquired through a questionnaire survey or the like for the measurement target (step S102).

The psychological burden learning unit 112 calculates the value of the feature amount representing the feature of the measurement information with respect to the measurement information input by the input unit 105 according to a predetermined feature amount calculation procedure. The feature amount calculated according to the predetermined feature amount calculation procedure represents information that may be related to the psychological burden (for example, “standard deviation SD” described later with reference to Equation 10 and the like). The psychological burden learning unit 112 creates and creates psychological burden training information (described later with reference to FIG. 6) in which the calculated feature amount value and the input psychological burden are associated with each other (step S103). The psychological burden training information is stored in the psychological burden information storage unit 115.

The psychological burden learning unit 112 expresses the relationship between the feature amount and the psychological burden by arithmetically processing the created psychological burden training information (psychological burden teacher data) according to the procedure related to the machine learning technique. A psychological burden estimation model is created (step S104). The machine learning technique is, for example, a support vector machine, a regression tree, or the like. The value of the feature amount is calculated by applying the psychological burden estimation model to the value of the feature amount calculated according to a predetermined feature amount calculation procedure.

Create a psychological burden estimation model with higher estimation accuracy as the number of measurement targets increases (or the longer the measurement period for the measurement target, the more items are investigated in the questionnaire for the measurement target). Can be done. The psychological burden training information may be created according to, for example, a subject-independent method that does not depend only on a specific measurement target.

The first chronic stress learning unit 111 calculates the value of the feature amount representing the feature of the measurement information with respect to the measurement information input by the input unit 105 according to a predetermined feature amount calculation procedure. The feature amount calculated according to the predetermined feature amount calculation procedure represents information that may be related to chronic stress (for example, “correlation dimension D2” described later with reference to Equation 6 and the like). The first chronic stress learning unit 111 creates first chronic stress training information (described later with reference to FIG. 7) in which the created feature value and the degree of input chronic stress are associated with each other (step S105). ), The created first chronic stress training information is stored in the first chronic stress information storage unit 114.

The first chronic stress learning unit 111 performs arithmetic processing on the created first chronic stress training information (first chronic stress teacher data) according to the procedure related to the machine learning technique, thereby determining the value of the feature amount and the psychological burden. A first chronic stress estimation model representing the relationship between the two is created (step S106). The machine learning technique is, for example, a support vector machine, a regression tree, or the like. By applying the first chronic stress estimation model to the feature amount calculated according to the predetermined feature amount calculation procedure (for example, "correlation dimension D2"), the degree of chronic stress with respect to the value of the feature amount is calculated. NS.

Chronic stress in the measurement target can also be estimated according to the same procedure as the procedure for estimating the psychological burden. The measurement information that is the basis for estimating chronic stress is obtained by measuring information that may be related to chronic stress with a sensor. In addition, the larger the number of measurement targets (or the longer the measurement period for the measurement target, the more items are investigated in the questionnaire for the measurement target), the higher the estimation accuracy can be created. .. That is, the first chronic stress training information is created according to a measurement-independent method that does not depend only on a specific measurement target.

Next, the second chronic stress learning unit 113 describes a second chronic stress estimation model (described later with reference to FIG. 8) representing the relationship between the input degree of chronic stress and the input degree of psychological burden. ) Is created (step S107).

For convenience of explanation, the degree of psychological burden in a certain period is expressed as P (however, P ≧ 0), and the degree of chronic stress in the certain period is expressed as S (however, S ≧ 0). In this case, the second chronic stress learning unit 113 executes a second chronic stress estimation model “S = F (P)” representing the relationship between S and P, for example, a regression analysis on P and S. Calculate according to the procedure to be performed. Regression analysis represents, for example, a linear regression analysis in which "S = F (P)" is linear. That is, the second chronic stress learning unit 113 calculates a second chronic stress estimation model that can predict the degree of chronic stress based on the degree of psychological burden. The second chronic stress learning unit 113 is a second chronic stress estimation model based on the degree of the input chronic stress and the degree of the input psychological burden as the information is input to the input unit 105. May be updated. In this case, the second chronic stress learning unit 113 is based on the newly input degree of psychological burden and the degree of stress, and the second chronic stress estimation that is suitable for the newly added degree. The model "S = F (P)" is calculated.

For convenience of explanation, it is assumed that the standard deviation SD with respect to the pressure center represents the degree of psychological burden. In this case, the standard deviation SD is not exactly a value at a certain point on the time axis, but is a value of the body to be measured within a time interval (for example, 10 seconds, 1 minute, etc.) having a certain width. It is calculated from the variation due to the fluctuation of the pressure distribution center based on the movement. In this case, "t" of SD (t) is a representative point (start point, end point, center point, etc.) within the time interval. Further, it is assumed that the correlation dimension D2 relating to the heartbeat of the measurement target represents the degree of chronic stress. The t in D2 (t) is also the same as the “t” in SD (t) described above. Furthermore, it is assumed that the relationship between the degree of psychological burden and the degree of chronic stress is expressed using a linear correlation.

The psychological burden accumulated in a certain period (for convenience of explanation, _{it is assumed to be the period from timing Ti} to timing T _f ) is that the psychological burden at each timing within the period is accumulated for the certain period. Information. Therefore, according to the above assumption, the psychological burden accumulated in a certain period can be calculated, for example, as a value obtained by integrating the standard deviation SD in a certain period.

Under the above assumptions, there is a linear correlation between the standard deviation SD and the correlation dimension D2, as shown in Equation 1.

However, A and B represent constants.

Here, it is assumed that the standard deviation SD and the correlation dimension D2 are calculated for a plurality of periods as shown in Equation 2.

_{However, t i _1, t f _1} , t f _2, ···, t f _N represents the timing. f, i, and N represent natural numbers.

As shown in Equations 3 to 5, the constants A and B can be calculated as values that minimize the error related to the periods included in the plurality of periods as described above.

However, j represents a natural number.

For example, the second chronic stress learning unit 113 can calculate the constant A and the constant B according to the processing procedure in the least squares method.

In FIG. 8, the second chronic stress estimation model “S = F (P)” is a linear function, but is weighted by a higher-order function of a second order or higher, a function such as an exponential function, or a plurality of functions. It may be Japanese. That is, the second chronic stress estimation model is not limited to the above-mentioned example or the example shown in FIG.

The processes shown in steps S103 to S106 of FIG. 2 do not necessarily have to be executed in the order shown in FIG. 2, and may be executed in a different order, or may be executed in parallel (or pseudo). May be executed in parallel). That is, the processing order in the learning process is not limited to the example shown in FIG. Further, the first chronic stress learning unit 111 and the psychological burden learning unit 112 do not necessarily have to execute the processing according to the same machine learning technique. Further, the second chronic stress learning unit 113 created the second chronic stress estimation model based on the input degree of psychological burden, but the psychological burden accumulation unit 108 (or the psychological burden estimation unit 107) A second chronic stress estimation model may be created based on the calculated degree of psychological burden.

Further, the psychological burden learning unit 112 may create a second chronic stress estimation model for each measurement target. Alternatively, the psychological burden learning unit 112 creates a second chronic stress estimation model for the measurement target based on the degree of psychological burden calculated for the measurement information measured for an organism similar to the measurement target. May be good. In this case, since the second chronic stress estimation model is a model that reflects individual differences, the stress estimation device 102 according to the present embodiment estimates chronic stress with high accuracy regardless of individual differences. be able to.

In the stress estimation device 102 according to the present embodiment, a predetermined feature amount calculation procedure representing a procedure for calculating the feature amount value will be described.

When the measurement information is the heartbeat of the measurement target such as the measurement target, the feature amount calculated according to the predetermined feature amount calculation procedure is, for example, the correlation dimension D2 calculated for the heartbeat. Hereinafter, the procedure for calculating the feature amount that may be related to the degree of chronic stress such as the value of the correlation dimension D2 may be referred to as a “predetermined second feature amount calculation procedure”. Correlation dimension D2 represents an example of information that may be related to chronic stress with respect to the measurement target. The heartbeat is measured using, for example, a biometric information sensor, a pressure distribution sensor, or the like.

Correlation dimension D2 is a feature quantity in which a feature possessed by time-series data such as heartbeat measured in a certain period is expressed as a degree of fractal property (fractal structure) possessed by the time-series data. .. The correlation dimension D2 will be described with reference to an example in which the time series data represents a heartbeat.

It is assumed that ξ (t) represents the heartbeat at time t. Further, it is assumed that τ represents a time lag representing an interval between two times. Further, the period from a certain time t to the time (t + τ × (M-1)) (that is, the period from a certain time until the time lag of M times elapses) is represented as a time window. However, t ≧ 0, τ ≧ 0, and M ≧ 1.

If it is assumed as described above, the heart rate in the time window that originates the time i is as shown in Equation 6 can be expressed as an embedded vector v _i.

Here, the time lag τ is assumed to be the time at which the autocorrelation function R between a plurality of different embedded vectors first appears in the time t when the function differentiated with respect to time is the minimum, as shown in Equation 7. do.

The number of combinations between embedding vectors v _i and expressed as N _p. In this case, the radius r (However, r> 0) centered on the v _i thought sphere, the derivative of the ratio of the logarithm of the probability of v _j falls within the sphere, and the logarithm of the radius r, D2 (M; r) is defined as shown in Equation 8.

However, Θ (z) represents a step function (a function in which 1 is 1 when z ≧ 0 and 0 is 0 when z <0).

Correlation dimension D2 is defined as the limit value when M is sufficiently large and the radius r is sufficiently close to zero.

The feature amount may be any information that may be related to chronic stress, and is not limited to the correlation dimension D2 shown in Equation 9.

Next, a predetermined feature amount calculation procedure representing a procedure for calculating the feature amount value that may be related to the psychological burden will be described.

For the feature amount that may be related to the psychological burden, for example, among the pressure distributions measured by the pressure distribution sensor, the center position of the pressure distribution (hereinafter referred to as "pressure center") is temporally. It is a standard deviation SD indicating the degree of variation. An example of the procedure for calculating the standard deviation SD with respect to the pressure center will be described. Hereinafter, the procedure for calculating the feature amount that may be related to the degree of psychological burden such as the value of the standard deviation SD may be referred to as a “predetermined first feature amount calculation procedure”.

The pressure distribution sensor has, for example, a plurality of pressure detection cells (FIG. 4, for example, pressure detection cell 121, pressure detection cell 122) arranged in a grid pattern in a predetermined region. For convenience of explanation, it is assumed that Y (where Y is a natural number) pressure detection cells are arranged in the vertical direction and X (where X is a natural number) pressure detection cells are arranged in the pressure distribution sensor. Further, it is assumed that the position where the pressure detection cell measures the pressure is represented by the position (x, y). Further, the pressure measured at the position (x, y) (where x and y are real numbers) at time t (where t is a real number) is expressed as P (x, y, t) and measured by the pressure distribution sensor. With respect to the pressure distribution, the x-coordinate representing the pressure center at time t is represented by CoP_x (t), and the y-coordinate representing the center is represented by CoP_y (t).

According to Equation 10, the x-coordinate CoP_x (t) of the pressure center is calculated. That is,

According to Equation 11, the y-coordinate CoP_y (t) of the pressure center is calculated. That is,

With respect to the x-coordinate CoP_x (t) of the pressure center, the average in the period from timing 1 to timing T is calculated according to Equation 12. That is,

With respect to the y-coordinate CoP_y (t) of the pressure center, the average in the period from timing 1 to timing T is calculated according to Equation 13. That is,

With respect to the x-coordinate CoP_x (t) of the pressure center, the standard deviation in the period from timing 1 to timing T (that is, the degree to which the x-coordinate of the pressure center varies) is calculated according to Equation 14. That is,

With respect to the y-coordinate CoP_y (t) of the pressure center, the standard deviation in the period from timing 1 to timing T (that is, the degree to which the y-coordinate of the pressure center varies) is calculated according to Equation 15. That is,

The variability calculated according to Equation 14 and Equation 15 represents a feature amount that may be related to the psychological burden. For example, the feature amount indicating the degree to which the x-coordinate value of the pressure center varies and the degree to which the y-coordinate value of the pressure center varies may be calculated according to Equation 16. That is,

Therefore, the feature quantity represents an index that may be related to the psychological burden. The features that may be related to the psychological burden are not limited to the standard deviation of the pressure center described above.

Psychological burden training information will be described with reference to FIG. FIG. 6 is a diagram conceptually representing an example of psychological burden training information stored in the psychological burden information storage unit 115.

In the psychological burden training information, information that may be related to the degree of psychological burden (for example, a feature amount calculated according to Equation 16) is associated with the degree of psychological burden. The psychological burden training information may be further associated with the measurement information measured by the measurement unit 103 or the feature amount calculated based on the measurement information.

For example, in the psychological burden training information illustrated in FIG. 6, items 1 to 8 are associated with each other. That is,
○ (Item 1) Variation in the x-axis direction of the pressure center “2.5” (for example, calculated according to Equation 14),
○ (Item 2) Variation in the y-axis direction of the pressure center “3.8” (for example, calculated according to Equation 15),
○ (Item 3) Standard deviation SD “6.3” (for example, calculated according to Equation 16),
○ (Item 4) Acceleration “1.3”, (however, “g” in FIG. 6 represents an abbreviation for gravity),
○ (Item 5) Skin conductivity “5.0”, (however, “μS” in FIG. 6 represents microseconds),
○ (Item 6) Heart rate "60",
○ (Item 7) Skin temperature “35.5”, (however, “° C” in FIG. 6 represents Celsius degree (Mr. Se)),
○ (Item 8) Psychological burden "3.4".

This is the information shown in items 1 to 7 that may be related to the psychological burden, and the psychological burden in the case of items 1 to 7 is "3.4". Represents that. Further, the information shown in items 1 to 3 and item 6 represents a feature amount calculated based on the measurement information. The information shown in item 4, item 5, and item 7 represents the measurement information measured by the measuring unit 103.

The psychological burden training information does not necessarily include all the information shown in items 1 to 7. The psychological burden training information may include other items as long as it is information that may be related to the degree of psychological burden. That is, the psychological burden training information is not limited to the example shown in FIG.

The first chronic stress training information will be described with reference to FIG. 7. FIG. 7 is a diagram conceptually representing an example of the first chronic stress training information stored in the first chronic stress information storage unit 114.

In the first chronic stress training information, information that may be related to the degree of chronic stress (for example, a feature amount calculated according to Equation 9) is associated with the degree of chronic stress. The first chronic stress training information may be further associated with the measurement information measured by the measurement unit 103 or the feature amount calculated based on the measurement information.

For example, in the first chronic stress training information illustrated in FIG. 7, the correlation dimension “4.2” and the chronic stress “3.1” are associated with each other. This indicates that the degree of chronic stress was 3.1 when the correlation dimension calculated according to Equation 9 was 4.2.

The first chronic stress training information may include other items as long as it is information that may be related to the degree of chronic stress. That is, the first chronic stress training information is not limited to the example shown in FIG.

The second chronic stress estimation model will be described with reference to FIG. FIG. 8 is a diagram conceptually representing an example of the second chronic stress estimation model stored in the second chronic stress information storage unit 116.

In the second chronic stress information storage unit 116, for example, the second chronic stress estimation model “S = F (P)” calculated according to the formulas 1 to 5 is stored for each measurement target. For example, in the second chronic stress information storage unit 116 illustrated in FIG. 8, the second chronic stress estimation model calculated for the measurement target C and the second chronic stress estimation model calculated for the measurement target D are stored. Has been done.

In FIG. 8, the second chronic stress estimation model is stored in the second chronic stress information storage unit 116 as a graph in which the horizontal axis represents the degree of psychological burden and the vertical axis represents the degree of chronic stress. It does not necessarily have to be a graph, and the coefficient of the function represented by the graph or the information representing the function may be stored. That is, the second chronic stress estimation model is not limited to the above-mentioned example.

The second chronic stress learning unit 113 sets the procedure shown in Equations 3 to 5 with respect to the value of the feature amount calculated based on the increased measurement information and the degree of psychological burden when the measurement information increases. Therefore, the constant A and the constant B may be calculated. That is, the second chronic stress learning unit 113 may update the constant A and the constant B based on the psychological burden calculated with respect to the increased measurement information. When the second chronic stress learning unit 113 updates the second chronic stress estimation model, the second chronic stress estimation model reflects the degree of psychological burden related to more measurement information. As a result, the estimation accuracy based on the second chronic stress estimation model is improved as compared with the case where the updating process is not executed.

Next, the estimation process in the stress estimation system 101 according to the first embodiment will be described with reference to FIG.

The input unit 105 inputs the measurement information measured by the measurement unit 103 (step S111). The measurement information represents information about the measurement target. The input unit 105 may store the input measurement information in the measurement information storage unit (not shown).

The psychological burden estimation unit 107 calculates the value of the feature amount that may be related to the psychological burden by calculating the measurement information input by the input unit 105 according to a predetermined feature amount calculation procedure (). Step S112). The psychological burden estimation unit 107 calculates the value of the feature amount related to the measurement information according to the above-described processing with reference to the equations 6 to 16. In the psychological burden estimation unit 107, the information including at least one of the calculated feature amount value and the input measurement information is an item (for example, an item) in the psychological burden training information (exemplified in FIG. 6). Create information arranged in the order of items 1 to 7). The psychological burden estimation unit 107 applies the psychological burden estimation model representing the relationship between the above-mentioned information and the psychological burden to the created information, so that the burden estimation information indicating the degree of the psychological burden is expressed. Is created (step S113). The psychological burden estimation model is created by the psychological burden learning unit 112 as described with reference to FIG. The psychological burden estimation unit 107 stores the created burden estimation information in the psychological burden information storage unit 115.

The psychological burden accumulation unit 108 accumulates the degree of psychological burden measured in a predetermined period or the degree of psychological burden calculated based on the measurement information measured in a predetermined period (step S114). The psychological burden accumulation unit 108 accumulates the degree of psychological burden by, for example, performing an integral operation as shown in Equation 1 with respect to the degree of psychological burden.

The period during which the psychological burden accumulation unit 108 calculates the cumulative value does not necessarily have to be before the timing for calculating the cumulative value, and may be the timing after the cumulative value is calculated. .. In this case, the psychological burden accumulation unit 108 relates to the degree of the psychological burden according to the above-mentioned processing based on the estimated value of the degree of the psychological burden in the period including the timing after the cumulative value is calculated. Calculate the cumulative value.

The psychological burden accumulation unit 108 may estimate the degree of psychological burden at the time when the measurement target is expected to be exposed to the psychological burden factor (for example, working hours). In this case, the working hours do not have to represent the hours actually worked, but represent the hours scheduled to be worked. When the working time is a scheduled time representing the scheduled time to work, the psychological burden accumulation unit 108 sets the degree of the psychological burden at the scheduled time, for example, according to the degree of the predetermined psychological burden. Calculate the value. Further, as shown in the second embodiment, the psychological burden accumulation unit 108 calculates the cumulative value of the degree of psychological burden based on the schedule information including the time when the measurement target is scheduled to be exposed to the psychological burden factor. It may be calculated.

Further, when the time when the measurement target is exposed to the stress factor and the cumulative value of the psychological burden related to the measurement target have a linear relationship, the psychological burden accumulation unit 108 performs the psychological burden according to the linear relationship. The degree of may be calculated. That is, the processing in the psychological burden accumulation unit 108 is not limited to the above-mentioned example.

The second chronic stress estimation unit 109 represents a relationship between the cumulative value of the degree of psychological burden and the degree of chronic stress in the cumulative value calculated by the psychological burden accumulation unit 108 (for example, a second chronic stress estimation model (for example). , A linear correlation as described with reference to Equation 1) is applied to calculate the degree of chronic stress (step S115). The second chronic stress estimation unit 109 may store the calculated degree of chronic stress in the second chronic stress information storage unit 116.

The chronic stress determination unit 110 calculates whether or not the degree of chronic stress calculated by the second chronic stress estimation unit 109 satisfies a predetermined condition (step S116). The predetermined condition is, for example, whether the degree of the chronic stress is equal to or higher than a predetermined threshold value. The predetermined threshold value may be a threshold value capable of determining whether or not there is a risk of suffering from a mental illness, or may be a value smaller than the threshold value.

When the degree of chronic stress satisfies a predetermined condition, the chronic stress determination unit 110 determines that the stress is high. When the degree of chronic stress satisfies a predetermined condition (YES in step S116), the chronic stress determination unit 110 creates, for example, a message advising to reduce the stress, and outputs the created message. Output to 104 (step S117). If the degree of chronic stress does not meet the predetermined condition (NO in step S116), the process shown in step S117 is not executed.

According to the chronic stress determination unit 110, when the predetermined threshold value is smaller than the threshold value at which it can be determined whether or not there is a risk of suffering from a mental illness, before the risk of suffering from a mental illness increases. In addition, a message indicating that the chronic stress is high can be presented in advance to the measurement target. The threshold for the risk of suffering from a mental illness is determined, for example, in the results of a questionnaire survey in which the psychological stress measurement effect is guaranteed, which is shown on the homepage (http://kokoro.mhlw.go.jp/check). The risk represents a level included in the level at which the risk of suffering from a mental illness is determined (in the above-mentioned specific example, the "need attention zone"). However, the predetermined threshold is not limited to this example. In addition, the message may be, for example, a content indicating that chronic stress is high.

Next, the effect of the stress estimation device 102 according to the first embodiment will be described.

According to the stress estimation device 102 according to the first embodiment of the present invention, the degree of chronic stress is estimated with high accuracy not only at the measurement timing at which the measurement target is measured but also at a timing different from the measurement timing. Can be done. The reason for this is that the stress estimation device 102 estimates the chronic stress based on the cumulative value of the psychological burden, so that a value representing the time is introduced into the process in which the chronic stress is estimated. That is, the stress estimation device 102 estimates the degree of chronic stress with high accuracy not only at the measurement timing at which the measurement target is measured but also at a timing different from the measurement timing by changing the value representing the time. be able to.

Further, according to the stress estimation device 102 according to the first embodiment of the present invention, the degree of future chronic stress can be estimated. The reason for this is that the stress estimation device 102 calculates the degree of chronic stress based on the degree of psychological burden expected to be received in the future. For example, according to the stress estimation device 102 according to the first embodiment, when the measurement target has a risk of suffering from a mental illness, the measurement target can know the risk in advance. The reason for this is that the stress estimator 102 outputs, for example, a message indicating that the chronic stress is high, depending on the magnitude of the degree of chronic stress estimated based on the degree of psychological burden expected to be received in the future. Because.

Further, according to the stress estimation device 102 according to the first embodiment of the present invention, the degree of chronic stress can be estimated with high accuracy for each measurement target. The reason for this is that a second stress estimation model can be created, for example, for each measurement target. Therefore, the second stress estimation model created by the stress estimation device 102 is a model that reflects individual differences.

Further, according to the stress estimation device 102 according to the first embodiment of the present invention, chronic stress can be estimated in a short period of time. The reason for this is that in the estimation process, the stress estimation device 102 refers to the measurement information and the training information (for example, the psychological burden training information and the first chronic stress training information) which is the basis for creating each model. This is because chronic stress can be estimated without any need. In general, since the process of creating a model has a larger amount of processing than the process of estimating based on the model, the stress estimation device 102 can execute the prediction process in a short period of time.

<Second embodiment>
Next, the stress estimation (determination) system 201 according to the second embodiment of the present invention based on the first embodiment described above will be described.

In the following description, the characteristic parts relating to the present embodiment will be mainly described, and the same reference numbers will be assigned to the same configurations as those of the first embodiment described above, thereby omitting duplicate explanations. do.

The configuration of the stress estimation system 201 according to the second embodiment of the present invention will be described in detail with reference to FIG. FIG. 9 is a block diagram showing a configuration of the stress estimation system 201 according to the second embodiment of the present invention.

The stress estimation system 201 according to the second embodiment of the present invention includes a stress estimation (determination) device 202, a measurement unit 103, and an output device 104.

The stress estimation device 202 according to the second embodiment includes an input unit 105, a first chronic stress estimation unit 106, a psychological burden estimation unit 107, a schedule information processing unit 208, and a second chronic stress estimation unit 109. It has a chronic stress determination unit 110, a first chronic stress learning unit 111, a psychological burden learning unit 112, and a second chronic stress learning unit 113. The stress estimation device 202 further includes a first chronic stress information storage unit 114, a psychological burden information storage unit 115, a second chronic stress information storage unit 116, and an item burden information storage unit 217 (referring to FIG. 12). It may have (described later) and a burden information calculation unit 222.

The stress estimation device 202 may be communication-connected to the chronic stress calculation unit 221 that can calculate the degree of stress at a certain timing.

First, with reference to FIG. 11, schedule information for which the stress estimation device 202 predicts chronic stress will be described. FIG. 11 is a diagram conceptually showing an example of schedule information.

The schedule information is information in which an item name representing a process executed by the measurement target or a process executed with respect to the measurement target is associated with the date and time of the process. In other words, the schedule information is information including an event period representing a period during which a target event representing an event occurring in a stressed measurement target occurs.

Hereinafter, for convenience of explanation, the event and the above-mentioned processing are referred to as “processing”. In addition, the event period is represented by using the date and time related to the processing.

The schedule information includes, for example, the date and time of the process represented by the item name (for example, the start date and time, the end date and time), the day of the week, the type information indicating the type of process, whether or not the process is executed periodically, and the process. It may include the importance that is important and represents a certain degree. The higher the importance, the higher the importance.

In the schedule information illustrated in FIG. 11, the item name "A", the start date and time "15:10", the end date and time "15:50", the day of the week "Month", the type "meeting", the regularity "non-regular", And the importance "3" is associated. This means that, for example, the process represented by the item name "A" is executed irregularly during the execution time (execution period) from the start date and time "15:10" on Monday to the end date and time "15:50". Represents. Further, the process represented by the item name "A" is an example of a meeting, and indicates that the importance is 3.

The schedule information does not necessarily include all of the above-mentioned items, and may include items different from the above-mentioned items. That is, the schedule information is not limited to the above-mentioned example.

Next, in the stress estimation device 202, the item burden information that is the basis for the schedule information processing unit 208 to calculate the degree of psychological burden will be described with reference to FIG. FIG. 12 is a diagram conceptually representing an example of item burden information stored in the item burden information storage unit 217.

In the item burden information, the item name indicating the process performed by the measurement target (or executed for the measurement target) is associated with the degree of psychological burden that the measurement target receives due to the process. ing. In the item burden information, information representing the measurement target, the day of the week on which the process is executed, the type of the process, and the importance of the process may be further associated. The higher the importance, the higher the importance.

In the item burden information, the psychological burden may be the information input to the input unit 105 or the information calculated by the psychological burden estimation unit 107. Further, the psychological burden may be a psychological burden caused by the entire process, or may be information per unit time regarding the psychological burden.

In the following description, for convenience of explanation, it is assumed that the psychological burden represents the information per unit time in the item burden information.

Referring to FIG. 12, the item name “E”, the measurement target “Q”, the day of the week “Month”, the type “going out”, the importance “7”, and the psychological burden “2.1” are associated with each other. Has been done. This means that, for example, when the measurement target "Q" executes the process represented by the item name "E" on Monday, the psychological burden on the measurement target "Q" is 2.1. Further, this indicates that the process represented by the item name “E” is an example of the process of “going out” and the importance is 7.

In the item burden information, the degree of psychological burden on a specific day of the week (for example, Monday) may be larger than the degree of psychological burden on other days of the week. In this case, the stress estimation device 202 is accurately chronic by performing the processing according to the processing described later with reference to FIG. 10, based on the empirical rule that Monday has a higher psychological burden than the other days of the week. The degree of stress can be predicted.

Next, the process in the stress estimation system 201 according to the second embodiment will be described with reference to FIG. FIG. 10 is a flowchart showing a processing flow in the stress estimation system 201 according to the second embodiment.

The input unit 105 inputs schedule information (exemplified in FIG. 11) (step S201).

The schedule information processing unit 208 calculates the cumulative value of the psychological burden related to the processing represented by the item name included in the input schedule information (step S202). In other words, the schedule information processing unit 208 calculates the cumulative value of the psychological burden received from the target event included in the input schedule information. The process shown in step S202 will be described more specifically.

The schedule information processing unit 208 reads the item name included in the input schedule information (exemplified in FIG. 11), and identifies the psychological burden related to the read item name based on the item burden information (exemplified in FIG. 12). do. For example, the schedule information processing unit 208 reads the psychological burden associated with the item name included in the schedule information (exemplified in FIG. 11) in the item burden information (exemplified in FIG. 12). The schedule information processing unit 208 reads the start date and time related to the item and the end date and time related to the item for each item included in the schedule information, and sets a numerical value representing the specified psychological burden and from the start date and time to the end date and time. The cumulative value of the psychological burden is calculated by multiplying the time of and calculating the sum of the results.

When the item name in the schedule information (exemplified in FIG. 11) is not included in the item burden information (exemplified in FIG. 12), the schedule information processing unit 208 calculates the cumulative value of the psychological burden based on the predetermined value. You may. In this case, the input unit 105 receives item burden information including the input information in response to inputting information indicating the degree of psychological burden related to the item name, for example, acquired by a questionnaire survey or the like (FIG. 12). (Example) is created. Alternatively, in response to the psychological burden estimation unit 107 calculating information indicating the degree of psychological burden related to the item name, item burden information (exemplified in FIG. 12) including the calculated information is created. By creating the item burden information, the psychological burden information related to the processing represented by the item name becomes accurate, so that the stress estimation device 202 according to the second embodiment is more accurate and chronic stress based on the schedule information. The degree of can be calculated.

Further, in the item burden information (exemplified in FIG. 12), when there are a plurality of numerical values indicating the degree of psychological burden related to a certain item name, the schedule information processing unit 208 sets the average value of the plurality of numerical values to the certain item. It may be calculated as information indicating the degree of psychological burden related to the processing represented by the name. In this case, the schedule information processing unit 208 calculates the average value of a plurality of numerical values related to a certain item name, creates the item burden information in which the calculated average value is associated with the certain item name, and the item burden information. The item burden information stored in the storage unit 217 may be updated using the created item burden information. In this case, the larger the number of numerical values that are the basis for calculating the average value, the more accurate the average value. Therefore, according to the stress estimation device 202 according to the second embodiment, it is more accurate and chronic. The degree of stress can be calculated.

For example, the schedule information processing unit 208 may calculate the cumulative value of the psychological burden based on the type information representing the type included in the schedule information. In this case, the schedule information processing unit 208 calculates the cumulative value of the psychological burden by executing the same processing as the above-mentioned processing for the item name with respect to the type information. When there are a plurality of numerical values representing the psychological burden associated with the type information in the item burden information (exemplified in FIG. 12), the schedule information processing unit 208 calculates the average value of the plurality of the numerical values. The cumulative value of the psychological burden may be calculated. In this case, even if the item name included in the schedule information (exemplified in FIG. 11) is not included in the item burden information (exemplified in FIG. 12), the schedule information processing unit 208 uses the type. The cumulative value of psychological burden can be calculated based on the information. Therefore, according to the stress estimation device 202 according to the second embodiment, the degree of chronic stress can be calculated accurately.

After the process of step S202 in FIG. 10, the second chronic stress estimation unit 109 applies the second chronic stress estimation model to the cumulative value calculated by the schedule information processing unit 208 to determine the degree of chronic stress. Calculate (step S115). In other words, the second chronic stress estimation unit 109 calculates the degree of chronic stress received from the target event by applying the second chronic stress estimation model to the cumulative value calculated by the schedule information processing unit 208.

Further, when the degree of chronic stress satisfies a predetermined condition (YES in step S116), the chronic stress determination unit 110 is associated with the item name among the item names in the schedule information (exemplified in FIG. 11). A process of low importance (for example, in FIG. 12, the value of importance is small) may be selected. For example, the chronic stress determination unit 110 selects the item having the lowest importance (or substantially the lowest) among the items included in the schedule information (exemplified in FIG. 11). In this case, the chronic stress determination unit 110 may output a message urging the stress to be reduced during the period in which the processing related to the selected item is being executed (step S117). When the chronic stress determination unit 110 selects a process of low importance, the stress estimation device 202 can output an appropriate timing at which the measurement target can rest.

The stress estimation device 202 may execute the process shown in FIG. 10 in response to the measurement information being measured by the measurement unit 103. In this case, as the measurement information is measured, the measurement information that is the basis for creating the first chronic stress estimation model, the psychological burden estimation model, or the second chronic stress estimation model increases. With respect to these estimation models, the estimation accuracy increases as the measurement information increases, so that the stress estimation device 202 can more accurately estimate the degree of chronic stress.

Next, the effect of the stress estimation device 202 according to the second embodiment will be described. The degree of future chronic stress can be estimated. The reason for this is that the configuration of the stress estimation device 202 according to the second embodiment includes the configuration of the stress estimation device 102 according to the first embodiment.

Furthermore, according to the stress estimation device 202 according to the second embodiment, the degree of future chronic stress can be estimated more accurately. The reason for this is that the stress estimation device 202 estimates the degree of psychological burden for each item name included in the schedule information representing the schedule for the measurement target.

In the above example, the psychological burden estimation unit 107 estimates the psychological burden, but the psychological burden is calculated based on, for example, the degree of stress related to a certain timing calculated by the chronic stress calculation unit 221. can do.

For convenience of explanation, it is assumed that the period during which the first process relating to the measurement target is executed is the first period from the first timing to the second timing.

Chronic stress calculation unit 221. The degree of stress at the first timing of the measurement target (hereinafter referred to as "the degree of the first calculation stress") and the degree of stress at the second timing of the measurement target (hereinafter, "second calculation"). It is expressed as "degree of stress"). The burden information calculation unit 222 calculates the psychological burden related to the first process based on the degree of the first calculated stress, the difference between the degree of the second calculated stress, and the length of the first period. .. The burden information calculation unit 222 calculates, for example, a psychological burden regarding the processing related to the measurement target, and the item burden information in which the calculated psychological burden and the item representing the first processing are also associated with the item name (FIG. 12). Example) is created. That is, the item burden information (exemplified in FIG. 12) can be calculated by using the chronic stress calculation unit 221 that can calculate the degree of stress related to a certain timing. In this case, according to the stress estimation device 202, the same effect as the above-mentioned effect is obtained.

<Third embodiment>
Next, the stress estimation (determination) device 301 according to the third embodiment of the present invention will be described.

The configuration of the stress estimation device 301 according to the third embodiment of the present invention will be described in detail with reference to FIG. FIG. 13 is a block diagram showing a configuration of the stress estimation device 301 according to the third embodiment of the present invention.

The stress estimation device 301 according to the third embodiment of the present invention has a schedule information processing unit 302 and a chronic stress estimation unit 303. The stress estimation device 301 may further include a chronic stress information storage unit 304.

As illustrated in FIG. 8, the chronic stress information storage unit 304 stores a second chronic stress estimation model that represents the relationship between the degree of psychological burden and the degree of chronic stress.

For convenience of explanation, it is assumed that the item burden information (exemplified in FIG. 12) referred to by the stress estimation device 301 includes the degree of psychological burden per unit time received from the processing represented by the item name. However, the degree of psychological burden in the item burden information does not have to be the degree per unit time.

Next, the process in the stress estimation device 301 according to the third embodiment of the present invention will be described in detail with reference to FIG. FIG. 14 is a flowchart showing a processing flow in the stress estimation device 301 according to the third embodiment.

The schedule information processing unit 302 specifies the degree of psychological burden related to the processing represented by the item name based on the item burden information (exemplified in FIG. 12) with respect to the item name included in the schedule information (exemplified in FIG. 11). (Step S301). For example, the schedule information processing unit 302 is associated with the item name "A" based on the item burden information (exemplified in FIG. 12) with respect to the process represented by the item name "A" in the schedule information illustrated in FIG. Identify the psychological burden "4.5". The schedule information processing unit 302 may specify a plurality of numerical values in the item burden information (exemplified in FIG. 12) when there are a plurality of numerical values representing the psychological burden associated with a certain item name. When a plurality of numerical values are specified, the schedule information processing unit 302 calculates, for example, the degree of psychological burden related to the processing represented by the item name by obtaining the average value of the specified plurality of numerical values.

The chronic stress estimation unit 303 determines that the degree of psychological burden specified for the item name included in the schedule information (exemplified in FIG. 11) is the cumulative value accumulated for the item name included in the schedule information. Calculate (step S302). By this process, the chronic stress estimation unit 303 calculates the degree of chronic stress related to the schedule information (exemplified in FIG. 11). Alternatively, the chronic stress estimation unit 303 reads the second chronic stress estimation model stored in the chronic stress information storage unit 304, and reads the second chronic stress estimation model into a cumulative value calculated by the schedule information processing unit 302. The degree of chronic stress may be calculated by applying to.

The schedule information processing unit 302 is realized by a function similar to the function of the psychological burden accumulation unit 108 shown in the first embodiment or the schedule information processing unit 208 shown in the second embodiment. be able to. The chronic stress estimation unit 303 has a function similar to that of the second chronic stress estimation unit 109 shown in the first embodiment, the second chronic stress estimation unit 109 shown in the second embodiment, and the like. Can be realized by. The chronic stress information storage unit 304 has a function of the second chronic stress information storage unit 116 shown in the first embodiment, the second chronic stress information storage unit 116 shown in the second embodiment, and the like. It can be realized by a similar function. Therefore, the stress estimation device 301 according to the third embodiment has the same function as the function of the stress estimation device 102 according to the first embodiment or the function of the stress estimation device 202 according to the second embodiment. Can be realized by.

Next, the effect of the stress estimation device 301 according to the third embodiment will be described.

According to the stress estimation device 301 according to the third embodiment, the degree of future chronic stress can be estimated. The reason for this is that the stress estimation device 301 specifies the degree of psychological burden for each item name included in the schedule information representing the schedule for the measurement target, and chronically sets the cumulative value of the specified psychological burden. This is because it is estimated as the degree of stress.

<Fourth Embodiment>
Next, the stress estimation (determination) device 401 according to the fourth embodiment of the present invention will be described.

The configuration of the stress estimation device 401 according to the fourth embodiment of the present invention will be described in detail with reference to FIG. FIG. 15 is a block diagram showing a configuration of the stress estimation device 401 according to the fourth embodiment of the present invention.

The stress estimation device 401 according to the fourth embodiment of the present invention has a psychological burden estimation unit 402, a psychological burden accumulation unit 403, and a chronic stress estimation unit 404. The stress estimation device 401 further includes a psychological burden information storage unit 405 and a chronic stress information storage unit 406.

The psychological burden information storage unit 405 stores a psychological burden estimation model that represents the relationship between the measurement information (or a feature amount that represents the characteristics of the measurement information) and the information that represents the degree of psychological burden. .. The chronic stress information storage unit 406 stores a second chronic stress estimation model that represents the relationship between the cumulative value of the psychological burden and the degree of chronic stress.

Next, with reference to FIG. 16, the process in the stress estimation device 401 according to the fourth embodiment of the present invention will be described in detail. FIG. 16 is a flowchart showing a processing flow in the stress estimation device 401 according to the fourth embodiment.

The psychological burden estimation unit 402 calculates the value of the feature amount representing the feature of the measurement information by executing the process according to the predetermined feature amount calculation procedure for the measurement information created by the sensor or the like that measures the measurement target. (Step S401). The psychological burden estimation unit 402 calculates the feature amount related to the measurement information according to the process described with reference to, for example, Equations 6 to 16. The psychological burden estimation unit 402 calculates numerical information indicating the degree of psychological burden related to the measurement information by applying the psychological burden estimation model to the calculated feature value (step S402).

The psychological burden accumulation unit 403 calculates the cumulative value of the numerical information representing the degree of the psychological burden calculated with respect to the measurement information measured in a certain period (step S403). The psychological burden accumulation unit 403 calculates the cumulative value of the degree of psychological burden according to the same process as the process shown in Equation 1, for example.

The chronic stress estimation unit 404 calculates the degree of chronic stress related to the measurement information by applying the second chronic stress estimation model to the cumulative value calculated by the psychological burden accumulation unit 403 (step S404).

The psychological burden estimation unit 402 has a function similar to that of the psychological burden estimation unit 107 shown in the first embodiment, the psychological burden estimation unit 107 shown in the second embodiment, and the like. It can be realized by using. The psychological burden accumulation unit 403 uses a function similar to that of the psychological burden accumulation unit 108 shown in the first embodiment or the schedule information processing unit 208 shown in the second embodiment. It can be realized. The chronic stress estimation unit 404 has a function similar to that of the second chronic stress estimation unit 109 shown in the first embodiment or the second chronic stress estimation unit 109 shown in the second embodiment. Can be realized using. That is, the stress estimation device 401 according to the fourth embodiment has the same function as the function of the stress estimation device 102 according to the first embodiment or the function of the stress estimation device 202 according to the second embodiment. Can be realized using.

Next, the effect of the stress estimation device 401 according to the fourth embodiment will be described.

According to the stress estimation device 401 according to the fourth embodiment, the degree of chronic stress can be estimated with high accuracy not only at the measurement timing at which the measurement target is measured but also at a timing different from the measurement timing. The reason for this is that the stress estimator 401 estimates the chronic stress based on the cumulative value of the psychological burden, so that a value representing the time is introduced into the process in which the chronic stress is estimated. That is, the stress estimation device 401 estimates the degree of chronic stress with high accuracy not only at the measurement timing at which the measurement target is measured but also at a timing different from the measurement timing by changing the value representing the time. be able to.

(Hardware configuration example)
An example of a configuration of hardware resources for realizing the stress estimation (determination) device in each embodiment of the present invention described above by using one calculation processing device (information processing device, computer) will be described. However, such a stress estimation device may be physically or functionally realized by using at least two calculation processing devices. Further, the stress estimation device may be realized as a dedicated device.

FIG. 17 is a block diagram schematically showing a hardware configuration example of a calculation processing device capable of realizing the stress estimation (determination) device according to the first to fourth embodiments. The calculation processing device 20 includes a central processing unit (Central_Processing_Unit, hereinafter referred to as “CPU”) 21, a memory 22, a disk 23, a non-volatile recording medium 24, and a communication interface (hereinafter referred to as “communication IF”) 27. Have. The calculation processing device 20 can be connected to or communicate with the input device 25 and the output device 26. The calculation processing device 20 can transmit / receive information to / from other calculation processing devices and the communication device via the communication IF 27. The input device 25 represents a pulse wave sensor, an acceleration sensor, a skin surface conductivity sensor, a heartbeat sensor, a wearable device, or the like.

The non-volatile recording medium 24 is, for example, a computer-readable compact disc (Compact_Disc) or a digital versatile disc (Digital_Versail_Disc). Further, the non-volatile recording medium 24 may be a universal serial bus memory (USB memory), a solid state drive (Solid_State_Drive), or the like. The non-volatile recording medium 24 holds the program and makes it portable without supplying power. The non-volatile recording medium 24 is not limited to the above-mentioned medium. Further, instead of the non-volatile recording medium 24, the relevant program may be carried via the communication IF27 and the communication network.

That is, the CPU 21 copies the software program (computer program: hereinafter, simply referred to as "program") stored in the disk 23 to the memory 22 when executing the software program, and executes the arithmetic processing. The CPU 21 reads the data required for program execution from the memory 22. When output to the outside is required, the CPU 21 outputs the output result to the output device 26. When inputting a program from the outside, the CPU 21 reads the program from the input device 25. The CPU 21 is a stress estimation (determination) program (FIGS. 2, FIG. 3, FIG. 10. Interpret and execute FIG. 14 or FIG. 16). The CPU 21 sequentially executes the processes described in each of the above-described embodiments of the present invention.

That is, in such a case, it can be considered that the present invention can also be achieved by the stress estimation program. Further, it can be considered that the present invention can be achieved by a non-volatile recording medium that can be read by a computer in which the stress estimation (determination) program is recorded.

The present invention has been described above using the above-described embodiment as a model example. However, the present invention is not limited to the above-described embodiments. That is, the present invention can apply various aspects that can be understood by those skilled in the art within the scope of the present invention.

It should be noted that some or all of the above-described embodiments may also be described as described in the following appendices. However, the present invention exemplified by each of the above-described embodiments is not limited to the following. That is,
(Appendix 1)
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and the stress information that represents the degree of stress when the psychological burden is received during the first period Stored chronic stress information storage means and
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the psychological burden estimation means for calculating the degree of the psychological burden with respect to the first measurement target, and the psychological burden estimation means.
A psychological burden accumulating means for calculating cumulative burden information representing a numerical value obtained by accumulating the degree of the psychological burden calculated based on the measurement information measured in the second period with respect to the first measurement target.
Stress determination including a second chronic stress estimation means for estimating the degree of stress received by the first measurement target in the second period by applying the second chronic stress estimation model to the cumulative burden information. Device.

(Appendix 2)
Appendix 1 is further provided with a stress determining means for determining that the stress received by the first measurement target during the second period is high when the degree of stress calculated for the second period satisfies a predetermined condition. The stress determination device according to.

(Appendix 3)
The measurement information represents pressure information representing pressure measured at a plurality of locations relating to the first measurement target at a plurality of timings.
The stress determination device according to Appendix 1 or Appendix 2, wherein the first feature amount indicates the degree to which the center of pressure of the plurality of points measured with respect to the first measurement target varies with respect to the plurality of timings.

(Appendix 4)
A second feature representing the feature of the second measurement information calculated from the second measurement information measured with respect to the second measurement target according to a predetermined second feature amount calculation procedure different from the predetermined first feature amount calculation procedure. A first chronic stress information storage means in which a first chronic stress estimation model representing a relationship between a quantity value and a numerical value representing the degree of stress related to the second measurement target is stored, and
From the measurement information measured with respect to the first measurement target, the value of the second feature amount is calculated according to the predetermined second feature amount calculation procedure, and the calculated value of the second feature amount is compared with the second feature amount. (1) The stress determination device according to any one of Appendix 1 to Appendix 3, further comprising a first chronic stress estimation means for estimating the degree of stress related to the first measurement target by applying the chronic stress estimation model.

(Appendix 5)
Linear regression with respect to the cumulative burden information calculated by the psychological burden accumulating means for the first measurement target and the degree of stress estimated by the first chronic stress estimation means for the first measurement target. The stress determination device according to Appendix 4, further comprising a second chronic stress learning means for creating the second chronic stress estimation model according to the analysis and storing the created second chronic stress estimation model in the chronic stress information storage means.

(Appendix 6)
By processing the psychological burden information in which the value of the first feature amount related to the measurement target and the degree of the psychological burden related to the measurement target are associated with each other according to a procedure related to a predetermined machine learning technique. The stress determination according to any one of Appendix 1 to Appendix 5, further comprising a psychological burden learning means for creating the psychological burden estimation model and storing the created psychological burden estimation model in the psychological burden information storage means. Device.

(Appendix 7)
Further provided with a heartbeat sensor for measuring the heartbeat of the second measurement target,
The stress determination device according to Appendix 4, wherein the second feature amount represents a correlation dimension calculated with respect to the measured heartbeat.

(Appendix 8)
The stress determination device according to Appendix 7, further comprising a wearable device having the heart rate sensor and to which the second measurement target can be worn.

(Appendix 9)
A pressure distribution sensor that measures the pressure of the first measurement target at the plurality of locations is further provided.
The pressure distribution sensor has a pressure detection cell capable of measuring pressure, which is arranged in a grid pattern in a predetermined region.
The stress determination device according to Appendix 3, wherein the first feature amount indicates the degree to which the pressure centers or substantially the centers at a plurality of locations measured by the pressure distribution sensor vary with respect to the passage of time.

(Appendix 10)
The stress distribution sensor according to Appendix 9, wherein the pressure distribution sensor is installed at at least one of the seat surface of the chair, the backrest of the chair, and the front of the chair.

(Appendix 11)
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and the stress information that represents the degree of stress when the psychological burden is received during the first period Using an information processing device that can read and write to the stored chronic stress information storage means,
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the degree of the psychological burden on the first measurement target was calculated, and the calculation was performed based on the measurement information measured in the second period with respect to the first measurement target. By calculating the cumulative burden information representing the cumulative numerical value of the degree of the psychological burden and applying the second chronic stress estimation model to the cumulative burden information, the first measurement target is measured in the second period. A stress determination method that estimates the degree of stress that a person receives.

(Appendix 12)
The relationship between the value of the first feature amount representing the feature of the measurement information calculated from the measurement information measured with respect to the measurement target according to the predetermined first feature amount calculation procedure and the degree of psychological burden on the measurement target. Psychological burden information storage means that stores the psychological burden estimation model to be represented,
A second chronic stress estimation model that represents the relationship between the cumulative value of the degree of psychological burden over the first period and stress information that represents the degree of stress when the psychological burden is received during the first period A computer that can read and write to the stored chronic stress information storage means,
From the measurement information measured with respect to the first measurement target, the value of the first feature amount is calculated according to the predetermined first feature amount calculation procedure, and the calculated value is stored in the psychological burden information storage means. By applying the psychological burden estimation model, the psychological burden estimation function for calculating the degree of the psychological burden on the first measurement target and the psychological burden estimation function
A psychological burden accumulation function that calculates cumulative burden information representing a numerical value that accumulates the degree of the psychological burden calculated based on the measurement information measured in the second period with respect to the first measurement target, and a psychological burden accumulation function.
By applying the second chronic stress estimation model to the cumulative burden information, stress that realizes a second chronic stress estimation function that estimates the degree of stress received by the first measurement target during the second period. Judgment program.

101 Stress estimation system 102 Stress estimation device 103 Measuring unit 104 Output device 105 Input unit 106 1st chronic stress estimation unit 107 Psychological burden estimation unit 108 Psychological burden accumulation unit 109 2nd chronic stress estimation unit 110 Chronic stress judgment unit 111th 1 Chronic stress learning unit 112 Psychological burden learning unit 113 2nd chronic stress learning unit 114 1st chronic stress information storage unit 115 Psychological burden information storage unit 116 2nd chronic stress information storage unit 121 Pressure detection cell 122 Pressure detection cell 123 Backrest 124 Seat surface 125 Pressure distribution sensor 126 Pressure distribution sensor 127 Pressure distribution sensor 131 Heartbeat sensor 201 Stress estimation system 202 Stress estimation device 208 Schedule information processing unit 217 Item Burden information storage unit 221 Chronic stress calculation unit 222 Burden information calculation unit 301 Stress Estimator 302 Schedule Information Processing Department 303 Chronic Stress Estimator 304 Chronic Stress Information Storage 401 Stress Estimator 402 Psychological Burden Estimate 403 Psychological Burden Accumulation 404 Chronic Stress Estimator 405 Psychological Burden Information Storage 406 Chronic Stress Information Storage unit 20 Calculation processing device 21 CPU
22 Memory 23 Disk 24 Non-volatile recording medium 25 Input device 26 Output device 27 Communication IF

Claims (9)

From the pressure generated according to the posture of the measurement target measured at a plurality of timings at a plurality of measurement targets or the measurement information including the heartbeat of the measurement target, the center of the pressure with respect to the plurality of locations is the plurality of pressures. The degree of variation with respect to the timing of the above, or the value of the feature amount including the numerical value indicating the temporal transition of the heartbeat is calculated, and the calculated value indicates the relationship between the value of the feature amount and the degree of psychological burden. By applying the psychological burden estimation model, a psychological burden estimation means for calculating the degree of the psychological burden on the measurement target, and a psychological burden estimation means.
A psychological burden accumulating means for calculating cumulative burden information representing a cumulative value in which the degree of the psychological burden in a certain period is accumulated, and
Psychology to estimate the degree of chronic stress in the certain period by applying the psychological burden cumulative-chronic stress relationship model showing the relationship between the cumulative value and the degree of chronic stress to the cumulative burden information. Accumulation of physical burden-A stress determination device equipped with a means for estimating a chronic stress relationship. The stress determination device according to claim 1, further comprising a stress determination means for determining that the degree of chronic stress is high when a predetermined condition for determining that the degree of chronic stress is high is satisfied. .. By calculating the value of the feature amount including the correlation dimension calculated for the heartbeat and applying the chronic stress estimation model representing the relationship between the feature amount and the degree of chronic stress to the calculated value, the chronicity The stress determination device according to claim 1 or 2, further comprising a chronic stress estimation means for estimating the degree of stress. Psychological burden accumulation-chronic stress relationship model is created according to linear regression analysis for the cumulative burden information calculated for the measurement target and the degree of chronic stress estimated for the measurement target. The stress determination device according to any one of claims 1 to 3, further comprising a burden accumulation-chronic stress relationship learning means. The psychological burden information associated with the value of the feature amount related to the measurement target and the degree of the psychological burden related to the measurement target is processed according to a procedure related to a predetermined machine learning technique. The stress determination device according to any one of claims 1 to 4, further comprising a psychological burden learning means for creating a physical burden estimation model. The stress determination device according to claim 3 or 4, further comprising a heart rate sensor for measuring the heart rate. The stress determination device according to claim 6, further comprising a wearable device having the heart rate sensor. The pressure generated by the information processing device according to the posture of the measurement target measured at a plurality of timings at a plurality of measurement targets, or the pressure related to the plurality of locations from the measurement information including the heartbeat of the measurement target. The degree to which the center of the above varies with respect to the plurality of timings, or the value of the feature amount including the numerical value representing the temporal transition of the heartbeat is calculated, and the calculated value is added to the value of the feature amount and the degree of psychological burden. By applying the psychological burden estimation model representing the relationship between the above, the degree of the psychological burden on the measurement target is calculated, and the cumulative burden information representing the cumulative value obtained by accumulating the degree of the psychological burden in a certain period By applying the psychological burden cumulative-chronic stress relationship model that represents the relationship between the cumulative value and the degree of chronic stress to the cumulative burden information, the degree of chronic stress in the certain period is applied. Stress determination method to estimate. From the pressure generated according to the posture of the measurement target measured at a plurality of timings at a plurality of measurement targets or the measurement information including the heartbeat of the measurement target, the center of the pressure with respect to the plurality of locations is the plurality of pressures. The degree of variation with respect to the timing of the above, or the value of the feature amount including the numerical value indicating the temporal transition of the heartbeat is calculated, and the calculated value indicates the relationship between the value of the feature amount and the degree of psychological burden. By applying the psychological burden estimation model, the psychological burden estimation function that calculates the degree of the psychological burden on the measurement target and the psychological burden estimation function
Psychological burden accumulation function that calculates cumulative burden information that represents the cumulative value of the accumulated degree of psychological burden in a certain period, and
Psychological burden to estimate the degree of chronic stress in a certain period by applying the psychological burden cumulative-chronic stress relationship model showing the relationship between the cumulative value and the degree of chronic stress to the cumulative burden information. A stress judgment program that realizes the cumulative burden-chronic stress relationship estimation function on a computer.

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