JP7112851B2 - Information processing device, fatigue evaluation method and program - Google Patents

Description

The present invention relates to an information processing device, fatigue evaluation method, and program.

In recent years, efforts have been made to prevent mental health problems in the workplace. For example, at present, workplaces with 50 or more employees are obliged to conduct stress checks on their employees. This stress check uses a questionnaire containing 57 check items to determine the stress level of employees, enabling the early detection of employees who are likely to develop mental health problems. This is an attempt to prevent mental health problems by conducting face-to-face guidance (Non-Patent Document 1).

"Stress check system implementation manual based on the Industrial Safety and Health Act", Ministry of Health, Labor and Welfare, April 2016

The determination method using the questionnaire is based on the premise that the employee answers accurately about his or her situation. However, according to the results of interviews with public health nurses and industrial physicians who deal with employee health issues at companies, the more unwell employees are, the less likely they are to answer the stress checkup questionnaire correctly. It has been found that people tend to hide their poor physical condition. Therefore, in order to accurately grasp the degree of mental and physical fatigue of employees, it is necessary to evaluate the degree of fatigue using a simpler and more objective physiological index, rather than the method of self-reporting subjective symptoms using a questionnaire. is required.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a technology capable of evaluating a user's degree of fatigue by a simple and objective method.

An information processing apparatus according to an aspect of the present invention is an information processing apparatus that evaluates a fatigue state of a user, and acquires biometric information related to blinking of the user that is measured using a sensor worn by the user. It has an acquisition unit, and an evaluation unit that evaluates the fatigue state of the user based on the biometric information relating to blinking of the user acquired by the acquisition unit.

A fatigue evaluation method according to another aspect of the present invention is a fatigue evaluation method executed by an information processing device that evaluates a fatigue state of a user, and It has a step of acquiring biometric information about eyes, and a step of evaluating the fatigue state of the user based on the acquired biometric information about blinking of the user.

A program according to another aspect of the present invention is a computer that evaluates the user's fatigue state, acquiring biometric information related to the user's blinking measured using a sensor worn by the user; and evaluating the fatigue state of the user based on the biological information related to the user's blinking.

ADVANTAGE OF THE INVENTION According to this invention, the technique which can evaluate a user's fatigue degree by a simple and objective method can be provided.

It is a figure which shows the structural example of the fatigue evaluation system which concerns on this embodiment. It is a figure which shows the structural example of the wearable terminal which concerns on this embodiment. It is a figure which shows the concrete measurement item of the biometric information regarding a blink. FIG. 4 is a diagram showing an example of an electro-oculography waveform when a user blinks. It is a figure which shows the structural example of the evaluation apparatus which concerns on this embodiment. It is a flowchart which shows an example of the processing procedure which an evaluation apparatus performs. It is a figure which shows an experimental result. It is a figure which shows an experimental result. It is a figure which shows an experimental result. It is a figure which shows an experimental result.

Preferred embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that, in each figure, the same reference numerals have the same or similar configurations.

<System configuration and overview>
FIG. 1 is a diagram showing a configuration example of a fatigue evaluation system 1 according to this embodiment. A fatigue evaluation system 1 according to the present embodiment includes a glasses-type wearable terminal 10 worn by a user and an evaluation device 20 capable of communicating with the wearable terminal 10 .

The wearable terminal 10 includes an electro-oculography sensor 13 that measures the electro-oculography signal of the user. The electro-oculography sensor 13 is composed of bioelectrodes 13a, 13b, and 13c attached to a pair of nose pads and a bridge portion. The fatigue evaluation system 1 analyzes the electro-oculogram measured by the electro-oculography sensor 13 to obtain biological information related to blinking performed by the user. Note that the electro-oculography sensor 13 is not essential. For example, instead of the electro-oculography sensor 13, a camera may be provided on the frame of the eyeglasses or the like, and biometric information relating to blinking may be obtained by image processing an image captured using the camera. . Also, the wearable terminal 10 has a 6-axis sensor and can detect the movement of the user's head. That is, the electro-oculography sensor 13 and the camera may be called "sensors".

The evaluation device 20 is a device that wirelessly communicates with the wearable terminal 10, and is, for example, a smart phone, a tablet terminal, a mobile phone, a personal computer, or the like owned by the user. The evaluation device 20 evaluates the fatigue state of the user based on the biometric information regarding the blink of the user measured by the wearable terminal 10 . Note that the evaluation device 20 may be composed of one device, or may be composed of a plurality of devices. For example, the evaluation device 20 may be composed only of a smartphone or the like possessed by the user, or may be composed of a smartphone or the like possessed by the user and a server capable of communicating via a network. Also, in the present embodiment, all the functions provided by the evaluation device 20 may be implemented in the wearable terminal 10 . That is, the evaluation device 20 may be called an "information processing device", and the wearable terminal 10 implementing the functions of the evaluation device 20 may be called an "information processing device".

<Configuration of wearable terminal and evaluation device>
FIG. 2 is a diagram showing a configuration example of the wearable terminal 10 according to this embodiment. The wearable terminal 10 has a CPU 11 , a storage device 12 such as a memory, an electro-oculography sensor 13 , a 6-axis sensor 14 , and a communication IF (Interface) 15 . The 6-axis sensor 14 is more specifically an acceleration sensor and a gyro sensor, and detects acceleration in 3-axis directions and angular velocity around 3 axes, respectively. The communication IF 15 communicates with the evaluation device 20 using short-range communication such as Bluetooth (registered trademark) and BLE (Bluetooth (registered trademark) Low Energy), mobile radio communication such as LTE (Long Term Evolution), and the like.

Wearable terminal 10 also has measuring section 110 and transmitting section 111 . The measurement unit 110 and the transmission unit 111 can be implemented by the CPU 11 executing a program stored in the storage device 12 . Also, the program can be stored in a recording medium. The recording medium storing the program may be a non-temporary recording medium.

The measurement unit 110 acquires an electro-oculography signal from the electro-oculography sensor 13 and analyzes the acquired electro-oculography signal to measure biological information related to blinking of the user wearing the wearable terminal 10 .

Here, specific measurement items and a measurement method for the biological information related to blinking measured by the measurement unit 110 will be described. FIG. 3 is a diagram showing specific measurement items of biological information related to blinking. FIG. 4 shows an example of an electro-oculography waveform measured by the electro-oculography sensor 13 when the user blinks.
"Item number 1: number of blinks": A measurement item indicating the number of times the user blinked in a predetermined unit time. Although the predetermined unit time is arbitrary, it may be one minute, for example.
"Item number 2: Blink strength": As shown in Fig. 4(a), this is a measurement item indicating the magnitude of the electro-oculography (potential difference) between the positive peak and the negative peak of the electro-oculography waveform. .
"Item number 3: strength of blink" is a measurement item that indicates the magnitude of the electro-oculography (potential difference) between the positive peak and the negative peak of the electro-oculography waveform, similar to item number 2. Compared to item number 2, the method of noise processing (removal, etc.) included in the measured electro-oculography waveform is changed. Specifically, item numbers 2 and 3 have different thresholds for identifying whether the electro-oculography waveform is a valid waveform or noise.
“Item No. 4: Positive peak value among values obtained by differentiating blink intensity waveform”: As shown in FIG. It is a measurement item.
"Item No. 5: Positive peak value among the values obtained by differentiating the blink intensity waveform": As with Item No. 4, this is a measurement item that indicates the positive peak value when the electro-oculography waveform is differentiated. However, compared to item number 4, the method of noise processing (removal, etc.) included in the measured electro-oculography waveform is changed.
"Item No. 6: Negative peak value among values obtained by differentiating blink intensity waveform": As shown in FIG. It is a measurement item.
"Item No. 7: Negative peak value among the values obtained by differentiating the blink intensity waveform": As with Item No. 6, this is a measurement item that indicates a value that becomes a negative peak when the electro-oculography waveform is differentiated. However, compared to item number 6, the method of noise processing (removal, etc.) included in the measured electro-oculography waveform is changed.
"Item No. 8: Blink time" is a measurement item indicating the time difference between the start time and the end time of the electro-oculogram waveform corresponding to one blink, as shown in FIG. 4(a).
“Item No. 9: Blink time”: As with Item No. 8, this is a measurement item that indicates the time difference between the start time and the end time of the electrooculogram waveform corresponding to one eye blink. In contrast, the technique of noise processing (removal, etc.) included in the measured electro-oculography waveform is changed.
"Item No. 10: Blink interval": As shown in FIG. 4A, the start time of the electro-oculography waveform corresponding to one blink and the start time of the electro-oculography waveform corresponding to the next blink. This is a measurement item that indicates the time difference between Note that the timing for measuring the interval is not limited to the time when the electro-oculogram waveform ends. For example, the timing corresponding to the positive or negative peak of the electro-oculography waveform, or the timing interval at which the electro-oculography waveform is started may be measured.

Each of the measurement items 1 to 10 described above may be an average value in a predetermined period. For example, the measurement unit 110 may acquire a plurality of measured values by performing measurements over a predetermined period of time, and use the average value of the acquired plurality of measured values as the measurement result. The predetermined period is arbitrary, but may be, for example, the average of the most recent 3 minutes or the average of the most recent 5 minutes. As a result, it is possible to absorb the variation in biological information related to blinking of the user, and it is possible to evaluate the degree of fatigue more accurately.

Further, the measurement unit 110 may calculate the standard deviation (SD) in a predetermined period for each of the measurement items 1 to 10, and use the calculated standard deviation as the measurement result. For example, the measurement unit 110 may acquire a plurality of measured values by performing measurements over a predetermined period of time, and calculate the standard deviation using the acquired plurality of measured values. Although the predetermined period is arbitrary, it is preferable to set it to a period in which a certain number (for example, about 50) of measured values can be obtained. Since the standard deviation is an index that indicates the variation of the data, for example, a state in which the strength of the blink changes greatly for each blink, or a state in which the strength of the blink hardly changes. be able to comprehend.

In addition, the measurement unit 110 may exclude the electro-oculography waveform when the user intentionally closes the eye and opens the eye after a certain period of time from the electro-oculography waveform used for the measurement of the measurement items 1 to 10. For example, when the user intentionally closes his/her eyes and then opens them after a certain period of time, as shown in FIG. appear at distant positions on the time axis. Therefore, when the positive waveform and the negative waveform of the electro-oculogram are separated by a predetermined time or longer, the measurement unit 110 considers that the user intentionally closes the eyes and then opens them after a predetermined time. It may be excluded from the electro-oculography waveform used for the measurement of items 1-10. This makes it possible to exclude, from evaluation targets, blinks that occur spontaneously (spontaneous blinks) and blinks other than blinks that are close to spontaneous blinks among blinks that the user voluntarily performs. become.

The transmission unit 111 has a function of transmitting the biometric information regarding the blink of the user measured by the measurement unit 110 to the evaluation device 20 via the communication IF 15 .

FIG. 5 is a diagram showing a configuration example of the evaluation device 20 according to this embodiment. The evaluation device 20 has a CPU 21 , a storage device 22 such as a memory, an input device 23 , an output device 24 and a communication IF 25 . The input device 23 is a device that receives an input operation from a user, and is, for example, a keyboard, mouse, touch panel, or the like. The output device 24 is a device that outputs information, such as a display and a printer. The communication IF 25 communicates with the wearable terminal 10 using short-range communication such as Bluetooth (registered trademark) or mobile radio communication such as LTE.

The evaluation device 20 also has an acquisition unit 210 and an evaluation unit 211 . The acquisition unit 210 and the evaluation unit 211 can be implemented by the CPU 21 executing programs stored in the storage device 22 . Also, the program can be stored in a recording medium. The recording medium storing the program may be a non-temporary recording medium.

In the storage device 22, statistical analysis is performed on "blink-related biological information" obtained from a plurality of subjects, and "fatigue evaluation index directly or indirectly indicating the state of fatigue" obtained from a plurality of subjects. Correlation information 220 is stored that indicates the correlation between the biological information about the blink and the fatigue evaluation index that is generated in this way. The correlation information 220 stores, for example, the values of the “blink-related biological information” described in item numbers 1 to 10 above and the fatigue evaluation index values correlated with the biological information in association with each other. there is Taking the case of “item number 1: number of blinks” as an example, the correlation information 220 includes, for example, information such that if the number of blinks is X, the value of the fatigue evaluation index is Y; Information is stored such that when the number of eyes is between A to B, B to C, and C to D, the values of the fatigue evaluation index are X, Y, and Z, respectively.

A fatigue evaluation index is an index that is measured by an interview about fatigue, an index that is an index that relates to the function of the autonomic nerves and that indirectly indicates the degree of fatigue, or an index that relates to living behavior including during sleep of the subject and is the degree of fatigue. It is an indicator that indirectly indicates A specific example will be described later.

Acquisition unit 210 has a function of acquiring biometric information relating to blinking of the user, which is measured using electro-oculography sensor 13 worn by the user.

The evaluation unit 211 has a function of evaluating the fatigue state of the user based on the biological information regarding the blink of the user acquired by the acquisition unit 210 . More specifically, the evaluation unit 211 acquires from the correlation information 220 the fatigue evaluation index corresponding to the biological information related to blinking of the user, and evaluates the fatigue state of the user based on the value of the acquired fatigue evaluation index. may

Although the configurations of the wearable terminal 10 and the evaluation device 20 have been described above, the measurement unit 110 included in the wearable terminal 10 may be provided on the evaluation device 20 side. In this case, the transmission unit 111 of the wearable terminal 10 may transmit the electro-oculography signal measured by the electro-oculography sensor 13 to the evaluation device 20 . The measurement unit 110 of the evaluation device 20 may measure biological information related to blinking of the user by analyzing the received electro-oculography signal.

<Processing procedure>
FIG. 6 is a flowchart showing an example of a processing procedure performed by the evaluation device 20. As shown in FIG. First, the acquisition unit 210 acquires biometric information relating to blinking of the user transmitted from the wearable terminal 10 (S100). Subsequently, the evaluation unit 211 acquires the value of the fatigue evaluation index corresponding to the value of the biological information related to blinking of the user from the correlation information 220, and evaluates the fatigue state of the user using the obtained value of the fatigue evaluation index. (S101). Subsequently, the evaluation unit 211 outputs the evaluation result to the output device 24 (S102). Here, as the evaluation result output from the output device 24, the value of the fatigue evaluation index may be output as it is, or a message corresponding to the value of the fatigue evaluation index may be output. In the latter case, information that associates each value of the fatigue evaluation index with a message to be output is stored in advance in the storage device 22, and the evaluation unit 211 accesses the information to determine the message to be output. You may make it For example, when the value of the fatigue evaluation index is a predetermined value, the evaluation unit 211 may output a message such as "Mental fatigue may be accumulated" as the fatigue state of the user. .

While the wearable terminal 10 is worn by the user, the wearable terminal 10 can constantly transmit biometric information about the user's blinks to the evaluation device 20 . Therefore, the evaluation device 20 may repeat the processing procedure of steps S100 to S102 at predetermined intervals (for example, every 12 hours or every day). The evaluation unit 211 may output the evaluation result to the output device 24 when the evaluation result of the fatigue state of the user changes.

<Experimental results>
Next, the “fatigue evaluation index that directly or indirectly indicates the fatigue state” and “biological information related to blinking” obtained from the results of an experiment in which the degree of fatigue was evaluated for 9 consecutive weeks on 10 subjects. The result of investigating the correlation with .

The inventors collected biological information related to blinking by having the wearable terminal 10 worn by the subject, and measured using an interview and a dedicated device to obtain the following fatigue evaluation index (index A ~C) values were collected.
Index A: An index that directly indicates the degree of fatigue, which is measured by interviewing about subjective fatigue. Index B: An index regarding the function of the autonomic nerves, which is the degree of fatigue, obtained by measuring using a dedicated measuring instrument. Indicator C: An indicator of the subject's daily activities, including during sleep, obtained by wearing a dedicated measuring device for 24 hours, and indirectly indicating the degree of fatigue Obtained from the experimental results 7 to 10 show the presence or absence of the correlation. 7 to 10, the upper numerical values indicate the correlation coefficient (r value), and the lower numerical values indicate the significance probability (p value).

Here, if "r value < -0.2 or 0.2 < r value" and "p value < 0.05", "a fatigue evaluation index that directly or indirectly indicates the fatigue state of the subject" , and the “biological information on eye blinks of the subject”. In addition, in the case of "r value < -0.2 or 0.2 < r value" and "0.05 < p value < 0.1", "directly or indirectly indicating the fatigue state of the subject It can be considered that there is a high possibility that there is a correlation between the "fatigue evaluation index" and the "biological information on blinking of the subject." On the other hand, if "0.1 < p value" or "-0.2 < r value < 0.2", "fatigue evaluation index directly or indirectly indicating the fatigue state of the subject" and "subject's It can be considered that there is no correlation with "biological information on blinking".

In FIGS. 7 to 10, for combinations that can be considered to have a correlation, the r-values and p-values are surrounded by dotted lines. In addition, the r-value and p-value are underlined for combinations that can be considered to have a high possibility of correlation. Also, the item numbers in FIGS. 7 to 10 correspond to the item numbers explained in FIG.

First, FIG. 7 will be described. “Chalder” is an index that indicates the degree of mental and physical fatigue called the Chalder Fatigue Scale, and is evaluated on a scale of 0 to 33 points, and the higher the score, the greater the degree of mental and physical fatigue. Show big. "CESD (CES-D)" is an index that indicates the degree of depression by score created by the National Institute of Mental Health, and is evaluated on a scale of 0 to 60. The higher the score, the stronger the depression. evaluated. "Physical fatigue" is a score (0 to 40 points) based on 47 items related to fatigue, and the higher the score, the greater the degree of physical fatigue (e.g., muscle fatigue, headache, joint pain, etc.). show. "Mental fatigue" is a score (0 to 40 points) based on a questionnaire of 47 items related to fatigue, and the higher the score, the greater the degree of mental fatigue (e.g., depression, decreased motivation, decreased concentration, etc.). show. "Comprehensive fatigue" is the total score (0 to 80 points) for physical fatigue and mental fatigue, and the higher the score, the greater the degree of physical and mental fatigue. show. "PSQIG" is an index of sleep quality called the Pittsburgh Sleep Quality Index, which is evaluated on a scale of 0 to 21, with higher scores indicating poorer sleep quality. Poor sleep quality is considered to indirectly indicate a high degree of physical fatigue or mental fatigue. That is, it can be considered that the index indicating sleep quality is an index that indirectly indicates mental fatigue and physical fatigue. "Czalda", "CESD", "physical fatigue", "mental fatigue", "general fatigue", and "PSQIG" correspond to the index A described above.

According to the experimental results shown in FIG. 7, it can be seen that "item number 1: number of blinks" has a positive correlation with "mental fatigue". This means that the number of blinks increases as the degree of mental fatigue increases. By using this result, the evaluation device 20 can evaluate that the greater the number of times the user blinks, the greater the degree of mental fatigue of the user. Also, it can be seen that "item number 1: number of blinks" has a positive correlation with "PSQIG". This means that the number of blinks increases as the quality of sleep deteriorates. By using this result, the evaluation device 20 can evaluate that the user's sleep quality is worse (that is, the user's degree of mental fatigue or physical fatigue is greater) as the number of blinks of the user increases.

In addition, it can be seen that "item number 2: strength of blinking" and "item number 3: strength of blinking" have a negative correlation with "CESD". This means that the higher the depressive state, the weaker the strength of blinking. By using this result, the evaluation device 20 can evaluate that the user's depressive state is higher as the user's blink strength is weaker.

In addition, it can be seen that there is a high possibility that "item number 3: strength of blinking" has a negative correlation with "physical fatigue". This means that the greater the degree of physical fatigue, the weaker the strength of blinking. By using this result, the evaluation device 20 can evaluate that the user's degree of physical fatigue increases as the strength of the blinking of the user decreases.

In addition, "Item No. 4: Positive peak value among the values obtained by differentiating the waveform of blink intensity" and "Item No. 5: Positive peak value among values obtained by differentiating the waveform of blink intensity" It can be seen that there is a negative correlation with "CESD". This means that the higher the depressive state, the smaller the amount of change in blinking strength. By using this result, the evaluation device 20 can evaluate that the user's depressive state is higher as the amount of change in the strength of blinking of the user decreases.

In addition, "Item No. 6: Negative peak value among the values obtained by differentiating the blink intensity waveform" and "Item No. 7: Negative peak value among the values obtained by differentiating the blink intensity waveform" It can be seen that there is a positive correlation with "CESD". This means that the higher the depressive state, the smaller the amount of change in blinking strength. By using this result, the evaluation device 20 can evaluate that the user's depressive state is higher as the amount of change in the strength of blinking of the user decreases.

In addition, "Item No. 8: Time to blink" and "Item No. 9: Time to blink" have a positive correlation with "PSQI" (Pittsburgh Sleep Questionnaire score: an index representing the degree of sleep disturbance). I understand. This means that the worse the sleep quality, the longer the blink time. By using this result, the evaluation device 20 can evaluate that the degree of the user's sleep disturbance is greater as the user's blink time is longer.

Next, FIG. 8 will be described. LF (Low Frequency) is an index that indicates the function of the sympathetic nerves, and the higher the value, the more active the sympathetic nerves are. HF (High Frequency) is an index indicating the activity of the parasympathetic nerves of the subject, and the higher the value, the more active the activity of the parasympathetic nerves. Also, {HF+LF} is an index indicating the function of the entire autonomic nerve function, and is a value calculated by adding LF and HF. The higher the value of {HF+LF}, the more active the function of the autonomic nervous system as a whole. Note that "LF", "HF", and "{HF+LF}" correspond to the index B described above. In this evaluation, in order to normalize the autonomic nerve function index, all were logarithmized, and Log (LF), Log (HF), Log (HF + LF), Log (LF/HF) were used for the autonomic nerve function evaluation. used as an index.

FIG. 8(a) shows experimental results when Log(LF) and Log(HF) were measured when the eyes were closed (the subject's eyes were closed). According to FIG. 8(a), "Item No. 9: Blinking time" has a positive correlation with Log(HF+LF), Log(LF) and Log(HF) when the eyes are closed. there is This means that the more active the autonomic nerves, the sympathetic nerves, and the parasympathetic nerves, the longer the blinking time. Using this result, the evaluation device 20 can evaluate that the longer the blinking time of the user, the more active the autonomic nerve activity of the sympathetic nervous system and the parasympathetic nervous system.

FIG. 8(b) shows experimental results when Log(LF) and Log(HF) are measured when the eyes are open (the subject's eyes are open). According to FIG. 8(b), "item number 1: number of blinks" indicates that there is a negative correlation with Log(HF+LF) at the time of eye opening. This means that the number of blinks increases as the function of the autonomic nerves as a whole decreases. By using this result, the evaluation device 20 can evaluate that the autonomic nerve activity at the time of opening the eyes decreases as the number of blinks of the user increases.

Also, "Item No. 8: Blinking time" and "Item No. 9: Blinking time" show that there is a positive correlation with Log(HF+LF) at the time of eye opening. This means that the more active the function of the autonomic nerves, the longer the blinking time. Using this result, the evaluation device 20 can evaluate that the longer the blinking time of the user, the more active the autonomic nerve activity of the sympathetic nervous system and the parasympathetic nervous system.

Also, "Item No. 10: interval between blinks" indicates that there is a positive correlation with Log (HF+LF) at the time of eye opening. This means that the more active the function of the autonomic nerves, the longer the interval between blinks. By using this result, the evaluation device 20 can evaluate that the longer the interval between blinks of the user, the more active the autonomic nerve activity.

In addition, "item number 9: blinking time" indicates that there is a positive correlation with Log (LF) at the time of eye opening. This means that the more active the sympathetic nerves are, the longer the blinking time is. By using this result, the evaluation device 20 can evaluate that the longer the blinking time of the user, the more active the autonomic nerve activity of the sympathetic nervous system.

Next, FIG. 9 will be described. The "number of awakenings" indicates the number of awakenings during sleep. "METs" is an index that indicates how many times the metabolism (calorie consumption) is in a resting state during activity or exercise. It is an index that evaluates the exercise intensity per unit time when observing the period and sleep period). A larger value indicates a larger amount of activity per day. "Drowsy" indicates the number of times sleep was evaluated not only in the sleep segment but also in the wakeful segment. A higher value indicates more dozing (drowsiness, degree of dozing off) during wakefulness. "Awakening ZC" indicates the amount of activity per unit time when awake, and the larger the value, the more actively moving the subject. The “number of awakenings”, “total METs”, “drowsiness”, and “ZC at awakening” correspond to the index C described above.

According to FIG. 9, "item number 2: strength of blinking", "item number 3: strength of blinking", "item number 8: time of blinking", and "item number 9: time of blinking" ” indicates that there is a negative correlation with “number of awakenings”. This means that the greater the number of awakenings during nighttime sleep, the weaker the blinking strength and the shorter the blinking time. By using this result, the evaluation device 20 can determine that the weaker the blinking intensity or the shorter the blinking time, the more times the user wakes up during sleep (that is, the user's sleep quality is poor), and the sleep disorder. can be evaluated as being in a state of

In addition, "item number 4: positive peak value among the values obtained by differentiating the blink intensity waveform" indicates that there is a high possibility that there is a negative correlation with the "number of nocturnal awakenings". This means that the amount of change in blinking strength decreases as the number of midway awakenings increases. By using this result, the evaluation device 20 determines that the number of awakenings during sleep increases (that is, the quality of the user's sleep is poor) as the amount of change in blink intensity decreases, indicating a state of sleep disorder. can be evaluated as

In addition, "Item No. 6: Negative peak value among the values obtained by differentiating the blink intensity waveform" and "Item No. 7: Negative peak value among the values obtained by differentiating the blink intensity waveform" . This means that the amount of change in blinking strength decreases as the number of midway awakenings increases. By using this result, the evaluation device 20 determines that the number of awakenings during sleep increases (that is, the quality of the user's sleep is poor) as the amount of change in blink intensity decreases, indicating a state of sleep disorder. can be evaluated as

Also, "item number 2: strength of blinking" and "item number 8: duration of blinking" indicate that there is a high possibility that there is a negative correlation with "total METs". This means that the lower the daily activity level, the stronger the blinking strength and the longer the blinking time (the slower the blinking). By using this result, the evaluation device 20 can evaluate a state of fatigue in which the amount of daily activity decreases as the blinking intensity increases or as the blinking time increases. can.

In addition, "Item No. 6: Negative peak value among the values obtained by differentiating the blink intensity waveform" and "Item No. 7: Negative peak value among the values obtained by differentiating the blink intensity waveform" , indicating that there is a positive correlation with “total METs”. This means that the amount of change in blinking strength decreases as the amount of activity in a day decreases. By using this result, the evaluation device 20 can evaluate the fatigue state in which the amount of daily activity decreases as the amount of change in the strength of blinking decreases.

In addition, "item number 10: interval between blinks" indicates that there is a high possibility that there is a positive correlation with "total METs". This means that the lower the daily activity level, the shorter the interval between blinks. By using this result, the evaluation device 20 can evaluate that the shorter the interval between blinks, the lower the amount of daily activity, indicating a state of fatigue.

In addition, "Item No. 6: Negative peak value among the values obtained by differentiating the blink intensity waveform" and "Item No. 7: Negative peak value among the values obtained by differentiating the blink intensity waveform" , indicating that there is a negative correlation with “drowsiness”. This means that the amount of change in blinking strength decreases as the number of dozes increases. By using this result, the evaluation device 20 can evaluate the fatigue state in which the amount of daily activity decreases as the amount of change in the strength of blinking decreases.

Also, "item number 8: time to blink" and "item number 9: time to blink" show that there is a positive correlation with "drowsiness". This means that the more dozing off (drowsiness, degree of dozing off) during wakefulness, the longer the blinking time. By using this result, the evaluation device 20 can evaluate that the longer the blinking time is, the more fatigued the person is in a drowsy or dozing state even in wakefulness.

In addition, "item number 2: intensity of blinking" indicates that there is a high possibility that there is a positive correlation with "drowsiness". This means that the more dozing off (drowsiness, dozing off state) during wakefulness, the stronger the blinking strength. By using this result, the evaluation device 20 can evaluate that the stronger the blinking intensity is, the more fatigued the person is in a drowsy or dozing state even in wakefulness.

In addition, "item number 1: number of blinks" indicates that there is a negative correlation with "ZC during wakefulness". This means that the number of blinks decreases as the amount of activity per unit time during wakefulness increases. By using this result, the evaluation device 20 can evaluate that the smaller the number of blinks, the lower the amount of activity per unit time during wakefulness, indicating a state of fatigue.

In addition, "item number 10: interval between blinks" indicates that there is a positive correlation with "ZC during wakefulness". This means that the greater the amount of activity per unit time during wakefulness, the longer the interval between blinks. By using this result, the evaluation device 20 can evaluate the fatigue state in which the shorter the interval between blinks, the lower the amount of activity per unit time during wakefulness.

FIG. 10(a) shows the correlation between the standard deviation of measurement items 1 to 11 and "Calda", "CESD", "physical fatigue", "mental fatigue", "general fatigue" and "PSQIG". ing.

According to FIG. 10(a), the standard deviation (variation) of "Item No. 2: Strength of blinking" is negatively correlated with "CESD" and "physical fatigue". is shown. This indicates that the greater the degree of depression or the greater the degree of physical fatigue, the less variation in the strength of blinking. By using this result, the evaluation device 20 can evaluate that the user is more depressed and more physically fatigued as the variation in the strength of blinking of the user is smaller.

In addition, the magnitude of the standard deviation (variation) of “Item No. 4: positive peak value among the values obtained by differentiating the blink intensity waveform” was negative for “CESD” and “physical fatigue”. This indicates that there is a high possibility that there is a correlation between This indicates that the higher the depression state or the higher the degree of physical fatigue, the less variation there is in the amount of change in blinking strength. By using this result, the evaluation device 20 can evaluate that the user is more depressed and more physically fatigued as the variations in the amount of change in blinking intensity of the user are smaller.

In addition, the standard deviation (variation) of "Item No. 6: the negative peak value among the values obtained by differentiating the blink intensity waveform" It shows that there is a negative correlation with "fatigue". This indicates that the greater the degree of depression, the greater the degree of physical fatigue, or the greater the overall feeling of fatigue, the smaller the variation in the amount of change in blinking strength. By using this result, the evaluation device 20 determines that the smaller the variation in the amount of change in the strength of blinking of the user, the higher the depressed state, the higher the degree of physical fatigue, and the higher the overall fatigue. can be evaluated as

In addition, the magnitude of standard deviation (variation) of “item number 8: blink time” indicates that there is a negative correlation with “PSQIG”. This indicates that the worse the quality of sleep, the smaller the variation in the amount of change in the strength of blinking. By using this result, the evaluation device 20 determines that the user's sleep quality is poorer (that is, the user's degree of mental fatigue or physical fatigue is greater) as the variation in the intensity of blinking of the user decreases. can be evaluated.

In addition, the magnitude of standard deviation (variation) of “item number 10: interval between blinks” indicates that there is a negative correlation with “mental fatigue” and “PSQIG”. This indicates that the higher the mental fatigue or the worse the sleep quality, the less variation in blink intervals. By using this result, the evaluation device 20 can evaluate that the user's degree of mental fatigue or physical fatigue is greater as the variation in intervals between blinks of the user is smaller.

FIG. 10(b) shows the standard deviation of measurement items 1 to 11 and the "waking ZC", "waking METs", "total ZC", "total METs", "sleep efficiency", and "number of awakenings". showing correlation. Here, "METs during wakefulness" is an index for evaluating exercise intensity per unit time when observing wakefulness in 24 hours a day. Show big. “Total ZC” is a different index from “Total METs”, which evaluates exercise intensity per unit time when observing all 24 hours a day (including all wakeful and sleeping intervals). It indicates that the amount of activity per day is large. "Sleep efficiency" indicates the ratio of time spent actually asleep to time spent in bed.

According to FIG. 10(b), it is highly possible that the standard deviation (variation) of "item number 2: strength of blink" has a positive correlation with "total ZC". showing. This indicates that the greater the amount of activity per day, the greater the variation in the intensity of blinking. By using this result, the evaluation device 20 can evaluate that the user is in a state of fatigue in which the amount of activity per day decreases as the variation in the strength of blinking of the user decreases.

In addition, the standard deviation (variation) of "item number 4: the positive peak value among the values obtained by differentiating the blink intensity waveform" may have a positive correlation with "total ZC". It shows that it is highly resilient. This indicates that the greater the amount of activity per day, the greater the variation in the amount of change in blinking strength. By using this result, the evaluation device 20 can evaluate that the user is in a state of fatigue in which the amount of activity per day has decreased as the variation in the amount of change in the strength of blinking of the user decreases.

In addition, the magnitude of standard deviation (variation) of “item number 8: time to blink” indicates that there is a positive correlation with “ZC during wakefulness”. This indicates that the greater the amount of activity per unit time during wakefulness, the greater the variation in the amount of change in blinking strength. By using this result, the evaluation device 20 evaluates that the smaller the variation in the amount of change in the strength of the user's blinking, the more fatigued the user's activity level per unit time during wakefulness is. can do.

Moreover, the magnitude of standard deviation (variation) of “item number 8: time to blink” indicates that there is a negative correlation with “number of nocturnal awakenings”. This indicates that the larger the number of awakenings, the smaller the variations in the amount of change in blinking strength. By using this result, the evaluation device 20 can evaluate that the smaller the variation in the amount of change in blinking strength of the user, the more times the user wakes up during sleep (that is, the higher the fatigue level of the user). can.

In addition, the magnitude of standard deviation (variation) of “item number 10: interval between blinks” is positively correlated with “ZC during wakefulness”, “METs during wakefulness”, “total ZC” and “total METs”. indicates that there is This indicates that the larger the "amount of activity per unit time during wakefulness" and the larger the "amount of activity per day", the greater the variation in the interval between blinks. By using this result, the evaluation device 20 determines that the smaller the variation in the interval between blinks of the user, the more the user is in a state of fatigue in which the amount of activity per unit time during waking and the amount of activity per day are reduced. can be evaluated as

<Modification>
The evaluation unit 211 may evaluate the fatigue state of the user based on at least two or more pieces of biological information related to blinking that have a correlation with the same fatigue evaluation index. For example, as shown in FIGS. 7 and 10(a), the CESD has six standard deviations of item number 2, the standard deviation of item number 2, and the standard deviation of item numbers 3 to 5 and item number 6. It has a negative correlation with the biometric information and a positive correlation with the two items of item numbers 6 and 7 . Therefore, the evaluation unit 211 determines that at least two or more pieces of biological information (for example, item numbers 2 and 6) that have a correlation with CESD among the biological information corresponding to these item numbers are similar to the fatigue state of the user (e.g., item numbers 2 and 6). If it can be confirmed that the state of depression is strong/low depression/normal, etc., the user may evaluate that the user is in the fatigue state. This makes it possible to improve the accuracy of diagnosis compared to the case where the user's fatigue state is evaluated using only one type of biological information. Listed below are fatigue evaluation indices that are correlated (or likely to be correlated) with a plurality of biological information obtained from the experimental results shown in FIGS.

Item numbers positively correlated with "CESD": 6, 7
Item numbers negatively correlated with "CESD": 2, 3, 4, 5, 2 (SD), 6 (SD)
Item number positively correlated with “physical fatigue”: 3
Item numbers negatively correlated with "physical fatigue": 3, 2 (SD), 4 (SD), 6 (SD)
Item number positively correlated with "mental fatigue": 1
Item number that is negatively correlated with “mental fatigue”: 10 (SD)
Item number that is negatively correlated with “general fatigue”: 6 (SD)
Item numbers positively correlated with "PSQIG": 1, 8, 9
Item numbers negatively correlated with "PSQIG": 8 (SD), 10 (SD),
Item number that is positively correlated with "Closed eyes Log (HF + LF)": 9
Item number that is positively correlated with "Closed eyes Log (LF)": 9
Item number that is positively correlated with "Closed eyes Log (HF)": 9
Item numbers that are positively correlated with "Open eye Log (HF + LF)": 8, 9, 10
Item number that is positively correlated with "Closed eyes Log (LF)": 9
Item numbers that are positively correlated with "number of awakenings": 6, 7
Item numbers that are negatively correlated with "number of awakenings": 2, 3, 4, 8, 9, 8 (SD)
Item number positively correlated with "total METs": 6, 7, 10, 10 (SD)
Item numbers negatively correlated with “total METs”: 2, 8
Item numbers that are positively correlated with "drowsy": 2, 8, 9
Item numbers that are negatively correlated with "drowsiness": 6, 7
Item number positively correlated with "waking ZC": 10, 8 (SD), 10 (SD)
Item number that is negatively correlated with "Awakening ZC": 1
Item number that is positively correlated with "METs during wakefulness": 10 (SD)
Item number positively correlated with "total ZC": 4 (SD), 10 (SD)

<effect>
According to the present embodiment, the evaluation device 20 evaluates the state of fatigue based on the biological information regarding the blink of the user measured by the wearable terminal 10 . This makes it possible to more objectively evaluate the user's fatigue state compared to the method using the questionnaire. Further, according to the present embodiment, the wearable terminal 10 that the user can wear at all times uses biological information measured to evaluate the state of fatigue. As a result, the user can save the trouble of wearing the device each time the measurement is performed, and can more easily evaluate the state of fatigue.

<Others>
The embodiments described above are for facilitating the understanding of the present invention, and are not intended to limit and interpret the present invention. Flowcharts, sequences, elements included in the embodiments, their arrangement, materials, conditions, shapes, sizes, and the like described in the embodiments are not limited to those illustrated and can be changed as appropriate. Also, it is possible to partially replace or combine the configurations shown in different embodiments.

DESCRIPTION OF SYMBOLS 1... Fatigue evaluation system, 10... Wearable terminal, 11... CPU, 12... Storage device, 13... Electrooculography sensor, 14... 6-axis sensor, 15... Communication IF, 20... Evaluation device, 21... CPU, 22... Storage device , 23... input device, 24... output device, 25... communication IF, 110... measurement unit, 111... transmission unit, 210... acquisition unit, 211... evaluation unit, 220... correlation information

Claims (6)

An information processing device for evaluating a fatigue state of a user,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the depression state which is a fatigue evaluation index a storage unit that stores correlation information including the correlation with the index indicating the degree ;
an acquisition unit that acquires a plurality of pieces of biological information about blinks of the user that are measured using a sensor worn by the user;
an evaluation unit that evaluates the fatigue state of the user based on a plurality of pieces of biological information related to blinking of the user acquired by the acquisition unit;
has
The evaluation unit
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained by the obtaining unit, and among the obtained plurality of fatigue evaluation indices , evaluating the fatigue state of the user based on a plurality of biological information related to at least two or more of the user's blinks having a correlation with the same fatigue evaluation index ,
The weaker the blinking strength of the user and the smaller the amount of change in the blinking strength of the user, the higher the degree of depression of the user is evaluated.
Information processing equipment. An information processing device for evaluating a fatigue state of a user,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the autonomic nerves, which are fatigue evaluation indices a storage unit that stores correlation information including a correlation between an index related to performance and an index that indirectly indicates a state of fatigue;
an acquisition unit that acquires a plurality of pieces of biological information about blinks of the user that are measured using a sensor worn by the user;
an evaluation unit that evaluates the fatigue state of the user based on a plurality of pieces of biological information related to blinking of the user acquired by the acquisition unit;
has
The evaluation unit
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained by the obtaining unit, and among the obtained plurality of fatigue evaluation indices , evaluating the fatigue state of the user based on a plurality of biological information related to at least two or more of the user's blinks having a correlation with the same fatigue evaluation index,
The longer the blinking time of the user and the longer the blinking interval of the user, the more active the autonomic nerve activity of the user is evaluated.
Information processing equipment. A fatigue evaluation method executed by an information processing device for evaluating a user's fatigue state,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the depression state which is a fatigue evaluation index a step of storing, in a storage unit, correlation information including a correlation with an index indicating the degree ;
obtaining a plurality of biological information regarding blinks of the user measured using a sensor worn by the user;
evaluating the fatigue state of the user based on a plurality of pieces of acquired biological information relating to blinking of the user;
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained in the obtaining step; Among them, a step of evaluating the fatigue state of the user based on a plurality of pieces of biological information related to at least two blinks of the user that have a correlation with the same fatigue evaluation index;
a step of evaluating that the degree of depression of the user is higher as the strength of blinking of the user is weaker and the amount of change in the strength of blinking of the user is decreased;
Fatigue evaluation method having. A fatigue evaluation method executed by an information processing device for evaluating a user's fatigue state,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the autonomic nerves, which are fatigue evaluation indices a step of storing, in a storage unit, correlation information including a correlation between an index related to performance and an index that indirectly indicates a state of fatigue;
obtaining a plurality of biological information regarding blinks of the user measured using a sensor worn by the user;
evaluating the fatigue state of the user based on a plurality of pieces of acquired biological information relating to blinking of the user;
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained in the obtaining step; Among them, a step of evaluating the fatigue state of the user based on a plurality of pieces of biological information related to at least two blinks of the user that have a correlation with the same fatigue evaluation index;
evaluating that the user's autonomic nerve activity is more active as the user's blinking time is longer and the user's blinking interval is longer;
Fatigue evaluation method having. A computer that evaluates the user's fatigue state,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the depression state which is a fatigue evaluation index a step of storing, in a storage unit, correlation information including a correlation with an index indicating the degree ;
obtaining a plurality of biological information regarding blinks of the user measured using a sensor worn by the user;
evaluating the fatigue state of the user based on a plurality of pieces of acquired biological information relating to blinking of the user;
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained in the obtaining step; Among them, a step of evaluating the fatigue state of the user based on a plurality of pieces of biological information related to at least two blinks of the user that have a correlation with the same fatigue evaluation index;
a step of evaluating that the degree of depression of the user is higher as the strength of blinking of the user is weaker and the amount of change in the strength of blinking of the user is decreased;
program to run the A computer that evaluates the user's fatigue state,
Generated by statistically analyzing a plurality of biological information related to eye blinks obtained from a plurality of subjects and a plurality of fatigue evaluation indices obtained from the plurality of subjects and directly or indirectly indicating the state of fatigue. , correlation information indicating a correlation between a plurality of biological information relating to blinking and a plurality of fatigue evaluation indices, wherein the biological information relating to blinking obtained from a plurality of subjects and the autonomic nerves, which are fatigue evaluation indices a step of storing, in a storage unit, correlation information including a correlation between an index related to performance and an index that indirectly indicates a state of fatigue;
obtaining a plurality of biological information regarding blinks of the user measured using a sensor worn by the user;
evaluating the fatigue state of the user based on a plurality of pieces of acquired biological information relating to blinking of the user;
obtaining from the correlation information the plurality of fatigue evaluation indices showing a significant correlation with the plurality of pieces of biological information relating to blinking of the user obtained in the obtaining step; Among them, a step of evaluating the fatigue state of the user based on a plurality of pieces of biological information related to at least two blinks of the user that have a correlation with the same fatigue evaluation index;
evaluating that the user's autonomic nerve activity is more active as the user's blinking time is longer and the user's blinking interval is longer;
program to run the

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