JP2021122580A - Physical condition evaluation method and physical condition evaluation system - Google Patents

Abstract

To provide a physical condition evaluation method capable of accurately evaluating a physical condition in a short time from the start of data acquisition, as a physical condition evaluation method evaluating a physical condition based on biological information of a person to be evaluated.SOLUTION: A method comprises: a step of acquiring heartbeat data and acceleration data of a person to be evaluated 10 by a biological information acquisition unit 11; and a step of, on the basis of a plurality of pieces of the acquired heartbeat data and a plurality of pieces of the acquired acceleration data, obtaining a representative value 41 of the heartbeat data and a representative value 41 of the acceleration data. Using the representative value of the heartbeat data, the representative value of the acceleration data, and a predetermined coefficient 42, the method calculates a heartbeat exponent 43 of the person and evaluates the physical condition of the person.SELECTED DRAWING: Figure 4

Description

The present application relates to a physical condition evaluation method for evaluating the physical condition of the evaluated person based on biological information obtained from the evaluated person, and a physical condition evaluation system.

In recent years, the environment for connecting to the Internet such as wireless LAN has been improved, the development of means for transmitting information over short distances such as Bluetooth (registered trademark), high-performance mobile devices such as smartphones, and body temperature. With the spread of small sensor devices that can measure body data such as heart rate, sweating amount, etc., evaluation systems that evaluate the physical condition of the evaluated person based on the biological information of the evaluated person acquired by the sensor device, and evaluation results Based on this, a physical condition management system that manages the health condition of the evaluated person and reduces the risk of developing heat stroke, which has become a problem in recent years, has been put into practical use.

As an example of a physical condition evaluation system that evaluates and manages such physical condition, a wearable biological signal equipped with a three-dimensional acceleration sensor that grasps the movement of the body of the evaluated person and a biological information acquisition unit that detects the heartbeat is detected. Using the detector, the work load index showing the work intensity of the evaluated person, the heart rate index and physical fitness index of the evaluated person, and the heat stroke onset risk index are calculated to determine the heat stroke of the evaluated person. A system has been proposed in which the risk of developing the disease and the physical condition are evaluated and the evaluation result is fed back to the evaluated person (see Patent Document 1).

Japanese Unexamined Patent Publication No. 2019-185386

The conventional physical condition evaluation system has an electrometer that detects the wearer's heartbeat, a three-dimensional acceleration sensor that can detect the wearer's body movement, and a temperature sensor that can detect the temperature inside the clothes on the chest of the undershirt. A biometric information acquisition unit is arranged, and the biometric information acquired by the biometric information acquisition unit is transmitted to the information processing unit of a cloud server on the Internet via a communication device such as a smartphone possessed by the person to be measured. The information processing unit obtains the heart rate index estimated to be the resting heart rate of the evaluated person based on the regression line obtained from the correlation between the detected heart rate data and the acceleration data, and thus the physical condition of the evaluated person. To evaluate. In addition, the heat stroke onset risk index is calculated based on the work load index obtained based on the heart rate index and the slope of the regression line, and the heat load index obtained from the measurement result of the internal temperature.

In the conventional physical condition evaluation system in which the heart rate index is calculated based on the regression line obtained from the correlation between the heart rate data and the acceleration data of the evaluated person, the regression line is correctly calculated in order to accurately evaluate the physical condition. The number of data that can be obtained is required. For this reason, the specifications are such that the physical condition evaluation is started after acquiring data for about two hours, which is about half of the working hours in the morning, or for a whole day.

However, there is an expectation that the worker who is the evaluated person should evaluate the physical condition immediately after starting to use the physical condition evaluation system. In addition, since one regression line is calculated using the data obtained over 2 hours or more, at least the data acquired within this data accumulation period is sorted according to the acquisition time and used as time-series data. Can't. Furthermore, even if the physical condition of the evaluated person suddenly changes (deteriorates) within the data accumulation period, the physical condition evaluation system cannot detect the change in physical condition and take some measures.

The purpose of this application is to solve the problems of the above-mentioned prior art, and as a physical condition evaluation method and a physical condition evaluation system for evaluating physical condition based on the biological information of the evaluated person, in a short time from the start of data acquisition. It is an object of the present invention to provide a physical condition evaluation method capable of performing accurate physical condition evaluation and a physical condition evaluation system.

In order to solve the above problems, the physical condition evaluation method disclosed in the present application includes a step of acquiring heartbeat data and acceleration data of the evaluated person by the biological information acquisition unit, and a plurality of acquired heartbeat data and a plurality of the accelerations. The evaluated person uses the step of obtaining the representative value of the heartbeat data and the representative value of the acceleration data based on the data, and the representative value of the heartbeat data, the representative value of the acceleration data, and a predetermined coefficient. It is characterized in that the physical condition of the evaluated person is evaluated by calculating the heart rate index of.

Further, the physical condition evaluation system disclosed in the present application includes a biological information acquisition unit that acquires heartbeat data and acceleration data as biological information of the evaluated person, and the heartbeat of the evaluated person based on the acquired biological information. A data processing unit for calculating an index is provided, and the data processing unit obtains a representative value of the heartbeat data and a representative value of the acceleration data based on the acquired plurality of the heartbeat data and the plurality of acceleration data. It is characterized in that the heart rate index of the evaluated person is calculated by using the representative value of the heart rate data, the representative value of the acceleration data, and a predetermined coefficient.

With the above configuration, the physical condition evaluation method disclosed in the present application does not use the measurement result on the day of measurement as a predetermined coefficient required for obtaining the heart rate index, so that the heart rate index can be calculated from a small amount of measurement data. Therefore, it is possible to evaluate the physical condition immediately after the start of measurement, and it is possible to grasp the transition of the physical condition evaluation result.

Further, with the above configuration, the physical condition evaluation system disclosed in the present application can obtain a heart rate index which is an index of physical condition evaluation based on a small amount of measurement data, and evaluates the physical condition of the evaluated person in various forms. You can tell the result.

FIG. 1 is a block diagram illustrating a configuration example of a physical condition evaluation system described as an embodiment. FIG. 2 is a diagram illustrating a configuration of a biological information acquisition unit used in the physical condition evaluation system described in the present embodiment. FIG. 3 is a diagram illustrating a conventional process of obtaining a heart rate index of an evaluated person based on heart rate data and acceleration data. FIG. 4 is a diagram illustrating a step of obtaining a heart rate index at the time of data acquisition based on heart rate data, acceleration data, and a predetermined coefficient in the physical condition evaluation system according to the present embodiment. FIG. 5 is a diagram showing a display example for displaying the current physical condition evaluation result of the evaluated person. FIG. 6 is a diagram showing a first display example of displaying the transition of the physical condition evaluation result of the worker who is the evaluated person. FIG. 7 is a diagram showing a second display example of displaying the transition of the physical condition evaluation result of the worker who is the evaluated person. FIG. 8 is a diagram showing a display example for displaying the history of the physical condition evaluation result of the worker who is the evaluated person.

The physical condition evaluation method disclosed in the present application includes a step of acquiring heartbeat data and acceleration data of an evaluated person by a biological information acquisition unit, and the heartbeat based on the acquired plurality of the heartbeat data and the plurality of acceleration data. The heart rate index of the evaluated person is calculated using the step of obtaining the representative value of the data and the representative value of the acceleration data, the representative value of the heartbeat data, the representative value of the acceleration data, and a predetermined coefficient. Evaluate the physical condition of the evaluated person.

With the above configuration, the physical condition evaluation method disclosed in the present application can calculate the heart rate index as long as the number of data for which the representative values of each can be obtained as the heart rate data and the acceleration data. Therefore, the time until the start of the physical condition evaluation is shortened, and the real-time physical condition evaluation result in the time series can be obtained.

In the above physical condition evaluation method, the heart rate index is an estimated resting heart rate of the evaluated person calculated based on the heart rate data and the acceleration data, and is the resting heart rate and the heart rate in normal times. It is preferable to evaluate the physical condition of the evaluated person at the time of measurement from the deviation from the index. Since it is known that the resting heart rate rises when the person is in poor physical condition, the physical condition of the evaluated person at the time of measurement can be grasped from the heart rate index that estimates the resting heart rate.

Further, it is preferable that the representative value of the heart rate data and the representative value of the acceleration data are the median values of the data measured by the biometric information acquisition unit within a predetermined measurement period. The median value of the data acquired within the specified period is less susceptible to outliers and noise than the average value, so it is considered to be more suitable as a representative value used in the physical condition evaluation method where measurement errors may occur. Be done.

It is preferable that the predetermined coefficient is a heart rate response coefficient showing the correlation between the heart rate data and the acceleration data calculated based on the past measurement data of the evaluated person. A more accurate heart rate index can be calculated by using a coefficient that indicates the correlation between the heart rate data and the acceleration data, which is calculated based on the data of the evaluated person.

The physical condition evaluation system disclosed in the present application obtains the heart rate index of the evaluated person based on the biometric information acquisition unit that acquires the heartbeat data and the acceleration data as the biometric information of the evaluated person and the acquired biometric information. The data processing unit includes a data processing unit for calculating, and the data processing unit obtains a representative value of the heartbeat data and a representative value of the acceleration data based on the acquired plurality of the heartbeat data and the plurality of acceleration data, and the data processing unit is described. The heart rate index of the evaluated person is calculated by using the representative value of the heart rate data, the representative value of the acceleration data, and a predetermined coefficient.

With such a configuration, the physical condition evaluation system disclosed in the present application can evaluate the physical condition in a short time from the start of measurement and can update the physical condition evaluation result at any time. Therefore, it is possible to provide various useful physical condition evaluation results to the evaluated person.

The physical condition evaluation system further includes an image display unit for displaying the physical condition evaluation result, and the image display unit displays the degree of deviation between the resting heart rate of the evaluated person and the heart rate index on a map. It is preferable to do so. By doing so, the evaluated person can visually grasp whether or not he / she is in good physical condition at the present time.

Further, it is preferable that an image display unit for displaying the physical condition evaluation result is further provided, and the transition of the heart rate index is displayed on the image display unit. By doing so, it becomes possible to provide the evaluated person with an easy-to-understand change in physical condition and to use it for his / her own physical condition management.

Hereinafter, the physical condition evaluation method disclosed in the present application and the embodiment of the physical condition evaluation system will be described with reference to the drawings.

(Embodiment)
[Overall system configuration]
First, the overall configuration of an example of the physical condition evaluation system disclosed in the present application will be described.

The physical condition evaluation system described as an example in this embodiment is incorporated in a heat stroke risk management system that acquires biometric information of workers working at a construction site and evaluates and manages the heat stroke risk of each worker. It is a system that evaluates the physical condition of each worker as an evaluated person.

The physical condition evaluation system disclosed in the present application determines the physical condition by calculating a heart rate index corresponding to the resting heart rate of the evaluated person based on the heart rate data and acceleration data acquired as the biological information of the evaluated person. It is to evaluate. Therefore, as illustrated in this embodiment, various biometric information processing and evaluation systems that acquire heartbeat (pulse) information and acceleration information indicating body movement as biometric information of the evaluation target person and perform some evaluation. It can be easily incorporated into the system, and the obtained biometric information can be shared to provide a system that exerts a function of evaluating the physical condition of the evaluated person.

FIG. 1 is a block diagram showing a configuration example of each part of a heat stroke onset risk management system incorporating the physical condition evaluation system described in the present embodiment.

As shown in FIG. 1, the heat stroke onset risk management system incorporating the physical condition evaluation system evaluates the physical condition of the worker 10 who is the evaluated person and the worker 10 based on the biological information of the worker 10 and also causes the heat stroke. A cloud server 21 on the Internet 20 that evaluates the risk of onset, a site supervisor 30 that supervises a work group including a certain number of workers 10, and a plurality of site supervisors 30 are placed under the control. It is composed of business establishments 40 that grasp the whole and operate and maintain the heat stroke onset risk evaluation system.

The above is a general-purpose example assuming a general construction site, and when there is one worker 10 managed by one site supervisor 30, or when the site supervisor and the business establishment are inseparable. It goes without saying that different forms can be appropriately adopted depending on the configuration of the site where the heat stroke risk management system is actually introduced, such as when a plurality of business establishments are included and the entire construction site is managed on a larger scale.

In the physical condition evaluation system described in the present embodiment, the worker 10 wears an undershirt 18 in which a biosensor 11 which is a biometric information acquisition unit for acquiring his / her own biometric information is arranged on the chest.

FIG. 2 is a diagram showing a configuration example of an undershirt on which a biosensor is arranged, which is worn by an operator in the physical condition evaluation system described in the present embodiment. FIG. 2A shows the front surface of the undershirt, and FIG. 2B shows the back surface of the undershirt, that is, the side that faces and contacts the body surface of the worker.

As shown in FIG. 2, a biosensor 11 is arranged on the chest of the undershirt 18 worn by the worker 10. More specifically, the biosensor 11 is connected to a data acquisition transmission unit 11a arranged in the central portion of the chest of the surface 18a of the undershirt 18 and the data acquisition transmission unit 11a, and is connected to the back surface 18b of the undershirt 18. That is, it is composed of the electrode portion 11b of the heart rate sensor which is arranged so as to extend in the left-right direction on the portion on the side in contact with the skin.

In the physical condition evaluation system according to the present embodiment, the biological sensor 11 detects the heartbeat, the temperature inside the clothes, and the movement of the worker 10, and is a heartbeat detecting means (heartbeat sensor) arranged on the back surface of the undershirt 18. By contacting the electrodes with the chest, the heartbeat of the worker 10 can be detected more accurately. Further, a temperature sensor (not shown) for detecting the temperature inside the clothes and an acceleration sensor chip (not shown) for detecting acceleration in the three-dimensional direction are housed in the data acquisition transmission unit 11a.

The biosensor 11 and the smartphone 12 as a mobile terminal possessed by the worker 11 are always connected by short-distance communication such as Bluetooth (registered trademark), and various information acquired by the biosensor 11 can be obtained. It is sent to the smartphone 12 at any time.

The smartphone 12 includes a data receiving unit 15 and a data transmitting unit 16, and is always connected to the Internet 20 as a network environment via a wireless LAN or an information carrier of a mobile phone. In the physical condition evaluation system of the present embodiment, the function of the physical condition evaluation system is used to be associated with the identification data of each worker 10 by the smartphone 12, and the smartphone 12 has the evaluated person information transmitting unit 13. Using the data transmission function of the smartphone 12, the biometric information linked with the worker's identification information is transmitted to the cloud server 21 arranged on the Internet 20.

To link the measuring device worn by the worker with the ID that identifies the work itself, use the method of inputting the name and management number of the biosensor used by the worker into the smartphone, and the image recognition function of the smartphone. A method of reading a two-dimensional or three-dimensional identification code attached to the biosensor, a method of using the identification code in short-distance communication between the smartphone and the biosensor, and other applications on the smartphone by the worker. Various methods can be used, such as the method of selecting. In addition, if the smartphone is rented out as part of the system usage rather than the property of the individual worker, the worker who uses the smartphone can be identified by data entry using the smartphone, reading of the identification code, and face recognition system. You can register using the above or other methods.

In addition, the smartphone 12 can receive data, emit voice, and display an image. Utilizing this function, in the physical condition evaluation system according to the present embodiment, the physical condition evaluation result is fed back to the worker 10 by using the image display unit 17 of the smartphone 12. In addition, each function of the smartphone 12 includes a warning notification unit 14 for fulfilling a warning notification function for transmitting the risk of heat stroke to the worker 10 and prompting the worker to take a break in the heat stroke risk management system. The physical condition evaluation result of the worker 10 itself, and as a function of the heat stroke onset risk management system, to fulfill the function of displaying the heat stroke onset risk evaluation result for the entire group to which the worker 10 and the worker 10 belong in an easy-to-read manner. It is used as an image display unit 17.

The cloud server 21 includes a data receiving unit 23 and a data transmitting unit 26 inside, and exchanges information via the Internet 20. Further, the cloud server 21 includes an evaluation determination unit 22 as a data processing unit, acquires biometric information data of all 10 workers who are the targets of the physical condition evaluation system, and is in good or bad physical condition for each worker 10. Calculate the physical condition evaluation index indicating.

In addition, the evaluation determination unit 22 of the cloud server 21 also calculates a work load index indicating the magnitude of the load received by each worker 11 in the heat stroke onset risk management system and a heat load index. Based on these indexes, a heat stroke risk index indicating the degree of risk of each worker 10 developing heat stroke is calculated. Further, the evaluation determination unit 22 can manage the risk of developing heat stroke for a group of workers 10 formed by the work contents and the commonality of the work environment.

The heat stroke onset risk management system, which is also the physical condition evaluation system described in the present embodiment, manages the heat stroke onset risk of each worker 10, and when it is judged that the heat stroke onset risk is particularly high, the risk is changed. Communicate information and encourage the worker to take measures to reduce the risk of developing heat stroke. Therefore, the cloud server 21 evaluates and determines the risk of developing heat stroke, and creates warning information to warn the worker when the risk of developing heat stroke is increasing.

Further, the cloud server 21 has a weather information acquisition unit 25, acquires weather information from an information site that provides weather information via the Internet 20, and obtains the temperature in the area where the worker 10 is working. It is possible to obtain weather conditions at the current time such as humidity, humidity, and amount of sunshine, and weather forecasts that anticipate changes within the next few hours, and it is possible to add the weather conditions to the evaluation of the risk of developing heat stroke.

Further, the cloud server 21 includes a data recording unit 24, and measures biometric information from each of the workers 10 registered in the heat stroke onset risk management system, physical condition evaluation results, heat stroke onset risk index, and warning information. It is possible to record the creation history of the above in chronological order. As a result, for example, the physical condition of each worker 10 can be evaluated on-time on the day based on the results of the physical condition evaluation up to the present day or the day before, and the risk of developing heat stroke can be managed. Can be done. In addition, more accurate heat stroke risk assessment can be performed based on the past heat stroke risk assessment results under similar weather conditions.

The cloud server 21 is connected to the personal computer 31 as an administrator information terminal used by the site supervisor 30 who is the administrator who supervises the work of the worker 10 who is the evaluated person at the construction site via the Internet 20. .. Therefore, the site supervisor 30 at the work site where the worker 10 works is enthusiastic about the data of the biological information of the worker 10 transmitted from the cloud server 21 at any time by the data receiving unit 33 of the personal computer 31, the physical condition evaluation result, and the heat. It is possible to grasp the evaluation result of the disease onset risk, whether or not the warning information is generated by the evaluation determination unit 22, and the like.

The evaluation determination unit 22 of the cloud server 21 evaluates the physical condition of the worker 10 at any time based on the heart rate data, the acceleration data, and the temperature data in the clothes obtained from the biological sensor 11 worn by the worker 10. Further, the work load index is calculated, and the heat stroke onset risk index of the worker 10 is calculated by adding the temperature information in the clothes and the environmental temperature information of the work place acquired via the Internet.

The specific contents of the calculation of the heart rate index, which is an index for evaluating the physical condition of the worker 10, the calculation of the work load index, the calculation of the heat stroke onset risk index, and the onset risk evaluation performed by the evaluation determination unit 22. Will be described later.

The cloud server 21 includes historical data as past history information of the worker 10 to be determined recorded in the data recording unit 24, weather information of the work area acquired by the weather information acquisition unit 25, and further, the determination target. Based on environmental information such as changes in various information obtained from workers other than the worker to be judged who are working at the same site as the worker, the evaluation results of the heat stroke development risk of 10 individual workers are corrected. It is possible to manage the risk of developing heat stroke more realistically.

In the physical condition evaluation system illustrated in this embodiment, the cloud server 21 is not limited to the evaluation determination unit 22. For example, various functions of the cloud server 21 may be implemented on an administrator information terminal or a management computer of a business establishment, and as long as the functions can be realized, the place or device on which the evaluation determination unit is implemented does not matter. ..

Whether or not the personal computer 31 of the site supervisor 30 has generated various information and warning information obtained by the biosensor 11 for the worker 10 belonging to the work site supervised by the site supervisor 30 including the worker 10. The information management unit 32 for managing the above is provided. Based on the information transmitted from the cloud server 21, the information management unit 32 always obtains information obtained from each worker 10 and information that serves as a reference for heat stroke onset risk evaluation as to whether or not warning information has been generated. I keep it as the latest information. Further, the information management unit 32 outputs the acquired evaluation determination result of the heat stroke onset risk and other environmental information of each worker 10 to the display image processing unit 35, and the display image processing unit 35 displays the LCD monitor or the like. The screen content displayed on the device 36 is adjusted.

In this way, the on-site supervisor 30 grasps the information of the worker 10 working at the work site he supervises, the risk of developing heat stroke, etc. as a whole or as detailed information of each worker on an easy-to-read screen. can do. As for the specific screen contents displayed on the display device 36 processed by the display image processing unit 35, it is sufficient that the information required by the appropriately formed system can be displayed in an easy-to-read manner. Detailed description will be omitted.

In the physical condition evaluation system according to the present embodiment, the physical condition evaluation result of the worker 10 is displayed on the display screen of the smartphone 12 owned by the worker 10, but the evaluation result is displayed on the personal computer 31 of the site supervisor 30. It is set so that it cannot be grasped. This is because the on-site supervisor 30 can achieve the purpose of the system and be in good physical condition because if the heat stroke onset risk assessment result of each worker 10 is obtained, measures can be taken to reduce the heat stroke onset risk. The evaluation result is rather a result considering that each person has a strong tendency to grasp as a part of self-management, and the worker 10 tends to dislike the physical condition evaluation result from being known to others. It should be noted that how and to whom the physical condition evaluation result should be fed back depends on the purpose of the physical condition evaluation system and the position of the evaluator and manager, and it is considered that it should be set appropriately in each system. Be done.

On the personal computer 31 of the site supervisor 30, the worker 10 develops heat stroke by receiving the change in the biological information obtained from the worker 10 after notifying the warning information and the confirmation of receipt of the warning information from the worker 10. It is possible to confirm whether or not measures have been taken to prevent heat stroke, and if the worker 10 has not taken measures to prevent the onset of heat stroke, the target worker 10 is repeatedly warned. It is possible to further alert the worker 10 by transmitting the above.

In the above description, an example in which the evaluation determination unit 22 of the cloud server 21 generates warning information notifying the worker 10 that the risk of developing heat stroke is high has been described. It can be generated by the information management unit 32 installed in the personal computer 31 of the site supervisor 30. Further, both the evaluation determination unit 22 and the information management unit 32 can be set to generate warning information. By doing so, the personal computer 31 of the site supervisor 30 who actually supervises the work site generates warning information prior to the determination result of the evaluation determination unit 22 and transmits it to the target worker 10. Therefore, it may be possible to further reduce the risk of developing heat stroke depending on the actual situation at the work site.

The warning information generated by the evaluation determination unit 22 of the cloud server 21 or the personal computer 31 of the on-site supervisor 30 is transmitted from the data transmission unit 34 of the personal computer 31 of the on-site supervisor 30 to an information carrier of a local network such as a wireless LAN or a mobile phone. It is transmitted to the smartphone 12 equipped by the worker 10 via the network including the above. Upon receiving the warning information, the warning notification unit 14 of the smartphone 12 develops heat stroke for the worker 10 by using various information transmission means such as voice, screen display, lighting / blinking of the lamp, and vibration. Notify that the risk of doing so is increasing. The worker 10 who has confirmed the warning information reports that the warning information has been received through the touch panel or the operation buttons of the smartphone 12, and also implements measures to prevent heat stroke such as interrupting the work and taking a rest. ..

The smartphone 12 of the worker 10 transmits to the personal computer 31 of the supervisor 30 that the worker 10 has confirmed the warning information and interrupted the work, and the supervisor 30 prevents the worker 10 from developing heat stroke. You can confirm that you have taken measures.

Further, in the heat stroke onset risk management system described in the present embodiment, the heat stroke onset risk data at the work site grasped by the site supervisor 30 is transmitted to the smartphone 12 of the worker 10 so that the worker 10 can perform the heat stroke onset risk management system. , You can check the current risk of heat stroke at the work site where you work. For example, if it can be confirmed that the risk of heat stroke onset of workers other than oneself is high, each worker can take measures to actively prevent the onset of heat stroke. In addition, if it is found that there is another worker who has interrupted the work after receiving the warning information of the risk of developing heat stroke, it can be expected that he / she will respond obediently by the warning information addressed to himself / herself from the site supervisor 30.

As described above, in the smartphone 12 owned by the worker 10, the worker obtains the physical condition evaluation result information such as the current physical condition evaluation result of the worker 10 and the transition of the physical condition evaluation result in the past several days. It can be illustrated and displayed in a form that is easy to understand. A display example of this physical condition evaluation result will be described in detail later. In addition, the smartphone 12 possessed by the worker 11 displays on the screen related information such as the change in the risk of developing heat stroke of the worker 10 up to the present, his / her heart rate acquired by the biosensor 11, and the calorie consumption. Then, the worker 10 himself can refer to it. As for the display form of information other than the physical condition evaluation result, it is sufficient that necessary items can be displayed in an easy-to-read manner according to each display content and display purpose, and therefore detailed description in the present specification will be omitted.

The cloud server 21 is also connected to the management computer 41 in the company or business establishment 40 to which the worker 10 belongs via the Internet 20, and the measurement result information of the worker 10 transmitted to the personal computer 31 of the site supervisor 30 and the measurement result information of the worker 10. Various information used by the cloud server 21 for determining the risk of developing heat stroke is transmitted in real time to the management computer 41 of the business establishment 40. Since the management computer 41 of the office 40 includes its own data receiving unit 42 and data transmitting unit 43, it is also connected to the personal computer 31 of the site supervisor 30 via the Internet, and the site supervisor 30 to the worker 10 It is possible to confirm information such as whether the warning information is correctly transmitted to the computer and whether the worker 10 has taken preventive measures against heat stroke, and give a predetermined instruction as necessary. Therefore, it is possible to effectively back up the avoidance of the risk of heat stroke of the worker 10.

Further, since the cloud server 21, the personal computer 31 of the site supervisor 30, and the management computer 40 of the office 40 are connected on the Internet 20 environment, the cloud server 21 is accessed from the personal computer 31 and the management computer 40. It is possible to control the data processing contents of the cloud server 21, update the judgment program of the evaluation judgment unit 22, and appropriately retrieve the information necessary for heat stroke prevention management from the cloud server 21. ..

In the above description, a smartphone is illustrated as a mobile terminal equipped by a worker, but the mobile terminal of a worker is not limited to a smartphone, and is particularly limited to mobile phones, tablet devices, and heat stroke onset risk management systems. It is possible to use a dedicated small terminal device capable of transmitting and receiving information. In addition, as an administrator information terminal operated by the on-site supervisor, as an example computer, it is possible to send and receive information, display data, record data, etc. through a network such as a desktop computer, a laptop computer, a tablet computer, and a small server device. Various information devices can be adopted.

Further, in the above description, the form of transmitting the warning information from the manager information terminal of the site supervisor to the mobile terminal of the worker has been described, but when the warning information is generated by the evaluation judgment unit of the cloud server, the cloud server The system can also be configured to send warning information directly to the worker's mobile terminal.

Further, it goes without saying that the information transmission means connecting the worker, the site supervisor, and the management department in the business establishment is not limited to the above-exemplified one, and various information communication means for transmitting and receiving data can be used.

Further, in the physical condition evaluation system described in the present embodiment, in the arrangement example of the biosensor 11 that acquires the heartbeat, the temperature inside the clothes, and the movement of the worker 10, the biosensor 11 is fixed to the undershirt 18 shown in FIG. It is not limited to the method. For example, a method in which the biosensor 11 is placed in a highly adhesive sheet-shaped mounting cover and the biosensor 11 is directly attached to the chest, or a work using an elastic wearing belt capable of holding the biosensor 11 in close contact with the body. It is possible to adopt a method of placing it on the chest of a person. However, according to the method of fixing the biosensor 11 to the undershirt 18 worn by the worker 10 as shown in FIG. 2, as compared with the case where the worker 10 wears the biosensor 11 by another method. , It is possible to relax the special consciousness that the sensor is attached and acquire the necessary information. Further, even if the worker 10 sweats or the body is twisted during the work, the biosensor 11 fixed to the undershirt 18 does not come off from the body surface of the worker 10 and is attached to the undershirt 18. The position can also be maintained in a state where it does not change substantially. Therefore, although a part of the heartbeat of the worker 10 may not be acquired as heartbeat data, it is possible to avoid a situation in which the heartbeat data cannot be acquired at all.

In addition to the above-mentioned chest of the worker 10, the biosensor 11 for acquiring the heartbeat data and the acceleration data of the worker 10 is arranged at the waist, back, upper arms and legs of the worker 10. It is possible to adopt a form arranged in the above. Further, not as a system for managing the risk of developing heat stroke with the worker 10 working at the construction site as the evaluated person as described in the present embodiment, for example, when evaluating the physical condition of a sports player who is training. In such cases, it is conceivable that the evaluated person wears sportswear, and in this case as well, it is most rational to place the biosensor 11 on the chest of the wear worn on the upper body.

Further, in the physical condition evaluation system according to the present embodiment, the biosensor that can be adopted as the biometric information acquisition unit that acquires the heartbeat data that is the biometric information of the evaluated person detects the change in potential at the electrode unit as illustrated above. It is not limited to the one that acquires heart rate data. For example, an evaluated person wearing a sensor that detects a pulse by a method of optically detecting a change in the volume of a blood vessel of the evaluated person, or a sensor that is worn on the wrist and detects the pulsation of a blood vessel as vibration. Various sensors capable of detecting the heartbeat or pulse of the blood vessel can be adopted.

Further, the part for acquiring the heartbeat data of the evaluated person and the part for detecting the acceleration data indicating the movement of the body of the evaluated person do not have to be arranged in the same member as illustrated above, and are physically. They may be arranged in separate housings separated from each other. In detecting the movement of the entire body of the evaluated person, it is preferable that the acceleration sensor for detecting the acceleration data is arranged in a portion close to the trunk of the upper body of the evaluated person. For this reason, when adopting a wrist-worn wristwatch-type pulse sensor that acquires the heart rate data of the evaluated person, the acceleration sensor is placed in another measuring member, and the collar, chest pocket, etc. are placed. It is conceivable to use it so that it can be worn on the upper body of the evaluated person.

[Physical condition evaluation method]
Next, the physical condition evaluation method in the physical condition evaluation system according to the present embodiment will be specifically described.

In the physical condition evaluation system according to the present embodiment, the heartbeat data of the evaluated person detected by the heartbeat detecting means provided in the measuring device worn by the evaluated person and the body of the evaluated person at the time when the heartbeat data is obtained. The acceleration data acquired by the three-dimensional acceleration sensor, which is an index showing the movement of the subject, is acquired, and the heart rate index considered to correspond to the resting heart rate of the evaluated person is obtained from a plurality of data, and this heart rate index is obtained. Physical condition is evaluated by. In addition, as a heat stroke onset risk management system, a work load index indicating the work intensity of the worker is calculated based on the heart rate index, and further, the worker's clothing temperature obtained from the biosensor and the worker The heat load index of the worker is calculated based on the environmental temperature of the work site. Then, based on these calculated work load index and heat load index, a heat stroke onset risk index indicating the risk of developing heat stroke is calculated.

In the following description of the physical condition evaluation method and the method of calculating the heat stroke onset risk index, each component of the physical condition evaluation system according to the present embodiment described with reference to FIG. 1 will be described as an appropriate example.

In the physical condition evaluation method according to the present embodiment, when the acceleration data is 0 from the correlation between the heartbeat data and the acceleration data detected by the biological sensor 11 worn by the worker 10 who is the evaluated person. That is, the heart rate at rest when not exercising is estimated and the heart rate index HR0 is obtained. In general, when the person is in poor physical condition, the heart rate at rest is high. Therefore, when the heart rate index HR0 is larger than usual, it can be estimated that the person is in poor physical condition.

From the correlation between the heart rate data detected by the biological sensor 11 of the worker 10 who is the evaluated person and the acceleration data, the heart rate when the acceleration data is 0 is estimated to determine the physical condition of the worker 10. The method is a method introduced in the conventional heat stroke risk management system. In the conventional heat stroke onset risk management system, the heartbeat data and acceleration data of the worker 10 are collected over a certain period (for example, about 2 hours or more), and a regression line is obtained based on the entire collected data. Is obtained, and the value of the heartbeat when the acceleration data is 0 is defined as the heartbeat index HR0.

On the other hand, in the physical condition evaluation method shown in the present embodiment, the heartbeat data and the acceleration data are represented from the heartbeat data detected from the biological sensor 11 of the worker 10 who is the evaluated person and the values of several points of the acceleration data at that time. By obtaining a value and multiplying this representative value by a predetermined coefficient, the central heart rate value when the acceleration data is 0 is calculated, and that value is set as the heart rate index HR0. Therefore, as compared with the conventional case, the heart rate index of the worker can be obtained from the measurement result in a short time, the physical condition evaluation is started immediately after the start of the measurement, and the physical condition evaluation is performed in real time. Can be done. In addition, the change in the physical condition of the evaluated person can be grasped from the transition of the heart rate index HR0.

(Overview of heart rate index calculation method: Difference from conventional method)
FIG. 3 is a diagram illustrating a method for calculating a heart rate index adopted in a conventional heat stroke risk management system. In this specification, the heart rate index obtained by the conventional calculation method shown in FIG. 3 is expressed as HR00.

In the conventional heat stroke onset risk management system, the central heart rate (median value of the heart rate within a predetermined period) acquired by the biological sensor 11 of the worker 10 and the three dimensions when the central heart rate is acquired. As an example, the acceleration displacement obtained by the acceleration sensor is collected for 2 hours or more, more preferably for one working hour (about 8 hours). Then, a regression line is calculated from the correlation between the central heart rate and the acceleration displacement based on all the data collected during this predetermined period.

More specifically, as shown in FIG. 3, data corresponding to the condition that the acceleration displacement is 0.05 [G] or more and less than 0.4 [G] is divided into seven sections every 0.05 [G]. Divide and find the median of the median heart rate value and the acceleration displacement value in the section. “+” Marks 31 to 37 shown in FIG. 3 indicate the coordinates of the median value of the median heart rate value and the acceleration displacement in each acceleration displacement section. Then, the regression line 38 is obtained from the seven points thus obtained, and the value 39 of the y-axis section of the regression line 38 is set as the resting heart rate having the heart rate index HR00.

It should be noted that the data in which the acceleration displacement is 0.05 [G] or more and less than 0.4 [G] is used in the region where the amount of exercise and the heart rate change linearly with this degree of physical movement. This is because it is considered to be based on the findings found by big data. On the other hand, the data in which the acceleration displacement is less than 0.05 [G] is considered to be a region in which the heart rate is changed by emotions rather than body movements. Further, in the region where the acceleration displacement is 0.4 [G] or more, it is considered that the intensity of exercise and the increase in heart rate do not necessarily change linearly, and it is considered that the heart rate at rest is estimated in both cases. This is because it is considered that an error is likely to occur when it is used for this purpose. Thus, the numbers 0.05 [G] and 0.4 [G] themselves have no definitive meaning, and are considered to be the range in which the heart rate rises linearly with respect to the magnitude of body movement. The region can be selected as appropriate.

FIG. 4 is a diagram illustrating a method of calculating a heart rate index (HR0) adopted in the physical condition evaluation method according to the present embodiment.

As shown in FIG. 4, also in the physical condition evaluation method according to the present embodiment, the central heart rate acquired by the biological sensor 11 of the worker 10 and the three-dimensional acceleration sensor when the data was obtained were detected. It is the same in that the heart rate index corresponding to the central heart rate at rest is calculated by obtaining the y-axis section from the value of the acceleration displacement which is the acceleration data. However, as described above, in the conventional heat stroke onset risk management system, the heart rate index HR00 is calculated using the entire data collected over several hours, whereas in the physical condition evaluation system of the present embodiment, several points ( At the stage when the measurement result of 7 points) is obtained as an example, the median value of the heart rate value and the acceleration displacement is determined (indicated as "+" point 41 in FIG. 4), and a predetermined value is determined from this median value 41. Using a coefficient, that is, using a straight line having a predetermined inclination (the line indicated by reference numeral 42), the y-axis section 43 is obtained, and the value is set as the heart rate index HR0. By doing so, in the physical condition evaluation system according to the present embodiment, the physical condition of the worker is obtained from the central heart rate obtained from the heart rate data of the worker who is the evaluated person in a short time of about 10 minutes or less. Can be evaluated.

(Specific example of data processing in physical condition evaluation)
Hereinafter, the content of specific data processing for calculating the heart rate index from the biometric information of the evaluated person acquired from the biometric information acquisition unit will be described with respect to the physical condition evaluation method in the physical condition evaluation system according to the present embodiment.

a. Pre-processing First, pre-processing for calculating the heart rate index is performed on the heart rate data and acceleration data.

The preprocessing of the heart rate data is performed by calculating the central heart rate HR from the heart rate data detected by the biosensor 11 worn by the worker 10.

The raw data sampled from the biosensor may contain a certain percentage of noise (abnormal heartbeat data) due to the influence of poor contact between the skin of the evaluated person and the electrodes. Therefore, in order not to use the heartbeat data that was not detected correctly for the physical condition evaluation and the heat stroke onset risk evaluation, for example, the heartbeat interval is 0.33 seconds or more with respect to the data for each beat (heartbeat interval). Data with 1.33 seconds or less and a difference (difference heartbeat interval) from the previous data of 0.15 seconds or less is determined to be normal and labeled.

The threshold value for determining normality / abnormality can be arbitrarily set, but an appropriate numerical value may be set so as to remove impossible heartbeat interval data from a physiological point of view. Then, the measurement data is divided into k subsections with a predetermined time width, and the percentage of the data labeled as normal for each subsection is calculated as the heartbeat waveform detection rate Q in all the section data. .. When the heart rate waveform detection rate of a partial section is a predetermined value, for example, 50% or more, the heart rate data acquisition interval included in the partial section is converted into the heart rate per partial section (for example, per minute in the past). To obtain the central heart rate HR. Here, as the section representative value of each subsection, the average value of each subsection may be used, but since the center of the section is more preferable, the center value of the section is adopted in the present embodiment and is referred to as the median heart rate.

For the acceleration data obtained by the acceleration sensor, the average value ΔA for the past 1 minute is obtained by the following procedure.

1) Exponential moving average of unequal time interval data For acceleration data {Ax (t)}, {Ay (t)}, {Az (t)} in each of the x-axis, y-axis, and z-axis directions, set the time constants. With 10 sec, the exponential moving average of the acceleration data in each axial direction is obtained using the exponential moving average method, which is a statistical method. The time constant is not particularly limited, but may be appropriately determined according to the performance of the acceleration sensor, for example, in the range of 5 to 10 sec.

Here, the exponential moving averages in the x-axis, y-axis, and z-axis directions are {Sx (t)}, {Sy (t)}, and {Sz (t)}, respectively.

2) Removal of exponential moving average Remove the above-mentioned exponential moving average from the acceleration data of each axis to obtain the trend-removed time-series acceleration. For example, in the case of the x-axis, "Ax (t) -Sx (t) ".

3) Calculation of sum of squares For the trend-removed time-series acceleration, calculate the square at each time using the following formula (Equation 1) to obtain the sum.

4) Average of acceleration per minute Calculate the average value “ΔA ² _ave ” of the ^{sum of squares “ΔA 2 (t)” obtained above per minute.} Here, the average value is obtained by dividing by the number of data points. Moreover, to calculate the square root ".DELTA.A _ave" of the mean square acceleration ".DELTA.A ² _ave". Here, ΔA _ave is the acceleration deviation A _RMS .

b. Removal of abnormal values Regarding the heart rate data obtained from the heart rate data, non-numerical data and those having a heart rate of 40 or less and 180 or more are removed as abnormal values. For acceleration data, non-numerical data is excluded. These excluded data will not be used in subsequent calculations of the heart rate index.

c. Calculation of heart rate index HR0 In the physical condition evaluation method of the present embodiment, the acceleration displacement ΔA is 0.05 [G] or more and less than 0.25 [G] as a value corresponding to low work (about 3 METs or less) and rest. Only the data shown in Fig. 4) is adopted.

1) First physical condition evaluation after the start of measurement At the start of measurement, which is the start of one day's work, the acceleration displacement ΔA is 0.05 [G] as data after removing the abnormal values obtained from the worker 10. When the measurement data of 7 points is obtained in the range of more than 0.25 [G], the heart rate index HR0 at the start of measurement is calculated. In the calculation of the central heart rate, which is the heart rate index HR0, the weighted median values (xA, yHR) of the heart rate data and the acceleration data of the seven points obtained based on the measurement results of the seven points are obtained, and a predetermined value is obtained. By multiplying by a coefficient, the central heart rate when the acceleration displacement is 0 [G] is estimated, and this value is set as the heart rate index HR0.

Here, as the acceleration data, the weighted median value is obtained by using the data of 7 points obtained after the start of the evaluation as it is. On the other hand, the heart rate data includes two data in the range of 0.05 [G] or more and less than 0.25 [G] obtained at the time of the latest physical condition evaluation of the worker 10 in addition to the obtained 7 points data, for example. , The median weighting in the range where the acceleration displacement is 0.05 [G] or more and less than 0.10 [G] and 0.20 [G] or more in the heart rate data acquired at the time of the physical condition evaluation of the worker on the previous day. The median weighting is obtained from the heart rate data of a total of 9 points, which is the sum of 2 points with the median weighting in the range of less than 0.25 [G]. By doing so, it is possible to prevent an abnormal deviation from the standard value.

As the predetermined coefficient, the slope (αHR) of the regression line between the heart rate data and the acceleration data obtained as the measurement result of one day at the time of the latest physical condition evaluation of the worker 10 is used. As the method of obtaining the regression line, the method of obtaining the regression line when obtaining the work load index in the conventional heat stroke onset risk management system described above using FIG. 3 can be adopted as it is. Specifically, the acceleration displacement is 0.05 [. It can be calculated from the weighted median within the interval of, for example, every 0.05 [G] in the range of [G] or more and less than 0.40 [G].

Then, the median value (xA, yHR) of the heart rate data and the acceleration data obtained based on the data of the seven points measured first is used with the coefficient αHR obtained as the measurement result of the previous day of the worker. Then, using the following formula, the heart rate index HR0 as the estimated median heart rate at rest, which is a y-axis section, is calculated as shown in FIG.
HR0 = yHR-αHR × xA.

When the worker to be evaluated becomes the evaluation target of the physical condition evaluation system according to the present embodiment for the first time, the data of 2 points to be added to the 7 points obtained as the measurement result as the heart rate data, and the heart rate index HR0. As a predetermined coefficient used in the calculation of, standard data that can be considered as a standard numerical value is substituted. As this standard data, the average value or the median value of all the workers at the work site where the worker to be measured works can be used. In addition, the measurement results of a group of workers who are engaged in the same work as the worker who is the evaluated person at the work site, and the physique, age, gender, etc. of the height, weight, etc. are similar to the worker who is the evaluated person. Numerical values that are considered appropriate to be substituted as numerical values representing the standard condition of the evaluated person, such as the measurement results of the group, can be appropriately adopted.

2) Second and subsequent physical condition evaluation After calculating the first heart rate index HR0 as described above, as an example, the heart rate index HR0 is calculated at predetermined intervals of 10 minutes to update the physical condition evaluation. The heart rate data and acceleration data used to calculate the heart rate index use all the data acquired up to the time of evaluation, but do not use the data for which a predetermined time (2 hours as an example) has passed at the time of evaluation, but at the time of evaluation. The heart rate index is calculated using only the heart rate data and the acceleration data that have not passed 2 hours since the acquisition. That is, the data used for calculating the heart rate index increases until 2 hours have passed from the start of measurement, but after 2 hours have passed from the start of evaluation, the calculation target data is sequentially replaced by the above method. Calculate the heart rate index.

In this case, if the number of points satisfying the condition that the acceleration displacement ΔA is 0.05 [G] or more and less than 0.25 [G] is 8 points or less, the data satisfying the condition (8 or less) is used for the acceleration data. The median weighting is calculated using all of them and used as yHR. Regarding the heart rate data, the median weighting is calculated for a maximum of 10 data obtained by adding the same two data as the data used at the time of the first physical condition evaluation to the data satisfying the conditions, and is set as xA.

The predetermined coefficient (αHR = slope of the regression line) used for calculating the heart rate index is the same value without replacement on the day of measurement.

In addition, in order to prevent large fluctuations in the heart rate index that occur when the measurement accuracy is low, the fluctuation range with the value of the heart rate index calculated immediately before (10 minutes ago) is within a predetermined range (± 5 ppm as an example). It is also conceivable to adopt a measure that suppresses the value within).

3) Calculation of the index after the end of the day's measurement When the day's measurement is completed, the intercept center heart rate (heart rate index) HR (day) and heart rate response coefficient (slope of a line of regression) α (day) of the day And are calculated.

First, the data having an acceleration deviation of 0.05 [G] or more is divided into two subsections I1 and I2 having an acceleration deviation of 0.05 to 0.25 and 0.25 to 0.45.

If the number of data in each of I1 and I2 is less than the predetermined number (20 points as an example), the value of the heart rate index HR obtained at the end of the day is adopted as HR (day) without calculating the value. Then, the numerical value 54.1 is adopted as α (day).

When there are 20 points or more of data in the partial sections I1 and I2, the median yI1 and yI2 of the heartbeat data and the median xI1 and xI2 of the acceleration data are obtained for the data in each partial section, and 2 points (2 points ( Find the equation of a straight line passing through xI1, yI1) and (xI2, yI2), and let the y-axis intercept be HR (day) and its slope be α (day).

That is,
HR (day) = yI1-xI1 · (yI2-yI1) / (xI2-xI1)
α (day) = (yI2-yI1) / (xI2-xI1)
Will be.

However, if the HR (day) is 45 bpm or less or 105 bpm or more, or if the α (day) is 20 or less or 100 or more, it is judged to be an abnormal value and the boundary value is adopted. do.

In addition, in order to obtain the physical fitness index PI at the end of the day, that is, the value obtained by normalizing the degree of increase in heart rate due to the body movement of the worker 10 who is the evaluated person with standardized data, PI (day). ) = Α (day) /54.1.

4) Physical condition evaluation after the second day Regarding the physical condition evaluation method after the second day, the above-mentioned procedure is repeated as it is for the calculation method of the heart rate index. As the coefficient α (HR) when calculating the heart rate index and the data to be added to the 7 points of the measurement data at the time of calculating the first heart rate index, the data of the first day, which is the previous day, can be used.

In the physical condition evaluation after the second day, when calculating the index for one day after the measurement is completed, when the number of data satisfying the conditions in the two subsections I1 and I2 is less than the predetermined number 20, HR ( As the values of day) and α (day), the value of HR (day) obtained on the previous day or the value obtained most recently, the value of α (day) obtained on the previous day or the value obtained most recently, respectively. The only difference is that

(Evaluation of physical condition by heart rate index)
As described above, in the physical condition evaluation method according to the present embodiment, based on the heart rate data and the acceleration data acquired by the biometric information acquisition unit worn on the chest by the evaluated person, immediately after the start of measurement and Every predetermined interval (10 minutes in the above example), a heart rate index that can be assumed to be the resting heart rate of the evaluated person can be calculated.

When the evaluated person is in poor physical condition, the heart rate increases even if the same load operation is performed because the amount of activity decreases. Further, for example, when the temperature at the work site is high, the core body temperature rises due to a large amount of heat stress, so that the heart rate also rises even when the same load operation is performed. In such a case, in the graph showing the correlation between the acceleration displacement and the central heart rate shown as FIGS. 3 and 4, the distribution of the coordinate points representing the measurement data moves upward or diagonally upward. In the physical condition evaluation method shown in the present embodiment, the value of the y-axis section indicating the resting heart rate is obtained from the coordinates indicating the median value of the central heart rate and the median value of the acceleration displacement using a line having a predetermined inclination. Therefore, in the case of poor physical condition, the numerical value HR0 becomes large. By using this, it is possible to grasp the physical condition of the evaluated person at the time of acquiring the biological data.

If the evaluated person is drowsy or has an imbalance of the independent nerve (parasympathetic tone), the heartbeat data itself becomes a small value, so that the acceleration displacement and the center shown in FIGS. 3 and 4 are shown. In the graph showing the correlation with the heart rate, the heart rate index HR0, which is the y-axis intercept, has a small value.

Using this, the current physical condition of the evaluated person can be shown as a map based on the obtained value of the heart rate index HR0.

FIG. 5 is a diagram showing an example of a map displaying the evaluation result of the physical condition evaluation method according to the present embodiment.

FIG. 5A shows an evaluation map of worker A, and FIG. 5B shows an evaluation map of worker B.

Both of the two evaluation maps show the heart rate index on the vertical axis and the physical fitness index on the horizontal axis. The range 53 of the "attention" state in which the person is in poor physical condition is shown so that the display pattern and the display color can be changed so that the range 53 can be grasped at a glance. The current (most recent) physical condition evaluation results of each worker are indicated by marks (circles) indicating as reference numerals 54 in the case of worker A and reference numeral 55 in the case of worker B.

For example, in the case shown in FIG. 5, the worker A is in a state of being slightly ill from the display mark 54 and needs a little attention, and the worker B is in a state of being ill from the display mark 55 at present than usual. It is in the state of "Caution", which indicates that it is a state to be careful when performing work that requires a heavy load.

The "normal" range and the "slightly careful" range on the physical condition evaluation map for each worker are the value of the heart rate index HR (day) obtained from the daily measurement results by the physical condition evaluation system. It is obtained by applying statistical processing to the above-mentioned value of the physical fitness index PI (day), which is a standardized value of α (day).

For example, the "normal" range can be set to the 95% existence area, and the "slightly careful" range can be set to the 98% existence area. In addition, since the physical condition evaluation result over one day is required as data, if the number of days for the worker to be evaluated to receive the physical condition evaluation by the physical condition evaluation method according to this embodiment is small, it is tentatively provided as shown below. The value is used to determine the range of "normal" and "caution" shown on the physical condition evaluation map.

First, if the worker who is the evaluated person uses the system on the first day or the second day, that is, if the past data is less than two days, the provisional average heart rate index and its provisional average heart rate index and its provisional The standard deviation will be used.

Specifically, as a standard value calculated based on the analysis of big data, as an example, the average heart rate HR (day) _ave = 77.4 [bpm], and the provisional standard deviation σHR (day) = 7. 8 [bpm] is used. Similarly, for the physical fitness index, the provisional average value PI (day) _ave = 1.0 and the provisional standard deviation σPI (day) = 0.35 are used.

As a result, the range of "as usual" is
Heart rate index HR (day) is 77.4 ± 1.96 × 7.8 [bpm]
Physical fitness index PI (day) is 1.0 ± 1.96 × 0.35
Next,
The range of "somewhat caution" is
Heart rate index HR (day) is 77.4 ± 2.33 × 7.8 [bpm]
Physical fitness index PI (day) is 1.0 ± 2.33 × 0.35
Will be.

From the 3rd to the 5th day when the daily measurement data in the physical condition evaluation system exists for 2 days or more and 4 days or less, the average value of the heart rate index and the physical fitness index is obtained from the past measurement data of the worker. The average heart rate index HR (day) _ave and the average physical fitness index PI (day) _ave are used, and the above-mentioned provisional value is used as the standard deviation value which is the standard of the width. By doing so, it is possible to create an evaluation result map that more reflects the physical condition of the worker who is the evaluated person.

Specifically, the range of "as usual" is
Heart rate index HR (day) is HR (day) _ave ± 1.96 × 7.8 [bpm]
Physical fitness index PI (day) is PI (day) _ave ± 1.96 × 0.35
Next,
The range of "somewhat caution" is
Heart rate index HR (day) is HR (day) _ave ± 2.33 × 7.8 [bpm]
Physical fitness index PI (day) is PI (day) _ave ± 2.33 × 0.35
Will be.

From the 6th day onward, since the worker's heart rate index data and physical fitness index data have been accumulated for 5 days or more, the measured values obtained from the measurement results are used for both the average value and the standard deviation.

That is, the range of "as usual" is
Heart rate index HR (day),
HR (day) _ave ± 1.96 × σ _{HR (day) ave} [bpm]
Physical fitness index PI (day),
PI (day) _ave ± 1.96 × σ _{PI (day) ave}
Next,
The range of "somewhat caution" is
Heart rate index HR (day),
HR (day) _ave ± 2.33 × σ _{HR (day) ave} [bpm]
Physical fitness index PI (day),
PI (day) _ave ± 2.33 × σ _{PI (day) ave}
Will be.

Next, another display method of the physical condition evaluation result in the physical condition evaluation method according to the present embodiment will be described.

FIG. 6 is an example of the first display screen showing the transition of the physical condition evaluation result in the physical condition evaluation method according to the present embodiment.

In this first display example, as shown in FIG. 6, regarding the physical condition evaluation result of the worker 10 who is the evaluated person, the transition for each measurement day is shown on the left side, and the transition for the measurement time on the measurement day is shown on the right side. Each is shown.

In particular, in the physical condition evaluation method according to the present embodiment, the physical condition can be evaluated at a predetermined time interval (10 minutes in the above example), so that the physical condition evaluation result for each hour on the day as shown on the right side of FIG. Can show the transition of. As a result, the evaluated person can grasp whether or not his / her physical condition on the measurement day is good or bad by comparing with the average physical condition evaluation results for the past several days on the left side of FIG. 6, and FIG. As shown, it is possible to objectively grasp the change in one's physical condition, such as the fact that the physical condition was not good around noon. For this reason, the cause of the illness is the work environment of the day, or the cause of the illness in light of one's own condition, such as whether the person is not resting enough the day before and is dragging fatigue. Can be considered.

As a result, for example, the next day, it is possible to select and implement measures for managing one's physical condition, such as improving measures against heat and taking sufficient rest to recover from fatigue. Since the physical condition evaluation result is information with a relatively high degree of privacy, it is expected that consideration such as detailed disclosure of the physical condition evaluation result will be limited only to the evaluated person himself / herself. ..

FIG. 7 is an example of a second display screen showing a transition of the physical condition evaluation result in the physical condition evaluation method according to the present embodiment.

This second display example tells the worker 10 who is the evaluated person whether his / her current physical condition evaluation result is in the normal range, or is in the range of caution or caution. It is displayed in an easy-to-understand manner. Specifically, as shown in FIGS. 7 (a) and 7 (b), the value of the heart rate index, which is the current physical condition evaluation result of the worker 10, is indicated by a predetermined mark (reference numeral 71, reference numeral 71, etc.) such as a circle. It is represented by 71'). The predetermined marks (reference numerals 71, 71') move to the right in the figure each time the physical condition evaluation result is updated. At this time, at the same time as the marks (reference numerals 71, 71'), a frame 72 indicating a normal range of the physical condition evaluation result and a frame 73 indicating a slightly caution range are displayed. By doing so, the physical condition evaluation result, which was in the normal range 72 at the time of FIG. 7 (a), is slightly out of the range of attention 73 at the time of FIG. 7 (b), which is a little later, and attention is paid. You can visually grasp that you are in the area. By doing so, the worker 10 can immediately grasp a sudden change in his / her physical condition evaluation result.

FIG. 8 is a display example of the physical condition evaluation result in the physical condition evaluation method according to the present embodiment, and is a display example in the case of clearly showing the history of the physical condition evaluation result.

The history display example shown in FIG. 8 shows the past (7 days as an example in this example) physical condition evaluation result of the worker 10 who is the evaluated person, and the display example of the physical condition evaluation result illustrated in FIG. Similar to the one shown on the left side of the above, the display for telling the worker 10 the result of the physical condition evaluation for the past several days is shown. In the left part of FIG. 6, the average daily physical condition evaluation result on the measurement day is shown as one point, but in FIG. 8, the transition of the daily physical condition evaluation result is compressed in the width direction and displayed. The difference is that they are.

In the physical condition evaluation method according to the present embodiment, since the transition of the physical condition evaluation result of the evaluated person can be grasped, as shown in FIG. 8, the physical condition evaluation result for each measurement day can be displayed so that the transition is clear. can. In this way, by displaying the transition of the physical condition evaluation result for one day over a plurality of measurement days, the worker 10 can perform the heart rate index HR0 on each measurement day together with the overall height of the heart rate index HR0 for each measurement day. It is possible to grasp the tendency of fluctuations in. As a result, the worker 10 has a tendency of a time zone in which his / her heart rate index HR0 is high, or a day when the heart rate index HR0 is high (or low) has a higher (lower) value in the afternoon than a value in the morning. You can grasp the fluctuation tendency of your own heart rate index HR0 at a glance.

Further, in FIGS. 6, 7, and 8, the boundaries of each evaluation range such as “normal”, “slightly careful”, and “caution” and the size (width) of each range are the past of the worker 10 as described above. It may be updated at any time using the measurement data. For example, the average value of the past heart rate index HR0 may be updated on a daily basis, and each evaluation range may be recalculated. That is, the width and position of each evaluation range on the vertical axis of FIGS. 6, 7, and 8 are variable, and the range display can be changed every day, for example. As a result, as the accumulated data increases, it is possible to display the physical condition evaluation result optimized for the individual worker.

The display method for notifying the operator who is the evaluated person of the evaluation result of the physical condition evaluation method according to the present embodiment is not limited to that shown in FIGS. 6, 7, and 8. Taking advantage of the ability to grasp your own physical condition evaluation results in real time, you can display only one of the physical condition evaluation results such as "normal", "slightly careful", and "attention" at any time, or you can display the physical condition evaluation results in chronological order. Taking advantage of the features that can be grasped, various things such as displaying the transition of the physical condition evaluation result on the previous day or the specific day specified by the worker and the transition on the current day in an overlapping manner so that the difference can be easily grasped. The display method of is conceivable.

In addition, regarding the display of the physical condition evaluation result, a method of displaying using the entire screen of a display medium such as a smartphone by being operated by an operator, for example, along with the evaluation result of the risk of developing heat stroke, is always displayed on a part of the screen. The display timing and display size, such as the method of displaying the physical condition evaluation result, can be appropriately selected.

By displaying the physical condition evaluation result as an easy-to-understand display screen in this way, the merit of the physical condition evaluation method according to the present embodiment that the physical condition evaluation can be performed at any time can be utilized more effectively.

[Heat stroke risk assessment method]
Here, the heat stroke onset risk evaluation method in the heat stroke onset risk management system equipped with the physical condition evaluation system according to the present embodiment will be briefly described.

As described above, the evaluation of the risk of developing heat stroke is performed by the work load index calculated using the heart rate data and the acceleration data acquired by the biosensor 11 worn by the worker 10 who is the evaluated person, and the biosensor 11. It is obtained from the heat load index of the worker 10 calculated from the obtained in-clothes temperature data and the environmental temperature data.

<Calculation of work load index>
With respect to the heart rate data and the acceleration data for calculating the work load index, the above-mentioned "a preprocessing" and "b removal of abnormal values" of the measurement data are performed as specific examples of the physical condition evaluation method.

In the physical condition evaluation method, the data when the heart rate waveform detection rate was less than the predetermined value (50%) was not used in the calculation of the heart rate index, but in the calculation of the work load index in the heat stroke onset risk evaluation, the heart rate was calculated. The difference is that when the detection rate is less than a predetermined value, only the acceleration data is used without using the heart rate data.

Data acquired during a predetermined time (2 hours as an example) or more as shown in FIG. 3 based on the central heart rate, which is the heart rate data obtained in each subsection, and the acceleration deviation, which is the acceleration data. A regression line is calculated from the above, and the slope is defined as the heart rate response coefficient αr, and the y-axis section is defined as the section heart rate βr.

Next, the central heart rate HR obtained in each subsection is converted into standardized heart rate HRs using the following (Equation 2).

HRs = (αs / αr) (HR-βr) + βs (Equation 2)
In the above equation (2), αs is the standard response heart rate and βs is the standard intercept heart rate, and the slope of the regression line in the standard heart rate response model considered to show the correlation between the standard heart rate data and the acceleration data. (Αs) and the value of the y-axis intercept (βs).

The standard heart rate response model is a heart rate response model created based on large-scale data obtained by measuring a large number of people. It is a model that represents the standard human heartbeat response to acceleration (body movement) and can be expressed by various parameters and predetermined mathematical formulas. In the heat stroke onset risk management system according to the present embodiment, the standard heart rate response coefficient αs and the standard section heart rate βs are obtained by using the regression line between the heart rate data and the acceleration data by the method shown in FIG.

The large-scale data may be data of a plurality of workers at the site for the past several days, or may be accumulated data sampled in advance at another site. Preferably, it is preferable to create a standard heart rate response model based on a large-scale data obtained by measuring a large number of workers who are engaged in the same work as the worker. This is a heart rate response model optimized for the task and is considered to represent the typical heart rate response of the worker engaged in the task. The number of people on which large-scale data is based is not particularly limited, but the larger the number of samples, the more accurately the heart rate response can be approximated. The number is preferably 5 or more, more preferably 50 or more. The accumulation period is not particularly limited, but it is preferable to acquire data of 2 days or more, more preferably 5 days or more at the same site.

By calculating the standardized heart rate HR _S in this way, it is possible to correct individual differences in calculating the work load index from the heart rate data based on the characteristics of each worker who is the evaluated person.

In addition, when the detection rate of heart rate data is low and the work load index is calculated using only the acceleration data, it is converted to the work load index using a predetermined mathematical formula such as multiplying the acceleration deviation, which is the acceleration data, by an appropriate coefficient. do it. In addition, an estimated standardized heart rate calculated based on the value of the acceleration deviation and a function (correlation curve) showing the correlation between the heart rate data calculated from the standard heart rate response model and the acceleration data can be used.

Based on the standardized heart rate and the acceleration deviation obtained in this way, the evaluation determination unit 22 calculates the work load index of the worker 10. At this time, the evaluation determination unit 22 determines whether to use the standardized heart rate or the estimated standardized heart rate. Further, the evaluation determination unit 22 determines the corrected heart rate HRc used for calculating the work load index by using the correction map created based on the standardized heart rate response model.

As the correction map, the one showing the correlation between the heart rate data and the acceleration data is used, and the data on the upper side and the data on the lower side of the correlation curve showing the standard heart rate response model according to the magnitude of the acceleration data are used as the measurement data. It is indicated whether the standardized heart rate HRs obtained based on the data is used as it is as the corrected heart rate HRc, or the value of the correlation curve or the corrected heart rate HRc shown as the specified value on the map is used. In addition, as a correction map, a map to be used when the heart rate detection rate is high is prepared separately, and when the heart rate detection rate is high, the degree of adopting the standardized heart rate is improved to more accurately follow the actual situation. It is possible to calculate the work load index.

Based on the corrected heart rate HR _c obtained using the correction map, the work load index W is calculated as follows.

_{First, the corrected heart rate HR c} is converted into metabolic equivalents METs (Metabolic equivalents) using the following mathematical formula (Equation 3).

METs = a _METs × HR _c + b _METs (Equation 3)
Here, a _METs and b _METs are predetermined parameters and can be determined based on a respiratory measurement experiment.

Next, the metabolic equivalents METs are converted into the workload index W using the following mathematical formula (Equation 4).

W = a _W × METs + b _W (Equation 4)
Here, a _W and b _W are predetermined parameters.

For example, when a _W = 0,2 and b _W = -0.2 are set, as an evaluation of the work load, if the work load index W is 0.6 or more, the work with a high metabolic rate, that is, the burden is When it is a large work and the value of W is 1 or more, it can be a work having an extremely high metabolic rate, that is, a work having a very large burden on the worker.

<Evaluation of heat load>
The evaluation determination unit 22 calculates the heat load index of the worker 10 based on the clothing temperature data of the worker 10 obtained from the biosensor 11 and the environmental temperature data of the worker 10 at the work site. .. The environmental temperature data of the work site is the temperature data around the work site acquired by the weather information acquisition unit 25 of the cloud server 21, and the temperature arranged in the work site when the worker is working indoors. It can be acquired based on the temperature information obtained from the sensor.

Using the clothing temperature Ti obtained by the measuring device 11 and the outside air temperature To obtained as the environmental temperature, the heat load index H is calculated by the following equation (Equation 5).

If the heat load index H is smaller than 0, H = 0.

When the heat load index H is 0.6 or more, it can be evaluated that the heat load is relatively high, and when the heat load index H is 1 or more, it can be evaluated that the heat load is extremely high.

<Evaluation of heat stroke risk>
Using the work load index W and the heat load index H obtained by the above calculation, the heat stroke onset risk evaluation index R of the worker 10 to be evaluated is obtained as shown by the following formula (Equation 6).

Here, a is a numerical value defined in response to the heat acclimation of the worker to be evaluated, and is a = -1.8 when there is heat acclimation and a = -1 when there is no heat acclimation. Let it be 3.

Regarding the heat stroke onset risk assessment value R obtained as described above, if R is less than 0.6, the onset risk is low risk, and if R is 0.6 or more and less than 1.0, caution level is required. If R is 1.0 or more, it is a high risk and can be determined to be a risk level for developing heat stroke.

Since it is not possible to actually verify the onset of heat stroke, when determining the criteria for determining the risk of developing heat stroke, the risk of developing heat stroke can be judged more strictly, that is, it is decided on the safer side. Should.

<Continuous evaluation of heat stroke risk>
When continuously evaluating the risk of heat stroke of the worker based on the measurement result obtained from the biological sensor 11 which is the measuring device worn by the worker 10, the heat load index H and the work load index W Each exponential moving average value is obtained from the following equations (Equation 7) and (Equation 8) with a sampling interval of 1 minute.

Here, w ₁ = 2/31 and w ₂ = 2/11.

Furthermore, the exponential moving average value of the heat stroke onset risk index R can be obtained from the following equation (Equation 9).

For example, if the index moving average value of the heat stroke risk index R is 1 or more for 30 minutes or more, it is judged that the risk of developing heat stroke is extremely high, and the worker is given a break. Take measures to prevent heat stroke such as urging.

<Display on 2D map>
As can be seen from the above equation (Equation 6), in the heat stroke onset risk management system according to the present embodiment, the index R representing the heat stroke onset risk is a heat load index H for the worker 10 and a work load index W. Expressed as a linear sum.

Utilizing this fact, the heat stroke onset risk index can be displayed as a heat stroke onset risk index on a two-dimensional map centered on the heat load index and the work load index, respectively. For example, by displaying symbols according to the heat stroke onset risk index at the present time in each of a plurality of workers 10 managed by the site supervisor 30 who is the manager on a two-dimensional map, the site supervisor 30 Can grasp the overall risk index of managed workers at a glance. A specific description of the display image showing the degree of heat stroke onset risk of the worker 10 will be omitted.

As described above, in the physical condition evaluation method and the physical condition evaluation system disclosed in the present application, the physical condition is small with a small number of data based on the heartbeat data and the acceleration data of the evaluated person detected by the measuring device worn by the evaluated person. Can be evaluated.

Therefore, the physical condition can be evaluated immediately after the start of measurement. For this reason, for example, when a worker working at a construction site is an evaluated person, the physical condition can be evaluated and judged immediately after the start of the work, and when the worker himself feels uncomfortable, he / she feels uncomfortable. It can be used as data that objectively shows the physical condition.

In addition, by utilizing the fact that physical condition evaluation is possible with a small amount of data, the latest physical condition evaluation result can always be shown, and for example, when the measurement period is one working period (8 hours), measurement is performed. It is possible to grasp the transition of the physical condition evaluation result at that time.

In addition, if you take measurements continuously over multiple days, you can grasp the daily changes in your physical condition, for example, how to take a rest on the weekend, the sleep time you need, and the break time. It is possible to provide valuable data that can be used in the physical condition management of the evaluated person.

In the above embodiment, an example in which the physical condition evaluation system disclosed in the present application is mounted on a heat stroke onset risk management system in which a worker working at a construction site or the like is evaluated is shown. The system for evaluating only physical condition and the work load index, physical condition evaluation index, heat load index, exercise load index, and other indexes of each evaluated person are evaluated based on the acquired biometric information. It can be installed in a biometric information processing system.

For this reason, biometric information processing with a wide range of contents, such as physical condition management during training of athletes and physical condition management system for residents in facilities for the elderly, of biometric information to be evaluated and measured, and its evaluation purpose is different. It can be used as a means for evaluating physical condition in the system to be performed.

The physical condition evaluation method and the physical condition evaluation system disclosed in the present application can calculate the heart rate index from a small amount of measurement data, enable the physical condition evaluation immediately after the start of measurement, and change the physical condition evaluation result. Can be grasped. For this reason, it is extremely useful as a physical condition evaluation method for various evaluated persons, including a method for evaluating the physical condition of a worker at a work site, and as a system thereof.

10 Workers (evaluated persons)
11 Biosensor (Biological information acquisition unit)
22 Evaluation judgment unit (data processing unit)
41 Representative value of heart rate data, representative value of acceleration data 42 Predetermined coefficient 43 Heart rate index (HR0)

Claims (7)

The process of acquiring the heartbeat data and acceleration data of the evaluated person in the biological information acquisition unit,
A step of obtaining a representative value of the heartbeat data and a representative value of the acceleration data based on the acquired plurality of the heartbeat data and the plurality of acceleration data.
Physical condition evaluation, which comprises calculating the heart rate index of the evaluated person using the representative value of the heart rate data, the representative value of the acceleration data, and a predetermined coefficient to evaluate the physical condition of the evaluated person. Method. The heart rate index is an estimated heart rate at rest of the evaluated person calculated based on the heart rate data and acceleration data, and is described from the difference between the resting heart rate in normal times and the heart rate index. The physical condition evaluation method according to claim 1, wherein the physical condition of the evaluated person at the time of measurement is evaluated. The physical condition evaluation method according to claim 1 or 2, wherein both the representative value of the heartbeat data and the representative value of the acceleration data are the median values of the data measured by the biometric information acquisition unit within a predetermined measurement period. .. The physical condition evaluation according to any one of claims 1 to 3, wherein the predetermined coefficient is a heart rate response coefficient showing a correlation between heart rate data and acceleration data calculated based on past measurement data of the evaluated person. Method. A biometric information acquisition unit that acquires heart rate data and acceleration data as biometric information of the evaluated person,
It is provided with a data processing unit that calculates the heart rate index of the evaluated person based on the acquired biometric information.
The data processing unit obtains a representative value of the heartbeat data and a representative value of the acceleration data based on the acquired plurality of the heartbeat data and the plurality of acceleration data.
A physical condition evaluation system characterized in that a heart rate index of the evaluated person is calculated using a representative value of the heart rate data, a representative value of the acceleration data, and a predetermined coefficient. According to claim 5, an image display unit for displaying a physical condition evaluation result is further provided, and the degree of deviation between the resting heart rate and the heart rate index of the evaluated person in normal times is displayed on the map in the image display unit. Described physical condition evaluation system. The physical condition evaluation system according to claim 5, further comprising an image display unit for displaying a physical condition evaluation result, and displaying the transition of the heart rate index in the image display unit.

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