JP2022086699A - Physical condition evaluation method, and physical condition evaluation system - Google Patents

Abstract

To provide a physical condition evaluation method capable of accurately evaluating the physical condition of a person to be evaluated in a high-temperature environment with a high environmental temperature, and a physical condition evaluation system.SOLUTION: The living body information acquisition unit (living body sensor 11) that is used in a physical condition evaluation system, includes: a heart rate detection means 11b that detects heart rate data of a person to be evaluated; a data acquisition transmission unit 11a which is an acceleration detection means for detecting acceleration data according to the operation by the person to be evaluated as well as a temperature detection means for detecting temperature data indicating the ambient temperature of the person to be evaluated. The physical condition evaluation method is a method for evaluating the physical condition of a person to be evaluated based on a difference between the heart rate data detected at the time of evaluation and a predictive value calculated from a prepared heart rate prediction model of the person to be evaluated based on heart rate data of the person to be evaluated, the acceleration data and the temperature data.SELECTED DRAWING: Figure 2

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 particular, when the evaluated person is in a high environmental temperature and has a large heat. It relates to a physical condition evaluation method and a physical condition evaluation system for evaluating physical condition under load.

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 widespread use of small sensor devices that can measure body data such as heart rate, sweating rate, etc., evaluation systems that evaluate the physical condition of the evaluated person based on the biometric 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 a physical condition evaluation system that evaluates and manages such physical condition, the inventors have wearable biological signals 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. Using a detection device that detects We are proposing a physical condition evaluation / management system that evaluates the risk of developing illness and physical condition and feeds back the evaluation results to the evaluated person (see Patent Document 1).

Japanese Unexamined Patent Publication No. 2019-185386

The conventional physical condition evaluation system has a potential meter for detecting the wearer's heartbeat, a three-dimensional acceleration sensor capable of detecting the wearer's body movement, and a temperature sensor capable of detecting the temperature inside the clothes on the chest of the undershirt. A biometric information acquisition unit is arranged, and the biometric information acquired by this 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 the physical condition thereof. To evaluate. In addition, the heat stroke risk index is 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 results of the environmental temperature and the worker's clothing temperature. It is calculated.

While the inventors are verifying the accuracy of the above physical condition evaluation and management system while actually operating it, the following new problems were discovered (1) In an environment where the outside air temperature exceeds the body temperature. Since heat flows from a high temperature to a low temperature, it is difficult to judge the risk by the conventional method assuming an outside temperature below the body temperature. (2) Temperature 24 ° C to 35 ° C, or WBGT (Wet Bulb Globe Temperature:) Wet-bulb globe humidity) In an environment of 22 ° C to 33 ° C, the conventional method is effective because the temperature and heat stress correlate, but it is considered that there is no correlation outside this range. Therefore, the heat load cannot be evaluated accurately only by the temperature and humidity information. (3) Since the resistance to heat varies from person to person, it cannot be judged by the same standard.

Therefore, in a high temperature state where the environmental temperature is equal to or higher than the body temperature, the risk of heat stroke of the evaluated person is evaluated by applying a different evaluation method from the case where the environmental temperature is not so high, and the subject is more reliably affected. It was found that it was preferable to be able to protect the evaluator from heat stroke.

In the heat index: WBGT, which has been widely used as an index for evaluating the heat load of the environment, when the environmental temperature exceeding the upper limit of 33 ° C recommended as a safety standard is as high as the body temperature. The risk of developing heat stroke in Japan cannot be accurately determined. Therefore, it is considered extremely useful to establish an evaluation method that can accurately determine the risk of heat stroke when the evaluated person is placed in such a high temperature environment.

The purpose of the present application is to solve the problems of the above-mentioned prior art, and in a physical condition evaluation method and a physical condition evaluation system for evaluating a physical condition based on the biological information of a person to be evaluated, in a high temperature environment where the environmental temperature is high. It is an object of the present invention to provide a physical condition evaluation method capable of accurately evaluating the physical condition of a person to be evaluated, 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 heartbeat detecting means for detecting the heartbeat data of the evaluated person, an acceleration detecting means for detecting the acceleration data accompanying the movement of the evaluated person, and the subject. A heart rate prediction model of the evaluated person in advance based on the obtained heart rate data, the acceleration data, and the temperature data using a temperature detecting means for detecting temperature data indicating the ambient temperature of the evaluator. Is characterized, and the physical condition of the evaluated person is evaluated based on the difference between the heart rate data detected at the time of evaluation and the predicted value calculated from the heart rate prediction model.

Further, the physical condition evaluation system disclosed in the present application includes a heartbeat detecting means for detecting heartbeat data as biological information of the evaluated person, an acceleration detecting means for detecting acceleration data accompanying an operation, and temperature data indicating an ambient temperature. The temperature detecting means to be detected and the heart rate prediction model of the evaluated person are created in advance based on the acquired biological information, and the heart rate data measured at the time of evaluation and the predicted value calculated from the heart rate prediction model are used. The data processing unit is provided with a data processing unit for calculating the difference between the above, and the data processing unit is characterized in that the physical condition of the evaluated person is evaluated based on the calculated difference.

With the above configuration, the physical condition evaluation method disclosed in the present application is based on the difference between the predicted value calculated from the heartbeat prediction model created based on the biological information obtained from the evaluated person and the heartbeat data measured at the time of evaluation. Based on this, it is possible to accurately determine the magnitude of the heat load applied to the evaluated person, and it is possible to correctly evaluate the change in the physical condition of the evaluated person due to the heat load.

Further, with the above configuration, the physical condition evaluation system disclosed in the present application can accurately evaluate the physical condition of the evaluated person from the increase in the heart rate of the evaluated person due to the heat load.

FIG. 1 is a block diagram illustrating a configuration example of a physical condition evaluation system shown 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 showing the results of investigating the ratio between the temperature inside the clothes and the rate of change in the heart rate in a high temperature environment. FIG. 4 shows an evaluation map for grasping the distribution of past measurement data of the evaluated person used when creating a heartbeat prediction model in the physical condition evaluation method according to the present embodiment. FIG. 5 is an image diagram showing the difference between the heart rate prediction model and the actually measured heart rate in the physical condition evaluation method according to the present embodiment.

The physical condition evaluation method disclosed in the present application indicates a heartbeat detecting means for detecting the heartbeat data of the evaluated person, an acceleration detecting means for detecting the acceleration data accompanying the movement of the evaluated person, and an ambient temperature of the evaluated person. Using the temperature detecting means for detecting the temperature data, a heartbeat prediction model of the evaluated person is created in advance based on the obtained heart rate data, the acceleration data, and the temperature data, and detected at the time of evaluation. The physical condition of the evaluated person is evaluated based on the difference between the obtained heart rate data and the predicted value calculated from the heart rate prediction model.

The physical condition evaluation method disclosed in the present application by having the above configuration grasps the heart rate of the evaluated person as a heart rate prediction model under a situation where a certain heat load is applied, and uses the heart rate data measured at the time of evaluation. It is possible to evaluate the physical condition of the evaluated person by determining the magnitude of the heat load applied to the evaluated person from the size of the deviation. Therefore, it is possible to accurately evaluate the physical condition of the evaluated person, which is particularly placed in a high temperature environment.

In the above-mentioned physical condition evaluation method, it is preferable to detect the temperature inside the clothes of the evaluated person as the ambient temperature of the evaluated person. The temperature inside the clothes does not change much compared to the ambient temperature, and can more accurately represent the thermal environment in which the evaluated person is placed.

Further, it is preferable that an upper limit and a lower limit are set for the ambient temperature used for creating the heart rate prediction model of the evaluated person. As a result of the study by the inventors, it was confirmed that the linear relationship between the environmental temperature and the heart rate rate appears only in a predetermined temperature range. Therefore, in order to perform an accurate physical condition evaluation, the ambient temperature is classified. Therefore, it is preferable to perform data processing corresponding to the temperature range.

When the ambient temperature is the temperature inside the clothes of the evaluated person, the lower limit is set to a temperature between 29 ° C and 32 ° C, and the upper limit is set to a temperature between 34 ° C and 38 ° C. It is preferable to be done.

Furthermore, the heart rate prediction model includes an index related to the heart rate data, an index related to the acceleration data, and an index related to the temperature data, which are determined based on the past measurement data of the evaluated person. It is preferable to be created by. In creating a heartbeat prediction model that serves as a reference for obtaining a difference from the measurement data at the time of evaluation, a more accurate prediction model can be created by using the past measurement data of the evaluated person.

Further, it is preferable to judge the risk of developing heat stroke of the evaluated person as a result of physical condition evaluation. This is because it is desired to accurately determine the risk of developing heat stroke, which is a social problem, as an effect on the human body due to heat load.

The physical condition evaluation system disclosed in the present application detects heartbeat detecting means for detecting heartbeat data as biological information of the evaluated person, acceleration detecting means for detecting acceleration data accompanying movement, and temperature data indicating ambient temperature. A heart rate prediction model of the evaluated person is created in advance based on the temperature detecting means and the acquired biological information, and the difference between the heart rate data measured at the time of evaluation and the predicted value calculated from the heart rate prediction model. The data processing unit is provided with a data processing unit for calculating the above, and the data processing unit evaluates the physical condition of the evaluated person based on the calculated difference.

With such a configuration, the physical condition evaluation system disclosed in the present application can accurately evaluate the physical condition of the evaluated person in a high temperature environment.

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 onset risk management system that acquires biometric information of workers working at a construction site and evaluates and manages the heat stroke onset 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 calculates the heart rate index corresponding to the resting heart rate of the evaluated person based on the heart rate data and the acceleration data acquired as the biological information of the evaluated person. It is something 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.

In this application, a system for accurately grasping the change in physical condition due to the heat load of the evaluated person working in a high temperature environment and determining / evaluating the risk of developing heat stroke will be described. In addition to the illustrated construction sites, the sites where workers work in such a high temperature environment with high ambient temperature include ironworks with blast furnaces and machine manufacturing factories with high temperature furnaces for processing steel plates and steel materials. Can be considered.

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 has 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 thereof. 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 only 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 the entire construction site is managed on a larger scale by including multiple business establishments.

In the physical condition evaluation system described in the present embodiment, the worker 10 wears an undershirt 18 in which a biological sensor 11 which is a biological information acquisition unit for acquiring own biological 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 facing and contacting 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 clothes temperature, 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 electrode with the chest, the heartbeat of the worker 10 can be detected more accurately. Further, a temperature sensor (not shown), which is a temperature detecting means for detecting the temperature inside the clothes, and an acceleration sensor chip (not shown), which is an acceleration detecting means for detecting acceleration in a three-dimensional direction, are inside the data acquisition transmission unit 11a. Is housed in.

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 transmission unit 13. Using the data transmission function of the smartphone 12, the biometric information linked to 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 a biosensor, a method of using an identification code in short-distance communication between a smartphone and a biosensor, and other applications on a smartphone by a 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 personal property of the worker, the identification of the worker using 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. Using this function, in the physical condition evaluation system according to the present embodiment, the image display unit 17 of the smartphone 12 is used to feed back the physical condition evaluation result to the worker 10. 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 evaluation result of the heat stroke onset risk for the entire group to which the worker 10 and the worker 10 belong in an easy-to-see manner. It is used as an image display unit 17.

The cloud server 21 internally includes a data receiving unit 23 and a data transmitting unit 26, 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 the workers 10 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.

Further, 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 commonality of work contents and 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 determined that the heat stroke onset risk is particularly high, the risk is controlled. 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, 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 data of biological 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, 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, it is possible to perform a more accurate evaluation of the risk of developing heat stroke based on the evaluation results of the risk of developing heat stroke under similar weather conditions in the past.

The cloud server 21 is connected to a 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 enthusiastic. 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 heartbeat 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 determination target worker 10 recorded in the data recording unit 24, weather information of the work area acquired by the weather information acquisition unit 25, and further, 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 onset risk of 10 workers are corrected. It is possible to manage the risk of developing heat stroke more realistically.

In the physical condition evaluation system exemplified 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 mounted 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 mounted 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 assessment as to whether or not warning information is 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 centrally or on an easy-to-read screen as detailed information of each worker. 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-see manner. Details 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 on-site supervisor 30. It is set so that it cannot be grasped. This means that if the on-site supervisor 30 can obtain the heat stroke onset risk assessment result of each worker 10, it is possible to take measures to reduce the onset risk of heat stroke, so that the purpose of the system can be achieved and the physical condition can be achieved. 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 on-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 the onset of heat, 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 information.

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 of the smartphone 12 or an operation button, and takes 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 confirms the warning information and interrupts 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 on-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 developing heat stroke is high for workers other than themselves, 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 on-site supervisor 30.

As described above, on the smartphone 12 owned by the worker 10, the worker can obtain 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 for the past several days. It can be illustrated and displayed in a form that is easy to grasp. 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 heat stroke of the worker 10 up to now, his / her heart rate acquired by the biological sensor 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 the display contents and the purpose of display, and therefore detailed description in the present specification is 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 business establishment 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 user 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, the cloud server 21 is accessed from the personal computer 31 and the management computer 40. It is possible to control the data processing content of the cloud server 21, update the determination program of the evaluation determination 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 exemplified 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 device.

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 biological sensor 11 for acquiring the heartbeat, the temperature inside the clothes, and the movement of the worker 10, the biological sensor 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 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, the worker 10 is compared with the case where the biosensor 11 is attached by another method. , It is possible to alleviate the special consciousness of wearing a sensor and acquire 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 arm and legs of the worker 10. It is possible to adopt a form arranged in such as. 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 the physical condition of a sports athlete to be trained is evaluated. 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 attached to 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 heart rate 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. It 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 a wristwatch-type sensor that is worn on the wrist is used as the 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.

Further, as the temperature sensor for measuring the ambient temperature of the evaluated person, the one capable of measuring the temperature inside the clothes of the evaluated person like the above-mentioned biological sensor 11 is preferable. This is because the temperature inside the clothes has less fluctuation than the ambient air temperature, and is the environmental temperature closest to the evaluated person. On the other hand, when the watch-type sensor detects the pulse and ambient temperature of the evaluated person, the temperature sensor is exposed and mainly measures the temperature of the ambient air, so the distance from the furnace, which is the heat source. Estimate the temperature inside the clothes, which is the closest temperature to the evaluated person, from the environmental temperature measured by the watch-type biosensor, such as grasping the relationship between the air temperature and the temperature inside the clothes in advance. It is preferable to take measures such as correction.

It is not always necessary for the evaluated person to wear the temperature sensor. For example, the temperature acquired from an environment sensor installed in the work environment may be used as the ambient temperature, or the body surface temperature of the evaluated person may be extracted from the thermal image acquired by a non-contact thermometer (for example, a thermo camera). , May be the ambient temperature.

[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, first, the heartbeat data of the evaluated person detected by the heartbeat detecting means provided in the measuring device (biological sensor) worn by the evaluated person, and 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 body of the evaluated person, is acquired. By extrapolating from the slope of the regression line showing the relationship between the obtained heart rate data and the acceleration data, the heart rate index, which is the heart rate when the acceleration data is 0, that is, when the evaluated person is in a resting state, is obtained. Physical condition is evaluated by this heart rate index.

Further, when the physical condition evaluation system according to the present embodiment functions as a management system for managing the risk of developing heat stroke, a work load index indicating the work intensity of the worker is calculated based on the heart rate index obtained above. Furthermore, the heat load index of the worker is calculated based on the temperature inside the clothes of the worker (T _i ) obtained from the biosensor and the environmental temperature (T ₀ ) of the site where the worker is working. do. 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.

The work load index W is obtained as follows.

First, a predetermined time (2 as an example) based on the central heart rate, which is the heart rate data obtained in each partial section, and the acceleration deviation, which is the acceleration data, by the biosensor worn by the worker who is the evaluated person. Time) A regression line is calculated from the data acquired in the above period, 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 1).

HRs = (αs / αr) (HR-βr) + βs (Equation 1)
In the above equation (1), 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).

Here, 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. 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 samplings, the more accurate 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 for 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 W from the heart rate data according to the characteristics of each worker who is the evaluated person.

Further, when the detection rate of the heartbeat data is low, the work load index can be calculated using only the acceleration data by using a predetermined mathematical formula such as multiplying the acceleration deviation which is the acceleration data by an appropriate coefficient. .. Further, 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 calculates the work load index of the worker. At this time, the evaluation determination unit determines whether to use the standardized heart rate or the estimated standardized heart rate. Further, the evaluation determination unit can determine 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 used, 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 are measured depending on the magnitude of the acceleration 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 by improving the degree of adopting the standardized heart rate in the state where the heart rate detection rate is high, it is more accurately in line with 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 2).

METs = a _METs × HR _c + b _METs (Equation 2)
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 (formula).

W = a _W × METs + b _W (Equation 3)
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 the work is large and the value of W is 1 or more, the work can be a work having an extremely high metabolic rate, that is, a work having a very heavy burden on the worker.

Further, the heat load index H is obtained by the following equation 4.

H = (2.73T _i + _0.05T 0-89.2) / 10 (Equation 4)
The environmental temperature data T ₀ of the work site is obtained from the temperature data around the work site acquired by the weather information acquisition unit of the cloud server, and from the temperature sensor placed in the work site when the worker is working indoors. It was acquired as the obtained temperature information. In the above equation 1, when 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.

Then, the heat stroke onset risk index R is calculated by the following formula 5.

Here, a is a numerical value defined in response to heat acclimatization of the worker to be evaluated, and is a = -1.8 with heat acclimatization and a = -1 without heat acclimatization. It is set to 3.

Regarding the heat stroke onset risk assessment value R obtained as described above, as an example, 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 is required. If the alert level of R is 1.0 or more, it is a high risk and it can be determined that the risk level is the onset of heat stroke. In addition, since it is not possible to actually verify the occurrence of heat stroke, when determining the criteria for determining the risk of developing heat stroke, it is decided so that the risk of developing heat stroke can be judged more strictly, that is, on the safer side. Should.

[Evaluation of physical condition in a high temperature environment]
(1. Changes in heart rate in a high temperature environment)
In the physical condition evaluation method and the heat stroke onset risk management method according to the present embodiment, as shown in the above formula 4, the heat load H increases substantially in proportion to the increase in the ambient air temperature of the worker. This is based on the classical study of Lind [Journal of Applied Physiology 18, 51 (1963)] and is a widely adopted assumption in current heat load assessments (such as ISO7243: 2017).

However, as a result of the studies by the inventors, the environmental temperature rises when the environment temperature around the worker, especially the temperature inside the worker's clothes, exceeds the body temperature (about 36 ° C.). It was confirmed that the degree to which the thermal burden affects the increase in heart rate is not proportional. It is known that the increase in heart rate with an increase in environmental temperature correlates with the increase in core body temperature, and the degree of increase in heart rate can be used to evaluate the heat burden (damage to the body from the environment). can.

FIG. 3 shows the measurement results of the fluctuation rate of the clothes temperature and the heart rate of the worker in a high temperature environment.

The data shown in FIG. 3 is based on the measurement results of a total of about 200,000 points when the work for 34 days was performed for about 10 workers working in the high temperature building. The operator to be measured performed the work with the biosensor shown in FIG. 2 attached. Here, based on the heart rate data, acceleration data, and clothes temperature data acquired by the biosensor, the relationship between the clothes temperature and the heart rate was plotted in a state where the work load was small (2.5 METs or less).

The “x” mark (reference numeral 31) in FIG. 3 plots the fluctuation rate of the heart rate obtained by dividing the median heart rate by the average heart rate of each worker (the average value of all measured data) at each environmental temperature. It was done. The broken line (reference numeral 32) is an approximate curve using a sigmoid type function.

As shown in FIG. 3, it can be seen that the rate of change in heart rate with respect to the temperature inside the clothes monotonically increases in the region (region 33) where the temperature inside the clothes is from about 30.5 ° C to about 36.5 ° C. On the other hand, in the region where the temperature inside the clothes is as low as 30.5 ° C or lower (region 34) and in the region where the temperature inside the clothes is as high as 36.5 ° C or higher (region 35), the heart rate is changed even if the temperature inside the clothes changes. It can be seen that the change in is extremely small. A similar trend of change depending on the temperature inside the clothes was also observed at a moderate workload. However, the increase in the heart rate change rate depending on the temperature inside the clothes was smaller as the work load was higher.

Since an increase in heart rate means an increase in heat burden, in an environment where the temperature inside clothes exceeds 36.5 ° C, the temperature and humidity of the environment, WBGT or temperature inside clothes is not appropriate as an index of heat load. Represents.

Therefore, in a work environment where the heat load is large and the temperature inside the clothes may exceed the body temperature level, the inventors are new to the evaluation based on the conventional heat stroke onset risk index R shown as the above formula 5. I devised an algorithm for evaluating physical condition.

(2. Algorithm for evaluating physical condition in high temperature environment)
a. Basic concept The heart rate HR of the evaluated person acquired by the biosensor shown in Fig. 2 is the resting heart rate HR ₀ , an increase ΔHR _M due to energy metabolism due to exercise, and an increase ΔHR _S due to static movement. Using the increase ΔHR _T due to heat load and the increase ΔHR _N due to psychological effects and other factors, it is expressed as the following equation 6.

HR = HR ₀ + ΔHR _M + ΔHR _S + ΔHR _T + ΔHR _N (Equation 6)
Since the effects of ΔHR _S and ΔHR _N are small and can be ignored, the increase in heart rate due to heat load is
ΔHR _T ≈ HR- (HR ₀ + ΔHR _M ) (Equation 7)
It can be expressed as. Since it is known that changes in core body temperature affect changes in heart rate (in the case of Japanese, it is considered to be about 20 bpm / ° C), changes (increases) in heart rate during heat load are used. By grasping it, it is possible to detect a change (rise) in core body temperature, that is, a change (rise) in heat load. Furthermore, by applying the heart rate HR prediction model of (Equation 7) to each individual to estimate the expected heart rate in normal times and evaluating the difference between the heart rate measured in real time and the predicted heart rate, the patient is in poor physical condition. It is possible to detect abnormal changes in heart rate associated with.

In the physical condition evaluation method and the physical condition evaluation system disclosed in the present application, the heart rate HR of the evaluated person actually measured by the biological sensor and the time when the heart rate is measured are based on the premise shown by the above formula 7. The difference from the heart rate as a predicted value obtained by using the acceleration deviation indicating the movement (activity amount) of the body in. Then, it is judged that this difference in heart rate is an increase in heart rate caused by a heat load, and the risk of physical condition change due to the magnitude of the heat load applied to the evaluated person is evaluated from the degree of this increase. Is.

b. Prediction of heart rate As described above, in the physical condition evaluation method and the physical condition evaluation system shown in the present embodiment, a prediction model for predicting the heart rate to be measured is created based on the activity amount of the evaluated person. This predictive model is updated every physical condition evaluation date used.

The prediction model of heart rate HR is expressed by the following equation 8.

Acceleration deviation A _RMS is the deviation of the acceleration data acquired at the same time when the heartbeat data is detected from the biosensor, and since the acceleration data is obtained as the average value ΔA for the past 1 minute, the average value for 1 minute is as follows. It is calculated by the procedure of.

First, for the acceleration data {Ax (t)}, {Ay (t)}, {Az (t)} in each of the x-axis, y-axis, and z-axis directions, the time constant is set to 6 sec, which is a statistical method. The exponential moving average of the acceleration data in each axial direction is calculated using the exponential moving average method. The time constant is not particularly limited, but may be appropriately determined in the range of, for example, 5 to 10 sec according to the characteristics of body movement and the performance of the acceleration sensor.

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

Next, the above-mentioned exponential moving average is removed 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)" is obtained.

Then, for the time-series acceleration from which the trend has been removed, the square at each time is calculated using the following equation (Equation 9) to obtain the sum.

The average value “ΔA ² _ave ” for each minute of the sum of squares “ΔA ² (t)” obtained above is calculated. Here, the average value is obtained by dividing by the number of data points. Also, the square root "ΔA _ave " of the squared average of acceleration "ΔA ² _ave " is calculated. This ΔA _ave is the velocity deviation A _RMS . If the data is non-numerical, it is excluded as an abnormal value.

As the clothing temperature T _in , the temperature data acquired from the biosensor can be used as it is. In addition, reflecting the measurement results of the worker's clothes temperature and the volatility of the heart rate shown in FIG. 3, the term “f (T _in )” is used in the third term on the right side of the above equation 8. Specifically, the upper limit T _max and the lower limit T _min of the internal temperature T _in are set in advance, and when the upper limit T _max is exceeded, the upper limit is constant, and when the temperature is lower than the lower limit T _min , the lower limit is constant. Become.

As an example, based on the measurement results shown in FIG. 3, T _max = 36.5 ° C. and T _min = 30.5 ° C. can be set, and the internal temperature T _in is 30.5 ° C. to 36.5 ° C. In between, f (T _in ) is a monotonically increasing function (for example, a piecewise linear function), but when the in-clothes temperature T _in is 30.5 ° C or lower, or when the in-clothing temperature T _in is 36.5 ° C or higher. Is calculated assuming that each takes a constant value.

c. Specific calculation example First, on the first day of application of the physical condition evaluation by the physical condition evaluation method according to this embodiment, since the past data of the evaluated person does not exist, it was obtained by the past operation example in the main body condition evaluation system. A heart rate model is created by substituting the value of the following formula 10 as representative data into the above formula 8.

In the case of the second day or later when the physical condition is evaluated according to the present embodiment, the parameters used in Equation 8 are calculated by the following method using the past data of the worker who is the evaluated person. Here, first, the number of past data measured is confirmed, and the estimation method of the prediction model is different depending on the number of reliable measurement data. This avoids erroneous results being obtained using the same estimation method as when the number of data is large when the number of data is small, while it is actually obtained from the worker even when the number of data is small. This is to perform a more appropriate physical condition evaluation by creating a prediction model based on the collected data.

FIG. 4 shows an evaluation map of the in-clothing temperature T _in and the acceleration deviation A _RMS used for evaluating the number of measured data.

As shown in FIG. 4, the 75% point (T _in ^(3Q) : third quartile) of the data of the in-clothing temperature T _in effectively measured from the biosensor is set as the vertical boundary line 41. A region is defined in which T _min = 30.5 ° C. is the lower limit 42 and T _max = 36.5 ° C. is the upper limit 43. Regarding the acceleration deviation A _RMS , the lower limit is 44, and the work is performed at a medium or higher level with a relatively large movement, with A _RMS = 0.05, which is considered to be static but not in a resting state. _{Let ARMS} = 0.25, which is considered to be present, be the intermediate boundary line 45. There is no upper limit for the acceleration deviation A _RMS .

In this way, the regions (region A, region B, region C, shown in FIG. 4) are divided into two in the vertical direction (internal temperature T _in ) and two in the horizontal direction (acceleration deviation A _RMS ). Area D) Obtain the median value for each measurement point included. Then, the above equation 8 is applied to the four points shown in the following equation 11 by the method of least squares.

However, if the result of the calculation is αHR <20 [bpm / G] or βT <2 [bpm / ° C], each parameter is determined using the above equation 11.

d. Evaluation of heat risk Finally, based on the difference between the estimated heart rate at each measurement time obtained based on Equation 8 and the heart rate actually measured by the biosensor, the heat load at the time of measurement by the worker concerned. Determine the risk.

FIG. 5 is an image diagram showing the difference between the estimated heart rate and the heart rate as a measurement result.

As shown in FIG. 5, in a state where a heat load is applied, the estimated heart rate 51 obtained by substituting the measurement data at each measurement time into the above equation 8 was actually measured by a biosensor. The heart rate 52 becomes a high value. In the physical condition evaluation according to the present embodiment, the risk of heat load at the time of measurement is evaluated based on the degree of increase of the measured heart rate 52 from the estimated heart rate 51 indicated by the black arrow in FIG.

Assuming that the evaluation time point is t = tk, the acceleration deviation A _RMS ^(60s) [k-1] at the immediately preceding measurement time point t = t [k-1], the internal temperature T _in [k-1], and the current time point. Central heart rate at HR ^(60s) [k-1].

If ΔHR _T [k-1]> 10 bpm obtained by Eq. 12 and ΔHR [k]> 15 bpm obtained by Eq. 13, it is determined that the patient is in a “caution” state exposed to a high temperature load. However, be careful not to work for a long time.

Further, the above _T'in is substituted into the following equations 14 and 15.

Central heart rate HR ^(60s) [k] is HR ^(60s) using ΔHR _T [k-1]> 10 bpm determined by equation 14 and HR [k-1] determined by equation 13. When the state of [k]> HR [k-1] + 15 bpm continues for a certain period of time or more, for example, 3 minutes, it is determined that the heart rate is abnormally increased in the “abnormality detection (danger)” state.

The "Caution" state or "Abnormality detection (danger)" state, which is the judgment result, is displayed on a smartphone as a mobile terminal owned by the worker to alert the worker. It is preferable to notify the site supervisor or the department that manages the entire worker to confirm whether the relevant worker has taken appropriate measures.

As described above, in the physical condition evaluation method and the physical condition evaluation system disclosed in the present application, the physical condition of each evaluated person can be determined even when the evaluated person is placed in a high temperature environment and is subject to a high heat load. It can be determined accurately.

The physical condition evaluation system and the physical condition evaluation method shown in the present embodiment can be applied as the main physical condition evaluation means to the evaluated person who can be assumed to be constantly placed in a high temperature environment. In addition, the physical condition evaluation system and the physical condition evaluation method disclosed in the present embodiment are combined with the physical condition evaluation system that evaluates the physical condition of the evaluated person based on the conventional central heart rate, and the surroundings of the evaluated person measured by the biological sensor. If it can be determined from the temperature data indicating the temperature that the evaluated person is in a high temperature environment, it is additionally applied as an evaluation method for performing more accurate physical condition evaluation by switching the data processing as in the above embodiment. can do.

The heart rate data of the evaluated person acquired by the biosensor includes the increase ΔHR of the heart rate related to each poor physical condition. For example, if you have an infectious disease such as a cold or influenza, or if you have inflammation in your body, your heart rate will increase. Since this evaluation method can detect an increase in heart rate due to these other factors, it is also possible to evaluate changes in physical condition other than thermal factors.

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 used as an evaluated person 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, for example, biometric information such as physical condition management during training of athletes and physical condition management system for residents in facilities for the elderly, biometric information to be evaluated and measured, and biometric information with different evaluation purposes is performed. 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 are applied when the evaluated person is in a high temperature environment and the physical condition evaluation using the heart rate index, which is the conventional central heart rate, cannot be correctly evaluated. , It is possible to perform accurate physical condition evaluation under heat load. For this reason, it is not limited to the case where it is assumed that a large heat load is applied to the evaluated person, but it is a work site as a physical condition evaluation method that is applied by switching when the ambient temperature of the evaluated person exceeds a certain level. It is extremely useful as a physical condition evaluation method for various evaluated persons, including a system for evaluating the physical condition of a worker, and as a system thereof.

10 Worker (evaluated person)
11 Biosensor (Biological information acquisition unit)
11a Data acquisition and transmission unit (acceleration detection means, temperature detection means)
11b Heart rate sensor electrode (heart rate detection means)
22 Evaluation judgment unit (data processing unit)

Claims (7)

A heartbeat detecting means for detecting the heartbeat data of the evaluated person, an acceleration detecting means for detecting the acceleration data accompanying the movement of the evaluated person, and a temperature detecting means for detecting the temperature data indicating the ambient temperature of the evaluated person. Using,
Based on the obtained heart rate data, the acceleration data, and the temperature data, a heart rate prediction model of the evaluated person is created in advance.
A physical condition evaluation method, characterized in that the physical condition of the evaluated person is evaluated based on the difference between the heartbeat data detected at the time of evaluation and the predicted value calculated from the heartbeat prediction model. The physical condition evaluation method according to claim 1, wherein the temperature inside the clothes of the evaluated person is detected as the ambient temperature of the evaluated person. The physical condition evaluation method according to claim 1 or 2, wherein an upper limit and a lower limit are set for the ambient temperature used for creating the heart rate prediction model of the evaluated person. When the ambient temperature is the temperature inside the clothes of the evaluated person, the lower limit is set as a temperature between 29 ° C and 32 ° C, and the upper limit is set as a temperature between 34 ° C and 38 ° C. The physical condition evaluation method according to claim 3. The heart rate prediction model is created by an index related to the heart rate data, an index related to the acceleration data, and an index related to the temperature data, which are determined based on past measurement data of the evaluated person. The physical condition evaluation method according to any one of claims 1 to 4. The physical condition evaluation method according to any one of claims 1 to 5, wherein the risk of developing heat stroke of the evaluated person is determined as a physical condition evaluation result. A heartbeat detecting means for detecting heartbeat data as biological information of the evaluated person, an acceleration detecting means for detecting acceleration data accompanying an operation, a temperature detecting means for detecting temperature data indicating an ambient temperature, and a temperature detecting means for detecting an ambient temperature.
Data processing that creates a heartbeat prediction model of the evaluated person in advance based on the acquired biometric information and calculates the difference between the heartbeat data measured at the time of evaluation and the predicted value calculated from the heartbeat prediction model. With a department,
The data processing unit is a physical condition evaluation system characterized by performing physical condition evaluation of the evaluated person based on the calculated difference.

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