JP7407419B2 - Physical condition evaluation method and physical condition evaluation system - Google Patents

Description

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

In recent years, with the development of the Internet connection environment such as wireless LAN, the development of methods that enable short-distance information transmission such as Bluetooth (registered trademark), and the development of high-performance mobile devices such as smartphones and body temperature With the spread of small sensor devices that can measure physical data such as heart rate, sweat rate, etc., evaluation systems that evaluate the physical condition of the person being evaluated based on the biological information acquired by the sensor device and evaluation results are becoming more and more popular. A physical condition management system has been put into practical use that manages the health condition of the person being evaluated based on the above information and reduces the risk of developing heatstroke, which has become a problem in recent years.

As an example of a physical condition evaluation system that performs evaluation and management of such physical condition, a wearable device that detects biological signals is equipped with a three-dimensional acceleration sensor that grasps the body movements of the person to be evaluated and a biological information acquisition unit that detects heartbeat. Using a detection device, the workload index indicating the work intensity of the assessee, the heart rate index and physical fitness index of the assessee, and the risk index for the onset of heat stroke are calculated, and the heat stroke index of the assessee is calculated. A system has been proposed that evaluates the risk of onset and physical condition and feeds back the evaluation results to the person being evaluated (see Patent Document 1).

Japanese Patent Application Publication No. 2019-185386

The conventional physical condition evaluation system described above has an electrometer on the chest of the undershirt that detects the wearer's heartbeat, a three-dimensional acceleration sensor that can detect the wearer's body movements, and a temperature sensor that can detect the temperature inside the clothes. A biometric information acquisition unit is arranged, and the biometric information acquired by the biometric information acquisition unit is transmitted to an information processing unit of a cloud server on the Internet via a communication device such as a smartphone owned by the person to be measured. The information processing unit calculates the heart rate index, which is estimated to be the resting heart rate of the person being evaluated, based on the regression line obtained from the correlation between the detected heart rate data and the acceleration data. Evaluate. Further, a heat stroke onset risk index is calculated based on a work load index determined based on the heart rate index and the slope of the regression line, and a heat load index obtained from the measurement results of the temperature inside the clothes.

In conventional physical condition evaluation systems such as this, in which the heart rate index is calculated based on the regression line obtained from the correlation between the heart rate data and acceleration data of the person being evaluated, it is difficult to accurately calculate the regression line in order to perform an accurate physical condition evaluation. The amount of data that can be obtained is required. For this reason, the physical condition evaluation is started after acquiring data for about two hours, which is about half of the morning working hours, or for a whole day.

However, there is an expectation that the worker, who is the person to be evaluated, evaluates his or her physical condition immediately after starting to use the physical condition evaluation system. Also, since one regression line is calculated using data obtained over two hours or more, at least the data obtained within this data accumulation period should be separated according to the acquisition time and used as time-series data. I can't. Furthermore, even if the physical condition of the person to be evaluated suddenly changes (deteriorates) within the data accumulation period, the physical condition evaluation system cannot detect the change in physical condition and take any countermeasures.

The purpose of the present application is to solve the problems of the above-mentioned conventional technology, and to provide a physical condition evaluation method and system for evaluating the physical condition based on the biological information of the person to be evaluated, in a short time from the start of data acquisition. The purpose of the present invention is to provide a physical condition evaluation method and a physical condition evaluation system that allow accurate physical condition evaluation.

In order to solve the above problems, the physical condition evaluation method disclosed in the present application includes a step of acquiring heart rate data and acceleration data of the person being evaluated in a biological information acquisition unit, and a step of acquiring heart rate data and acceleration data of the person being evaluated in a biological information acquisition unit, a step of determining a representative value of the heartbeat data and a representative value of the acceleration data based on the data; The method is characterized in that the physical condition of the subject is evaluated by calculating the heart rate index of the subject.

In addition, the physical condition evaluation system disclosed in the present application includes a biological information acquisition unit that acquires heart rate data and acceleration data as the biological information of the person to be evaluated; and a data processing unit that calculates an index, the data processing unit determining a representative value of the heartbeat data and a representative value of the acceleration data based on the plurality of the acquired heartbeat data and the plurality of the acceleration data. , the heart rate index of the person to be evaluated is calculated 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 results on the day of measurement as a predetermined coefficient necessary when calculating the heart rate index, and therefore 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 starting the measurement, and it is also possible to understand the transition of the physical condition evaluation result.

In addition, with the above configuration, the physical condition evaluation system disclosed in this application can obtain a heart rate index, which is an index for physical condition evaluation, based on a small amount of measurement data, and can evaluate the physical condition of the person in various ways. Can communicate the results.

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 the configuration of a biological information acquisition unit used in the physical condition evaluation system described in this embodiment. FIG. 3 is a diagram illustrating a conventional process of determining a heart rate index of a subject based on heart rate data and acceleration data. FIG. 4 is a diagram illustrating a process of determining 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 illustrating a display example of the current physical condition evaluation results of the person to be evaluated. FIG. 6 is a diagram illustrating a first display example that displays the transition of the physical condition evaluation results of the worker who is the person to be evaluated. FIG. 7 is a diagram illustrating a second display example that displays the transition of the physical condition evaluation results of the worker who is the person to be evaluated. FIG. 8 is a diagram illustrating a display example of a history of physical condition evaluation results of a worker who is an evaluated person.

The physical condition evaluation method disclosed in the present application includes a step of acquiring heart rate data and acceleration data of the person to be evaluated in a biological information acquisition unit, and a step of acquiring the heart rate data and acceleration data of the person to be evaluated based on the acquired heart rate data and the acceleration data. a step of calculating a representative value of the data and a representative value of the acceleration data; and a step of calculating a heart rate index of the evaluator using the representative value of the heart rate data, the representative value of the acceleration data, and a predetermined coefficient. Evaluate the physical condition of the person being evaluated.

By having the above configuration, the physical condition evaluation method disclosed in the present application can calculate a heart rate index if enough data can be obtained as heart rate data and acceleration data to obtain their respective representative values. Therefore, the time required to start the physical condition evaluation is shortened, and real-time physical condition evaluation results can be obtained in chronological order.

In the physical condition evaluation method, the heart rate index is an estimated resting heart rate of the person to be evaluated, calculated based on the heart rate data and acceleration data, and is the resting heart rate in normal times and the heart rate. It is preferable to evaluate the physical condition of the person to be evaluated at the time of measurement based on the deviation from the index. It is known that the heart rate at rest increases when the person is in poor physical condition, so the heart rate index, which is an estimate of the heart rate at rest, can be used to determine the physical condition of the person being evaluated at the time of measurement.

Further, it is preferable that the representative value of the heartbeat data and the representative value of the acceleration data are both median values of data measured by the biological information acquisition unit within a predetermined measurement period. The median value of data acquired within a given period is less susceptible to outliers and noise than the average value, and is therefore considered to be more suitable as a representative value for use in physical condition assessment methods that may have measurement errors. It will be done.

Note that it is preferable that the predetermined coefficient is a heartbeat response coefficient that indicates a correlation between heartbeat data and acceleration data calculated based on past measurement data of the person to be evaluated. By using a coefficient calculated based on the evaluated person's own data as a coefficient indicating the correlation between heart rate data and acceleration data, a more accurate heart rate index can be calculated.

The physical condition evaluation system disclosed in this application includes a biological information acquisition unit that acquires heart rate data and acceleration data as the biological information of the person to be evaluated, and a heart rate index of the person to be evaluated based on the acquired biological information. a data processing unit that calculates a representative value of the heartbeat data and a representative value of the acceleration data based on the plurality of the acquired heartbeat data and the plurality of the acceleration data; A heart rate index of the person to be evaluated is calculated using a representative value of the heart rate data, a 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 update the physical condition evaluation results at any time. Therefore, various useful physical condition evaluation results can be provided to the person being evaluated.

The physical condition evaluation system further includes an image display section that displays the physical condition evaluation results, and the image display section displays on a map the degree of deviation between the resting heart rate of the person to be evaluated and the heart rate index in normal times. It is preferable to do so. By doing so, the person to be evaluated can visually understand how well or bad his or her current physical condition is.

Preferably, the apparatus further includes an image display section for displaying physical condition evaluation results, and the image display section displays changes in the heart rate index. By doing so, it becomes possible to provide the person being evaluated with information about changes in their physical condition in an easy-to-understand manner, and to have them use the information to manage their own physical condition.

DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments of a physical condition evaluation method and a physical condition evaluation system disclosed in the present application will be described using the drawings.

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

The physical condition evaluation system described as an example in this embodiment is incorporated into a heatstroke onset risk management system that acquires biological information of workers working at a construction site and evaluates and manages the risk of developing heatstroke for each worker. This system evaluates the physical condition of each worker, with each worker as the person being evaluated.

The physical condition evaluation system disclosed in this application calculates the heart rate index corresponding to the resting heart rate of the person to be evaluated based on the heart rate data and acceleration data acquired as biological information of the person to be evaluated, thereby evaluating the person's physical condition. It is something to be evaluated. Therefore, as exemplified in this embodiment, various biological information processing and evaluation systems that acquire heartbeat (pulse) information and acceleration information indicating body movement as biological information of the evaluation subject and perform some kind of evaluation. The system can be easily incorporated into a system that can share the obtained biological information and perform the function of evaluating the physical condition of the person being evaluated.

FIG. 1 is a block diagram showing a configuration example of each part of a heatstroke onset risk management system in which the physical condition evaluation system described in this embodiment is incorporated.

As shown in Fig. 1, the heatstroke onset risk management system incorporating the physical condition evaluation system evaluates the physical condition of the worker 10 who is the person to be evaluated and the worker's 10 based on the biological information of the worker 10, and also prevents heat stroke. A cloud server 21 on the Internet 20 that evaluates the risk of onset, a site supervisor 30 who is an administrator who supervises a work group that includes a certain number of workers 10, and a plurality of site supervisors 30 under its management. The system is comprised of 40 business establishments that operate, maintain, and manage the heat stroke risk assessment system by understanding the overall situation.

Note that the above is a general 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 office are inseparable, It goes without saying that different forms may be adopted depending on the structure of the site where the heatstroke risk management system is actually introduced, such as when managing an entire construction site on a larger scale that includes multiple business establishments.

In the physical condition evaluation system described in this embodiment, the worker 10 wears an undershirt 18 in which a biosensor 11, which is a biometric information acquisition unit that obtains biometric information about himself, is placed on his chest.

FIG. 2 is a diagram showing a configuration example of an undershirt on which a biosensor is arranged, which is worn by a worker in the physical condition evaluation system described in this embodiment. FIG. 2(a) shows the front surface of the undershirt, and FIG. 2(b) shows the back surface of the undershirt, that is, the side facing and in contact with the worker's body surface.

As shown in FIG. 2, a biosensor 11 is placed on the chest of an undershirt 18 worn by the worker 10. More specifically, the biosensor 11 includes a data acquisition and transmission unit 11a disposed at the center of the chest on the front surface 18a of the undershirt 18, and is connected to the data acquisition and transmission unit 11a, and is connected to the back surface 18b of the undershirt 18, In other words, it is composed of an electrode portion 11b of a heart rate sensor disposed extending in the left-right direction on the side that contacts the skin.

In the physical condition evaluation system according to the present embodiment, the heartbeat, temperature inside clothes, and movement of the worker 10 are detected by the biosensor 11, which is a heartbeat detection means (heartbeat sensor) placed on the back side of the undershirt 18. By bringing the electrode into contact with the chest, the heartbeat of the worker 10 can be detected more accurately. Further, a temperature sensor (not shown) that detects the temperature inside the clothes and an acceleration sensor chip (not shown) that detects acceleration in three-dimensional directions are housed in the data acquisition and transmission unit 11a.

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

The smartphone 12 includes a data receiving section 15 and a data transmitting section 16, and is constantly connected to the Internet 20 as a network environment via a wireless LAN or a mobile phone information carrier. In the physical condition evaluation system of this embodiment, the functions of the physical condition evaluation system are used to link the identification data of each worker 10 with the smartphone 12, and the smartphone 12 has an evaluated person information transmitting section 13. Using the data transmission function of the smartphone 12, the biometric information linked to the identification information of the worker is transmitted to the cloud server 21 located on the Internet 20.

The measurement device worn by the worker and the ID that identifies the work itself can be linked by inputting the name and management number of the biosensor used by the worker into a smartphone, or by using the smartphone's image recognition function. 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-range communication between a smartphone and a biosensor, and a method of using an application on a smartphone by a worker. Various methods are available, including the method of selecting In addition, if the smartphone is not the personal property of the worker but is lent out as part of system use, the worker using the smartphone can be identified by data input using the smartphone, reading of the identification code, and facial recognition system. You can register using , or other methods.

Furthermore, the smartphone 12 can receive data, emit sound, and display images. Utilizing this function, the physical condition evaluation system according to the present embodiment uses the image display section 17 of the smartphone 12 to provide feedback of the physical condition evaluation results to the worker 10. In addition, each function of the smartphone 12 includes a warning notifying unit 14 that performs a warning function to convey the risk of developing heat stroke to the worker 10 and urge the worker to take a break in the heat stroke onset risk management system; In order to fulfill the function of displaying the physical condition evaluation results of the worker 10 himself, as well as the evaluation results of the risk of developing heatstroke for the worker 10 and the entire group to which the worker 10 belongs, as a function of the heatstroke onset risk management system, in an easy-to-read manner. It is used as an image display section 17.

The cloud server 21 internally includes a data receiving section 23 and a data transmitting section 26, and exchanges information via the Internet 20. In addition, the cloud server 21 includes an evaluation determination unit 22 as a data processing unit, which acquires biological information data of all the workers 10 who are the targets of the physical condition evaluation system, and determines whether the physical condition of each worker 10 is good or bad. A physical condition evaluation index is calculated.

In addition, the evaluation determination unit 22 of the cloud server 21 also calculates a work load index indicating the magnitude of the load that each worker 11 is under due to work and a heat load index in the heatstroke onset risk management system, Based on these indices, a heatstroke onset risk index is calculated that indicates the degree of risk of each worker 10 developing heatstroke. Furthermore, the evaluation/judgment unit 22 can manage the risk of developing heatstroke for a group of workers 10 formed based on the commonality of work content and work environment.

The heatstroke onset risk management system, which is also a physical condition evaluation system described in this embodiment, manages the risk of developing heatstroke of each worker 10, and when it is determined that the risk of developing heatstroke is particularly high, Convey information to encourage the worker concerned to take measures to reduce the risk of developing heatstroke. For this reason, the cloud server 21 evaluates and determines the risk of developing heatstroke, and if the risk of developing heatstroke is increasing, creates warning information to warn the worker to that effect.

The cloud server 21 also has a weather information acquisition unit 25, which acquires weather information from an information site that provides weather information via the Internet 20, and obtains information about the temperature in the area where the worker 10 is working. It is possible to obtain weather conditions at the current time, such as temperature, humidity, and amount of sunlight, as well as weather forecasts that take into account changes in the next few hours, making it possible to take weather conditions into consideration when evaluating the risk of developing heatstroke.

Furthermore, the cloud server 21 is equipped with a data recording unit 24, which includes measurement data of biological information from each worker 10 registered in the heatstroke onset risk management system, physical condition evaluation results, heatstroke onset risk index, and warning information. You can record the creation history etc. in chronological order. As a result, for example, it is possible to perform an on-time physical condition evaluation of each worker 10 on the day based on the results of the physical condition evaluation up to the present day or the previous day, and to manage the risk of developing heatstroke. Can be done. Furthermore, it is possible to perform a more accurate risk assessment of heatstroke based on past evaluation results of risk of heatstroke under similar weather conditions.

The cloud server 21 is connected via the Internet 20 to a personal computer 31 serving as a manager information terminal used by a site supervisor 30 who is a manager who supervises the work of the worker 10 who is the person to be evaluated at the construction site. . For this reason, the foreman 30 at the work site where the worker 10 is working receives data on the biological information of the worker 10 sent from the cloud server 21 from time to time, the physical condition evaluation result, the enthusiasm It is possible to grasp the evaluation result of the disease onset risk, whether or not warning information has been 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 heart rate data, acceleration data, and clothing temperature data obtained from the biosensor 11 worn by the worker 10. Further, a work load index is calculated, and a heatstroke onset risk index for the worker 10 is calculated by taking into account the temperature information inside the clothes and the environmental temperature information of the work place acquired via the Internet.

In addition, the specific details 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 workload index, the calculation of the heat stroke onset risk index, and the onset risk evaluation, which are performed by the evaluation determination unit 22. will be explained 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 information about the worker 10 to be determined. Based on environmental information such as changes in various information obtained from workers other than the worker targeted for assessment who are working at the same site as the worker, the evaluation results of the risk of developing heatstroke for 10 individual workers are corrected. This allows for more realistic management of the risk of developing heatstroke.

Note that in the physical condition evaluation system exemplified in this embodiment, it is not limited to the cloud server 21 that includes the evaluation determination section 22. For example, various functions of the cloud server 21 may be implemented on an administrator information terminal or a management computer at a business office, and as long as the functions can be realized, it does not matter where or what equipment the evaluation judgment unit is installed on. .

The personal computer 31 of the site supervisor 30 determines whether various information and warning information obtained by the biosensor 11 regarding the workers 10 belonging to the work site supervised by the site supervisor 30 including the worker 10 have been generated. The information management section 32 is provided to manage the information. Based on the information sent from the cloud server 21, the information management unit 32 constantly collects information obtained from each worker 10 and information that serves as a standard for evaluating the risk of developing heat stroke, such as whether or not warning information has been generated. We understand this as the latest information. In addition, the information management unit 32 outputs the obtained evaluation judgment results of the risk of developing heat stroke for each worker 10 and other environmental information to the display image processing unit 35, and the display image processing unit 35 outputs the obtained evaluation results of the risk of developing heat stroke of each worker 10 and other environmental information to the display image processing unit 35, The screen content displayed on device 36 is adjusted.

In this way, the site supervisor 30 can grasp information on the workers 10 working at the work site he supervises, the risk of developing heat stroke, etc., either as a whole or as detailed information for each worker on an easy-to-see screen. can do. Note that the specific screen content displayed on the display device 36 that has been processed by the display image processing unit 35 will only be able to display information required by a system that is appropriately formed in an easy-to-see manner; Detailed explanation will be omitted.

In addition, 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 not displayed on the personal computer 31 of the site supervisor 30. It is set in such a way that it cannot be understood. This means that if the site supervisor 30 can obtain the results of evaluating the risk of developing heat stroke for each worker 10, he or she can take measures to reduce the risk of developing heat stroke. This is a result of taking into consideration that the evaluation results have strong characteristics that each person should understand as part of their self-management, and that the workers 10 tend to dislike having others know the results of their physical condition evaluations. Furthermore, to whom and how the physical condition evaluation results should be fed back differs depending on the purpose of the physical condition evaluation system, the position of the evaluator, the administrator, etc., and should be set appropriately for each system. It will be done.

The personal computer 31 of the site supervisor 30 detects changes in the biological information obtained from the worker 10 after notifying the warning information and receives confirmation of receipt of the warning information from the worker 10, thereby determining whether the worker 10 is suffering from heat stroke. 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 heatstroke, a warning information is repeatedly sent to the worker 10 in question. It is possible to further alert the worker 10 by, for example, transmitting the following information.

In addition, in the above explanation, an example was explained in which the evaluation determination unit 22 of the cloud server 21 generates warning information that notifies the worker 10 that the risk of developing heatstroke is high. It can be generated by the information management unit 32 installed in the personal computer 31 of the site supervisor 30. Further, it is also possible to set both the evaluation determination section 22 and the information management section 32 to generate warning information. By doing this, warning information is generated from the personal computer 31 of the site supervisor 30 who is actually supervising the work site, and is transmitted to the target worker 10 in advance of the determination result by the evaluation determination unit 22. By doing so, 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 judgment unit 22 of the cloud server 21 or the personal computer 31 of the site supervisor 30 is transmitted from the data transmitting unit 34 of the personal computer 31 of the site supervisor 30 to a local network such as a wireless LAN or an information carrier of a mobile phone. The information is transmitted to the smartphone 12 equipped by the worker 10 via a network including the . Upon receiving the warning information, the warning notification unit 14 of the smartphone 12 uses various information transmission means such as audio, screen display, lighting or blinking of a lamp, and vibration to inform the worker 10 that he/she is suffering from heatstroke. Inform the public that there is an increasing risk of After confirming the warning information, the worker 10 reports that he has received the warning information through the touch panel or operation button of the smartphone 12, and also takes measures to prevent heat stroke, such as interrupting 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 confirmed the warning information and interrupted the work, and the supervisor 30 prevents the worker 10 from developing heatstroke. You can confirm that the measures have been taken.

Furthermore, in the heat stroke onset risk management system described in this embodiment, the heat stroke onset risk data at the work site that is understood by the site supervisor 30 is transmitted to the smartphone 12 of the worker 10, and the worker 10 You can check the current risk of developing heatstroke at the workplace where you work. For example, if it can be confirmed that workers other than themselves are at high risk of developing heat stroke, each worker can take measures to proactively prevent the onset of heat stroke. Furthermore, if it is known that there are other workers who have interrupted their work after receiving warning information about the risk of developing heatstroke, it is expected that the worker will respond obediently to the warning information sent to him/her from the foreman 30.

As described above, the smartphone 12 owned by the worker 10 allows the worker to view physical condition evaluation result information such as the current physical condition evaluation result of the worker 10 and the changes in the physical condition evaluation result over the past few days. It can be illustrated and displayed in an easy-to-understand format. A display example of this physical condition evaluation result will be described in detail later. In addition, the smartphone 12 owned by the worker 11 displays on the screen related information such as changes in the risk of developing heat stroke of the worker 10 to date, his or her own heart rate acquired by the biosensor 11, and calorie consumption. Then, the worker 10 himself can refer to it. Note that the display form of information other than the physical condition evaluation results may be such that necessary information can be displayed in an easy-to-see manner according to the respective display contents and purpose of display, and therefore detailed description thereof will be omitted in this specification.

The cloud server 21 is also connected to a management computer 41 in the company or business office 40 to which the worker 10 belongs via the Internet 20, and receives the measurement result information of the worker 10 sent to the personal computer 31 of the site supervisor 30, The cloud server 21 transmits various information used to determine the risk of developing heat stroke to the management computer 41 of the business office 40 in real time. The management computer 41 of the office 40 is equipped with its own data receiving section 42 and data transmitting section 43, so it is also connected to the personal computer 31 of the on-site supervisor 30 via the Internet, so that the on-site supervisor 30 can communicate with the worker 10. It is possible to check information such as whether the warning information was correctly transmitted to the workers and whether the worker 10 took measures to prevent heat stroke, and give predetermined instructions as necessary. Therefore, it is possible to effectively back up the avoidance of the risk of the worker 10 developing heat stroke.

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 cannot be accessed from the personal computer 31 or the management computer 40. It is possible to control the data processing content in the cloud server 21, update the determination program in the evaluation determination unit 22, and retrieve information necessary for heat stroke prevention management from the cloud server 21 as appropriate. .

In the above explanation, a smartphone is used as an example of a mobile terminal that a worker is equipped with, but the mobile terminal of a worker is not limited to a smartphone, and may include a mobile phone, a tablet device, and even a heat stroke risk management system. It is possible to use a dedicated small terminal device that can transmit and receive information. In addition, the administrator information terminal operated by the on-site supervisor can be a desktop computer, a notebook computer, a tablet computer, a small server device, etc., which can send and receive information, display data, record data, etc. through a network. Various information devices can be adopted.

Furthermore, in the above explanation, the warning information is sent from the site supervisor's administrator information terminal to the worker's mobile terminal, but if the warning information is generated by the evaluation judgment section of the cloud server, the cloud server The system can also be configured to send warning information directly to the worker's mobile device.

Furthermore, it goes without saying that the information communication means that connects the workers, the site supervisor, and the management department within the business office is not limited to those exemplified above, and that various information communication means for transmitting and receiving data can be used.

In addition, in the physical condition evaluation system described in this embodiment, an example of the arrangement of the biosensor 11 that acquires the heartbeat, temperature inside clothes, and movement of the worker 10 is to fix the biosensor 11 to the undershirt 18 shown in FIG. The method is not limited. For example, the biosensor 11 can be placed inside a highly adhesive sheet-like mounting cover and affixed directly to the chest, or an elastic mounting belt can be used to hold the biosensor 11 in close contact with the body. A method such as placing it on the chest of a person can be adopted. However, according to the method of attaching the biosensor 11 to the undershirt 18 worn by the worker 10 as shown in FIG. , it is possible to obtain necessary information without having to be particularly conscious of wearing a sensor. Furthermore, even if the worker 10 sweats or twists his or her body while working, the biosensor 11 fixed to the undershirt 18 will not come off the body surface of the worker 10, and the wearer will not be able to wear it. The position can also remain substantially unchanged. Therefore, although there may be cases where part of the heartbeat of the worker 10 cannot be acquired as heartbeat data, it is possible to avoid a situation in which no heartbeat data is continuously acquired.

Note that the biosensor 11 for acquiring the heartbeat data and acceleration data of the worker 10 can be placed in the waist, back, upper arm, or leg of the worker 10 in addition to the chest of the worker 10 described above. It is possible to adopt a form in which the information is placed in a location such as In addition, the system is not used as a system for managing the risk of developing heat stroke using the worker 10 working at a construction site as the person to be evaluated, as described in this embodiment, but for example, when evaluating the physical condition of an athlete training. In such cases, the person to be evaluated may wear sportswear, and in this case as well, it is most rational to place the biosensor 11 on the chest of the clothing worn on the upper body.

In addition, in the physical condition evaluation system according to the present embodiment, a biosensor that can be employed as a biometric information acquisition unit that captures heart rate data, which is biometric information of the person to be evaluated, detects a change in potential at an electrode unit as exemplified above. The present invention is not limited to those that acquire heart rate data. For example, a sensor that detects the pulse rate by optically detecting changes in the volume of the blood vessel of the person being evaluated, or a sensor that is worn on the wrist and detects the pulsation of the blood vessel as vibration, etc. Various sensors capable of detecting heartbeat or pulse can be employed.

Furthermore, the part that acquires the heart rate data of the person to be evaluated and the part that detects the acceleration data that indicates the movement of the person's body do not need to be located in the same member as in the example above; They may be placed in separate housings separated from each other. In order to detect the movement of the entire body of the person to be evaluated, it is preferable that the acceleration sensor that detects acceleration data is placed in a portion of the upper body of the person to be evaluated close to the trunk. For this reason, when using a wristwatch-type pulse sensor that is worn on the wrist to obtain the heart rate data of the evaluator, the acceleration sensor should be placed inside a separate measurement member, such as around the collar or chest pocket. It is conceivable that the device could be used to be worn on the upper body of the person being evaluated.

[Physical condition evaluation method]
Next, a physical condition evaluation method in the physical condition evaluation system according to this embodiment will be specifically explained.

In the physical condition evaluation system according to the present embodiment, heart rate data of the person to be evaluated detected by a heart rate detection means included in a measuring device worn by the person to be evaluated, and the state of the body of the person to be evaluated at the time when this heart rate data is obtained. Acceleration data obtained by a three-dimensional acceleration sensor, which is an index representing the movement of Evaluate your physical condition. In addition, as a heatstroke risk management system, we calculate a workload index that indicates the intensity of the worker's work based on the heart rate index, and also calculate the worker's internal temperature based on the temperature inside the worker's clothing obtained from the biosensor. The heat load index of the worker is calculated based on the environmental temperature of the work site. Then, based on the calculated workload index and heat load index, a heat stroke onset risk index indicating the risk of developing heat stroke is calculated.

In addition, in explaining the following physical condition evaluation method and the calculation method of the heatstroke onset risk index, each component of the physical condition evaluation system according to the present embodiment described using FIG. 1 will be appropriately illustrated and explained.

In the physical condition evaluation method according to the present embodiment, heart rate data and acceleration data detected by the biosensor 11 worn by the worker 10 who is the person to be evaluated are used, and based on the correlation between them, when the acceleration data is 0, That is, the heart rate index HR0 is determined by estimating the heart rate at rest without exercise. Generally, when a person is in poor physical condition, the resting heart rate increases, so if the heart rate index HR0 is larger than usual, it can be estimated that the person is not in good physical condition.

Note that the physical condition of the worker 10 is determined by estimating the heart rate when the acceleration data is 0 from the correlation between the heartbeat data and acceleration data detected by the biosensor 11 of the worker 10 who is the person to be evaluated. This method is a method that has been introduced in a conventional heatstroke onset risk management system. In the conventional heat stroke risk management system, heart rate data and acceleration data of the worker 10 are collected over a certain period of time (for example, about 2 hours or more), and a regression line is calculated based on the entire collected data. The value of the heartbeat when the acceleration data is 0 is determined as the heart rate index HR0.

On the other hand, in the physical condition evaluation method shown in this embodiment, representative heartbeat data and acceleration data are obtained from the heartbeat data detected from the biosensor 11 of the worker 10 who is the person to be evaluated and the values of several acceleration data points at that time. By calculating the value and multiplying this representative value by a predetermined coefficient, the median heart rate value when the acceleration data is 0 is calculated, and this value is set as the heart rate index HR0. Therefore, compared to conventional methods, it is possible to determine the worker's heart rate index from the measurement results in a short time, and it is possible to start assessing the worker's physical condition immediately after starting the measurement, and furthermore, to perform a real-time physical condition evaluation. Can be done. Further, changes in the physical condition of the person to be evaluated can be grasped from the change in the heart rate index HR0.

(Overview of heart rate index calculation method: Differences from conventional methods)
FIG. 3 is a diagram illustrating a method of calculating a heart rate index employed in a conventional heatstroke onset risk management system. In this specification, the heart rate index obtained by the conventional calculation method shown in FIG. 3 will be expressed as HR00.

In the conventional heatstroke onset risk management system, the median heart rate (median value of heart rate within a predetermined period) acquired by the biosensor 11 of the worker 10 and the three-dimensional value when the median heart rate was acquired For example, the acceleration displacement obtained by the acceleration sensor is collected for two hours or more, and more preferably for one day's working hours (about 8 hours). Then, based on all the data collected during this predetermined period, a regression line is calculated from the correlation between the central heart rate and the acceleration displacement.

More specifically, as shown in Figure 3, data that falls under 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]. Then, find the median heart rate value and median acceleration displacement value within the section. The "+" marks 31 to 37 shown in FIG. 3 indicate the coordinates of the median heart rate value and the median value of the acceleration displacement in each acceleration displacement section. A regression line 38 is determined from the seven points thus obtained, and the value 39 of the y-axis intercept of the regression line 38 is taken as the resting heart rate, which is the heart rate index HR00.

Note that the data for acceleration displacement of 0.05 [G] or more and less than 0.4 [G] is used because this is the region where the amount of exercise and heart rate change linearly for this degree of body movement. This is because it is thought to be, and is based on knowledge revealed through big data. On the other hand, data in which the acceleration displacement is less than 0.05 [G] is considered to be an area where changes in heart rate are caused by emotions rather than body movements. Furthermore, in a region where the acceleration displacement is 0.4 [G] or more, it is thought that the intensity of exercise and the increase in heart rate are approaching a region where the increase in heart rate does not necessarily change linearly, and in both cases the heart rate at rest is estimated. This is because it is thought that errors are likely to occur if used to do so. In this way, 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 increases linearly with respect to the size of the body's movement. It is possible to select the area as appropriate.

FIG. 4 is a diagram illustrating a method for calculating the heart rate index (HR0) employed 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 biosensor 11 of the worker 10 and the central heart rate detected by the three-dimensional acceleration sensor at the time when the data was obtained. They are the same in that the heart rate index corresponding to the resting median heart rate is calculated by finding the y-axis intercept from the acceleration displacement value, which is acceleration data. However, as mentioned above, in the conventional heatstroke onset risk management system, the heart rate index HR00 was calculated using the entire data collected over several hours, whereas in the physical condition evaluation system of this embodiment, several points ( At the stage when measurement results (for example, 7 points) are obtained, the median value of the heart rate value and the median value of the acceleration displacement is determined (shown as a "+" point 41 in FIG. 4), and a predetermined value is determined from this median value 41. Using the coefficients, that is, using a straight line with a predetermined slope (line indicated by reference numeral 42), the y-axis intercept 43 is determined and its value is set as the heart rate index HR0. By doing so, the physical condition evaluation system according to the present embodiment can calculate the physical condition of the worker based on the median heart rate obtained from the heart rate data of the worker who is being evaluated in a short period of about 10 minutes or less. can be evaluated.

(Specific example of data processing in physical condition assessment)
Hereinafter, regarding the physical condition evaluation method in the physical condition evaluation system according to the present embodiment, the details of specific data processing for calculating the heart rate index from the biological information of the person to be evaluated acquired from the biological information acquisition unit will be explained.

a. Preprocessing First, the heart rate data and acceleration data are preprocessed to calculate the heart rate index.

The preprocessing of the heart rate data is performed by calculating the median 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 poor contact between the skin of the person to be evaluated and the electrodes. Therefore, in order to prevent heartbeat data that is not detected correctly from being used for physical condition evaluation or heat stroke risk assessment, for example, if the heartbeat interval is 0.33 seconds or more, Data for which the time is 1.33 seconds or less and the difference (differential heartbeat interval) from the previous data is 0.15 seconds or less is determined to be normal and labeled.

Although the threshold value for determining normality/abnormality can be set arbitrarily, it is sufficient to set an appropriate value based on a physiological viewpoint so as to eliminate data on impossible heartbeat intervals. Then, the measured data is divided into k subintervals with a predetermined time width, and the heartbeat waveform detection rate Q is calculated as the percentage of data labeled as normal for each subinterval in the total data. . When the heartbeat waveform detection rate of a partial interval is a predetermined value, for example 50% or more, convert the heart rate data acquisition interval included in the partial interval to the heart rate per partial interval (for example, per past minute). to obtain the median heart rate HR. Here, the interval representative value of each partial interval may be the average value of each partial interval, but since the interval center is more preferable, in this embodiment, the interval median value is employed and is referred to as the median heart rate.

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

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

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

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) Calculating the sum of squares For the trend-removed time series acceleration, use the following formula (Formula 1) to calculate the squares at each time and find the sum.

4) Average acceleration per minute Calculate the average value "ΔA ² _ave " for each minute of the sum of squares "ΔA ² (t)" obtained above. Here, the average value is obtained by dividing by the number of data points. Further, the square root "ΔA _ave " of the root mean square of the acceleration "ΔA ² _ave " is calculated. 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-numeric data, heart rates of 40 or less and heart rates of 180 or more are removed as abnormal values. Furthermore, non-numeric data is excluded from acceleration data. These excluded data are not used for subsequent heart rate index calculations.

c. Calculation of heart rate index HR0 In the physical condition evaluation method of this embodiment, the acceleration displacement ΔA is 0.05 [G] or more and less than 0.25 [G] ( (see Figure 4) is adopted.

1) First physical condition evaluation after the start of measurement At the start of measurement, which is the start of the day's work, the acceleration displacement ΔA is 0.05 [G] as data after removing abnormal values obtained from the worker 10. At the stage when the measurement data of seven points is obtained in the range of less than 0.25 [G], the heart rate index HR0 at the time of starting the measurement is calculated. To calculate the median heart rate, which is the heart rate index HR0, calculate the weighted median value (xA, yHR) of each of the seven points of heart rate data and acceleration data obtained based on the measurement results of these seven points, and then apply a predetermined value to this. By multiplying by the coefficient, the median heart rate when the acceleration displacement is 0 [G] is estimated, and this value is set as the heart rate index HR0.

Here, as for the acceleration data, the weighted median value is calculated using the data of the seven points obtained after the start of the evaluation as is. On the other hand, the heart rate data includes two pieces of data in the range of 0.05 [G] or more and less than 0.25 [G] obtained at the time of the most recent physical condition evaluation of the worker 10, for example, in addition to the obtained seven points of data. , the weighted median value in the range of acceleration displacement of 0.05 [G] or more and less than 0.10 [G] and 0.20 [G] or more of the heartbeat data acquired during the physical condition evaluation of the worker the previous day. The weighted median value is calculated from a total of nine points of heartbeat data, including two points with the weighted median value in the range of less than 0.25 [G]. By doing so, abnormal deviation from the standard value can be prevented.

As the predetermined coefficient, the slope (αHR) of the regression line between the heart rate data and acceleration data obtained as the measurement results for one day at the time of the most recent physical condition evaluation of the worker 10 is used. Note that the method for determining this regression line can be the same as the method for determining the regression line when determining the workload index in the conventional heatstroke onset risk management system described above using FIG. 3. Specifically, the acceleration displacement is 0.05[ G] or more and less than 0.40 [G], for example, it can be calculated from a weighted median value within an interval of 0.05 [G].

Then, the coefficient αHR obtained as the measurement result of the previous day of the worker is used as the median value (xA, yHR) of the heart rate data and acceleration data obtained based on the data of the first seven measured points. Using the following formula, calculate the heart rate index HR0 as the estimated resting central heart rate, which is the y-axis intercept, as shown in Figure 4.
HR0=yHR−αHR×xA.

In addition, when the worker to be evaluated becomes the person to be evaluated by the physical condition evaluation system according to the present embodiment for the first time, two points of data in addition to the seven points obtained as the measurement results as heartbeat data and heart rate index HR0 Standard data that can be considered as standard numerical values is substituted for the predetermined coefficients used in the calculation. As this standard data, the average value or median value of all 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 engaged in the same work as the worker to be evaluated at the work site, and the results of measurements of a group of workers who are similar to the worker to be evaluated in terms of physique such as height and weight, age, gender, etc. Numerical values that are considered appropriate to be substituted as numerical values representing the standard condition of the person to be evaluated, such as group measurement results, can be appropriately employed.

2) Second and subsequent physical condition evaluations After calculating the first heart rate index HR0 as described above, the heart rate index HR0 is calculated at predetermined intervals of, for example, 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 the evaluation, but do not use data that has passed a certain period of time (for example, 2 hours) at the time of the evaluation. A heart rate index is calculated using only heart rate data and acceleration data that have not been acquired for two hours. In other words, the amount of data used to calculate 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 data to be calculated is sequentially replaced and the data used to calculate the heart rate index is increased. Calculate heart rate index.

In this case, if the number of points that satisfy the condition that the acceleration displacement ΔA is 0.05 [G] or more and less than 0.25 [G] is 8 or less, the data that satisfies the condition (8 or less) is used as the acceleration data. A weighted median value is calculated using all the values and set as yHR. Regarding the heartbeat data, a weighted median value is calculated for a maximum of 10 pieces of data obtained by adding the same two pieces of 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.

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

In addition, in order to prevent large fluctuations in the heart rate index that occur when measurement accuracy is low, the range of fluctuation from the heart rate index value calculated immediately before (10 minutes ago) is set within a predetermined range (for example, ±5 ppm). ) may be considered.

3) Calculation of index after one day's measurement is completed When one day's measurement is completed, the intercept median heart rate (heart rate index) HR (day) and heart rate response coefficient (slope of regression line) α (day) for that day are calculated. Calculate.

First, data with an acceleration deviation of 0.05 [G] or more is divided into two partial sections I1 and I2, with 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 heart rate index HR obtained at the end of the day is used as HR (day) without calculating the value. Then, the numerical value 54.1 is adopted as α (day).

If there are 20 or more data points in subintervals I1 and I2, calculate the median values yI1 and yI2 of heartbeat data and the median values xI1 and xI2 of acceleration data for the data in each subinterval, and calculate the 2 points ( A formula for a straight line passing through xI1, yI1) and (xI2, yI2) is found, and its y-axis intercept is HR (day), and its slope is α (day).

That is,
HR (day) = yI1-xI1・(yI2-yI1)/(xI2-xI1)
α(day)=(yI2-yI1)/(xI2-xI1)
becomes.

However, if HR (day) is 45 bpm or less or 105 bpm or more, and α (day) is 20 or less or 100 or more, these are judged to be abnormal values and a boundary value is adopted. do.

In addition, when determining 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 body movements of the worker 10 who is the person to be evaluated, using standardized data, PI (day )=α(day)/54.1.

4) Physical condition evaluation from the second day onward Regarding the physical condition evaluation method from the second day onward, the heart rate index calculation method involves repeating the above-mentioned procedure as is. Note that data from the first day, which is the previous day, can be used for both the coefficient α (HR) when calculating the heart rate index and the data added to the seven measurement data points when calculating the first heart rate index.

In addition, in the physical condition evaluation from the second day onward, when calculating the daily index after the measurement is completed, if the number of data satisfying the condition in the two partial intervals I1 and I2 is less than the predetermined number of 20, HR ( The values of HR (day) and α (day) are the value of HR (day) obtained on the previous day or the value obtained most recently, and the value of α (day) obtained on the previous day or the value obtained most recently. The only difference is that .

(Physical condition evaluation based on heart rate index)
As explained above, in the physical condition evaluation method according to the present embodiment, immediately after the start of measurement, and At predetermined intervals (10 minutes in the above example), a heart rate index that can be assumed to be the resting heart rate of the person being evaluated can be calculated.

When the person to be evaluated is in poor physical condition, the amount of activity decreases, so the heart rate increases even if the person performs an operation with the same load. Furthermore, for example, when the temperature at a work site is high, the core body temperature rises due to increased heat stress, so the heart rate also rises even when performing operations with the same load. In such a case, in the graphs showing the correlation between acceleration displacement and central heart rate shown in FIGS. 3 and 4, the distribution of coordinate points representing measurement data moves upward or diagonally upward. In the physical condition evaluation method shown in this embodiment, the value of the y-axis intercept indicating the resting heart rate is calculated using a line with a predetermined slope from the coordinates indicating the median value of the median heart rate and the median value of acceleration displacement. Therefore, when a person is unwell, the numerical value HR0 increases. Using this, it is possible to grasp the physical condition of the person to be evaluated at the time of acquiring the biological data.

Note that if the person being evaluated is sleepy or has an imbalance in the autonomic nervous system (parasympathetic nervous tension), the heart rate data itself will be a small value, so the acceleration displacement and center shown in Figures 3 and 4 will be In the graph showing the correlation with heart rate, heart rate index HR0, which is the y-axis intercept, has a small value.

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

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

FIG. 5(a) shows an evaluation map for worker A, and FIG. 5(b) shows an evaluation map for worker B.

The two evaluation maps both show the heart rate index on the vertical axis and the physical fitness index on the horizontal axis, and each person's physical condition is in the "normal" range 51, the "slightly cautious" state 52, which is a little unwell, A range 53 of a "caution" state where the user is not feeling well is shown in a manner that can be understood at a glance by changing the display pattern and display color. The current (recent) physical condition evaluation results of each worker are displayed as marks (circles), such as 54 for worker A and 55 for worker B.

For example, in the case shown in FIG. 5, the display mark 54 indicates that worker A is not feeling well and needs some attention, and the display mark 55 indicates that worker B is currently feeling worse than usual. This state indicates that you should be careful when performing work that requires a large load.

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

For example, the "normal" range can be set as a 95% presence region, and the "slightly cautious" range can be set as a 98% presence region. In addition, since the physical condition evaluation results for one day are required as data, if the worker to be evaluated has only a few days to undergo the physical condition evaluation using the physical condition evaluation method according to this embodiment, provisional evaluation may be made as appropriate as shown below. The values are used to determine the "normal" and "caution" ranges shown on the physical condition evaluation map.

First, if it is the first or second day that the worker who is being evaluated uses the system, that is, if the past data is less than two days' worth, then the provisional average heart rate index and its provisional Standard deviation will be used.

Specifically, as standard values calculated based on the analysis of big data, for 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, a provisional average value PI (day) _ave = 1.0 and a provisional standard deviation σPI (day) = 0.35 are used.

As a result, the range of “normal” 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
Then,
The range of “slightly careful” 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
becomes.

From the 3rd to the 5th day, when there is more than 2 days worth of daily measurement data and less than 4 days worth of measurement data in the physical condition evaluation system, the average values of the heart rate index and physical fitness index are based on 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 value of the standard deviation which is the standard of width. By doing so, it is possible to create an evaluation result map that better reflects the physical condition of the worker who is being evaluated.

Specifically, the range of “normal” 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
Then,
The range of “slightly careful” 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
becomes.

From the 6th day onwards, since the heart rate index data and physical fitness index data of the worker have been accumulated for more than 5 days, the actual values obtained from the measurement results are used for both the average value and standard deviation.

In other words, the range of "normal" is
Heart rate index HR (day) is
HR (day) _ave ±1.96×σHR (day) _ave [bpm]
Physical fitness index PI (day) is
PI(day) _ave ±1.96×σPI(day) _ave
Then,
The range of “slightly careful” is:
Heart rate index HR (day) is
HR (day) _ave ±2.33×σHR (day) _ave [bpm]
Physical fitness index PI (day) is
PI(day) _ave ±2.33×σPI(day) _ave
becomes.

Next, another method of displaying the physical condition evaluation results in the physical condition evaluation method according to the present embodiment will be explained.

FIG. 6 is an example of a first display screen showing the transition of physical condition evaluation results 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 results of the worker 10 who is the person to be evaluated, the left side shows the changes by measurement day, and the right side shows the changes by measurement time on the measurement day. are shown respectively.

In particular, in the physical condition evaluation method according to the present embodiment, since physical condition evaluation can be performed at predetermined time intervals (10 minutes in the above example), physical condition evaluation results for each hour of the day as shown on the right side of FIG. It is possible to show the transition of This allows the person to be evaluated to understand whether their physical condition is good or bad on the day of the measurement by comparing it with the average physical condition evaluation results for the past few days shown on the left side of Figure 6. As shown in the figure, it is possible to objectively understand changes in one's physical condition, such as not feeling well around noon. For this reason, the cause of your poor physical condition can be determined based on your own condition, such as whether the cause of your poor physical condition is due to the work environment that day, or whether you are still feeling tired because you did not get enough rest the day before. can be considered.

As a result, the user can select and implement measures to manage his or her own physical condition, such as taking better measures against the heat the next day or taking sufficient rest to recover from fatigue. In addition, since physical condition evaluation results are information with a relatively high level of privacy, it is assumed that consideration will be required, such as ensuring that detailed disclosure of physical condition evaluation results is limited to the person being evaluated. .

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

This second display example allows the worker 10, who is the person being evaluated, to know whether his or her current physical condition evaluation result is within the normal range, or whether it is within the range of caution or caution. It should be 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 marked with a predetermined mark such as a circle (symbol 71, 71'). This predetermined mark (numerals 71, 71') moves to the right in the figure every time the physical condition evaluation result is updated. At this time, at the same time as these marks (numerals 71, 71'), a frame 72 indicating the normal range of the physical condition evaluation result and a frame 73 indicating the range requiring some caution are displayed. By doing this, the physical condition evaluation result, which was in the normal range 72 at the time of FIG. 7(a), slightly falls outside the cautionary range 73 at the time of FIG. You can visually see what is in the area. By doing so, the worker 10 can immediately grasp sudden changes in his or her own physical condition evaluation results.

FIG. 8 is a display example of the physical condition evaluation results in the physical condition evaluation method according to the present embodiment, and is a display example in which the history of the physical condition evaluation results is clearly shown.

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

In the physical condition evaluation method according to the present embodiment, since it is possible to grasp the changes in the physical condition evaluation results of the person being evaluated, it is possible to display the physical condition evaluation results for each measurement day so that the changes are clear, as shown in FIG. can. In this way, by displaying the trends in the daily physical condition evaluation results over multiple measurement days, the worker 10 can check the overall height of the heart rate index HR0 for each measurement day as well as the heart rate index HR0 for each measurement day. It is possible to grasp the trend of fluctuations in As a result, the worker 10 can determine, for example, the tendency of the time period when the heart rate index HR0 is high, and on days when the heart rate index HR0 is high (or low), the value in the afternoon is higher (lower) than the value in the morning. You can grasp the fluctuation trend of your own heart rate index HR0 at a glance.

In addition, the boundaries of each evaluation range such as "normal", "slightly cautious", and "caution" in FIGS. 6, 7, and 8 and the size (width) of each range are based on the past It may be updated as needed using 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 in FIGS. 6, 7, and 8 are variable, and the range display can be changed every day, for example. With this, as the accumulated data increases, it is possible to display a physical condition evaluation result that is more optimized for the individual worker.

Note that the display method for notifying the worker, who is the person to be evaluated, of the evaluation results of the physical condition evaluation method according to the present embodiment is not limited to those shown in FIGS. 6, 7, and 8. Taking advantage of the ability to understand your own physical condition evaluation results in real time, there are ways to display only the physical condition evaluation results such as "normal," "slightly cautious," or "warning" at any time, or to display the physical condition evaluation results in chronological order. Taking advantage of the feature that can be grasped, various methods such as displaying the changes in physical condition evaluation results from the previous day or a specific day specified by the worker and the changes on the current day can be displayed so that the differences can be easily understood. There are several possible display methods.

In addition, regarding the display of physical condition evaluation results, we have proposed a method in which the entire screen of a display medium such as a smartphone is displayed by the operator's operation, and a method that displays the results of the physical condition evaluation using the entire screen of a display medium such as a smartphone. The method of displaying the physical condition evaluation results, the timing of display, the display size, etc. can be selected as appropriate.

In this way, by displaying the physical condition evaluation results as an easy-to-understand display screen, the advantage 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.

[Heatstroke risk assessment method]
Here, a heatstroke onset risk evaluation method using a heatstroke onset risk management system equipped with the physical condition evaluation system according to the present embodiment will be briefly mentioned.

As mentioned above, the risk of developing heatstroke is evaluated based on the workload index calculated using heart rate data and acceleration data acquired by the biosensor 11 worn by the worker 10 who is the person to be evaluated, and the work load index obtained by the biosensor 11. The heat load index of the worker 10 is calculated from the internal clothing temperature data and the environmental temperature data.

<Calculation of workload index>
Regarding the heartbeat data and acceleration data used to calculate the workload index, "a preprocessing" and "b abnormal value removal" of the measurement data are performed as described above as a specific example of the physical condition evaluation method.

In addition, in the physical condition evaluation method, data when the heartbeat waveform detection rate was less than a predetermined value (50%) was not used to calculate the heart rate index. The difference is that when the detection rate is less than a predetermined value, only acceleration data is used without using heartbeat data.

Based on the median heart rate, which is heart rate data, and the acceleration deviation, which is acceleration data, obtained in each partial interval, data is acquired over a period of more than a predetermined time (for example, two hours) as shown in Figure 3. A regression line is calculated from , and its slope is defined as the heart rate response coefficient αr, and the y-axis intercept is defined as the intercept heart rate βr.

Next, the median heart rate value HR obtained in each sub-interval is converted into a standardized heart rate HRs using the following (Equation 2).

HRs=(αs/αr)(HR−βr)+βs (Formula 2)
In the above equation (2), αs is the standard response heart rate count, βs is the standard intercept heart rate, and the slope of the regression line in the standard heart rate response model that is considered to show the correlation between standard heart rate data and 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. A model that represents the standard human heartbeat response to acceleration (body movement), and can be expressed using various parameters and predetermined mathematical formulas. In the heatstroke onset risk management system according to the present embodiment, the standard heart rate response coefficient αs and the standard intercept heart rate βs are determined by using the regression line between heart rate data and acceleration data using the method shown in FIG.

Note that the large-scale data may be data from the past several days of a plurality of workers at the site, or may be accumulated data sampled in advance at another site. Preferably, a standard heart rate response model is created based on large-scale data obtained by measuring a large number of workers engaged in similar work to the worker in question. This is a heartbeat response model optimized for the task in question, and is considered to represent the typical heartbeat response of a worker engaged in the task. Although there is no particular limit to the number of people on which large-scale data can be based, the larger the number of samples, the more accurately the heart rate response can be approximated. Preferably the number is 5 or more, more preferably 50 or more. Although there is no particular rule regarding the accumulation period, it is preferable to acquire data for two or more days, more preferably for five 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 workload index from heart rate data based on the characteristics of the individual worker who is the person to be evaluated.

In addition, if the detection rate of heart rate data is low and a workload index is calculated using only acceleration data, convert the acceleration data (acceleration deviation) to a workload index using a predetermined formula, such as multiplying it by an appropriate coefficient. do it. Furthermore, it is possible to use an estimated standardized heart rate calculated based on the value of the acceleration deviation and a function (correlation curve) indicating the correlation between heart rate data and acceleration data calculated from a standard heart rate response model.

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

The correction map used is one that shows the correlation between heart rate data and acceleration data, and depending on the magnitude of the acceleration data, data on the upper side and data on the lower side of the correlation curve indicating the standard heart rate response model can be adjusted to the measured data. It is indicated whether to use the standardized heart rate HRs obtained based on this as is as the corrected heart rate HRc, or to use the value of the correlation curve or the corrected heart rate HRc shown as a specified value on the map. In addition, a correction map that is used when the heartbeat detection rate is high is prepared separately, and by increasing the degree of adoption of the standardized heart rate when the heartbeat detection rate is high, it is possible to more accurately match the actual situation. It is possible to calculate a workload index.

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

First, the corrected heart rate HR _c is converted into metabolic equivalents (METs) using the following formula (Equation 3).

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

Next, the metabolic equivalent METs is converted into a workload index W using the following formula (Equation 4).

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

For example, when setting a _W = 0.2 and b _W = -0.2, as a work load evaluation, if the work load index W is 0.6 or more, it is considered a task with a high metabolic rate, that is, a work with a low burden. When the work is large and the value of W is 1 or more, it can be a work that requires an extremely high metabolic rate, that is, a work that places a very heavy 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 temperature data inside the clothes of the worker 10 obtained from the biosensor 11 and the environmental temperature data at the site where the worker 10 works. . Note that the environmental temperature data at the work site is the temperature data around the work site acquired by the weather information acquisition unit 25 of the cloud server 21, or when the worker is working indoors, the temperature at the work site. It can be acquired based on temperature information etc. obtained from a sensor.

The heat load index H is determined by the following formula (Formula 5) using the clothing temperature Ti obtained by the measuring device 11 and the outside temperature To obtained as the environmental temperature.

Note that 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.

<Assessment of risk of developing heat stroke>
Using the workload index W and the heat load index H obtained by the above calculation, the heatstroke onset risk evaluation index R of the worker 10 to be evaluated is determined as shown in the following formula (Formula 6).

Here, a is a numerical value defined in accordance with the heat acclimatization of the worker to be evaluated; in the case of heat acclimation, a=-1.8, and in the case of no heat acclimation, a=-1. Set it to 3.

Regarding the heatstroke onset risk evaluation value R obtained as above, if R is less than 0.6, the risk of onset is low risk, and if R is 0.6 or more and less than 1.0, it is a warning level that requires caution. If R is 1.0 or more, it can be determined that there is a high risk of developing heat stroke.

Furthermore, since it is not possible to verify the actual occurrence of heat stroke, when establishing the criteria for determining the risk of developing heat stroke, we aim to determine the risk of developing heat stroke more strictly, that is, to be on the safer side. Should.

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

Note that w ₁ =2/31 and w ₂ =2/11 here.

Furthermore, the exponential moving average value of the heatstroke onset risk index R is determined from the following formula (Formula 9).

For example, if the exponential moving average value of the heatstroke onset risk index R continues to be 1 or more for 30 minutes or more, it is determined that the risk of developing heatstroke is extremely high, and the worker is advised to take a break. Take countermeasures to prevent heat stroke, such as encouraging heatstroke.

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

Utilizing this fact, the heatstroke onset risk index can be displayed as a heatstroke onset risk index on a two-dimensional map with the heat load index and the workload index as axes, respectively. For example, by displaying symbols on a two-dimensional map that correspond to the current heat stroke risk index for each of the multiple workers 10 managed by the site supervisor 30, who is the manager, the site supervisor 30 can allows you to understand at a glance the overall risk indicators for managed workers. Note that a specific description of the display image that displays the degree of risk of heatstroke of the worker 10 will be omitted.

As explained above, in the physical condition evaluation method and physical condition evaluation system disclosed in this application, based on the heart rate data and acceleration data of the evaluated person detected by the measurement device worn by the evaluated person, the physical condition can be evaluated using a small number of data. can be evaluated.

Therefore, physical condition evaluation can be performed immediately after starting measurement. Therefore, for example, if a worker working at a construction site is the person being evaluated, their physical condition can be evaluated immediately after starting work, and if the worker feels uncomfortable, It can be used as data that objectively shows your physical condition.

In addition, by taking advantage of the fact that it is possible to evaluate physical condition with a small amount of data, it is possible to always show the latest physical condition evaluation results. It is possible to grasp the trends in physical condition evaluation results at the time.

In addition, when measurements are taken continuously over multiple days, it is possible to understand daily changes in one's physical condition, such as how to take a rest on the weekend, how much sleep and rest time one needs. It is possible to provide valuable data that can be used in managing the physical condition of the person being evaluated.

In addition, in the above embodiment, an example was shown in which the physical condition evaluation system disclosed in the present application is installed in a heatstroke onset risk management system in which workers working at a construction site etc. are evaluated. The system is not limited to physical condition evaluation, and it is possible to evaluate the workload index, physical condition evaluation index, heat stress index, exercise load index, and other indices of each assessee based on the acquired biological information. It can be installed in biological information processing systems.

For this reason, biometric information processing is required for a wide range of purposes, such as the physical condition management of athletes during training and the physical condition management system for residents at elderly care facilities. It can be used as a means for physical condition evaluation in systems that perform

The physical condition evaluation method and physical condition evaluation system disclosed in this application can calculate the heart rate index from a small amount of measurement data, making it possible to evaluate the physical condition immediately after starting the measurement, and to monitor the changes in the physical condition evaluation results. can be grasped. Therefore, the present invention is extremely useful as a physical condition evaluation method and system for evaluating various types of people, including those for evaluating the physical condition of workers at work sites and the like.

10 Worker (evaluated person)
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 (6)

A physical condition evaluation method for evaluating the physical condition of the person being evaluated on the day using a computer operated by a computer program,
a step of acquiring heart rate data and acceleration data of the evaluated person on the day of evaluation in a biological information acquisition unit;
a step of determining a representative value of the heartbeat data and a representative value of the acceleration data on the evaluation day based on the acquired plurality of the heartbeat data and the plurality of the acceleration data;
The subject is evaluated using a representative value of the heart rate data, a representative value of the acceleration data, and a heart rate response coefficient indicating the relationship between the heart rate data and acceleration data calculated based on the measured data of the subject up to the previous day. A physical condition evaluation method characterized by calculating the evaluator's heart rate index and evaluating the physical condition of the evaluator on that day . The heart rate index is an estimated resting heart rate of the evaluator, calculated based on the heart rate data and acceleration data, and is based on the discrepancy between the heart rate at rest and the heart rate index in normal times. The physical condition evaluation method according to claim 1, wherein the physical condition of the person to be evaluated is evaluated at the time of measurement. The physical condition evaluation method according to claim 1 or 2, wherein the representative value of the heartbeat data and the representative value of the acceleration data are both median values of data measured by the biological information acquisition unit within a predetermined measurement period. . a biological information acquisition unit that acquires heart rate data and acceleration data on the day of evaluation as biological information of the person to be evaluated;
and a data processing unit that calculates a heart rate index of the subject based on the acquired biological information,
The data processing unit calculates a representative value of the heartbeat data and a representative value of the acceleration data on the evaluation day based on the plurality of the acquired heartbeat data and the plurality of acceleration data,
The subject is evaluated using a representative value of the heart rate data, a representative value of the acceleration data, and a heart rate response coefficient indicating the relationship between the heart rate data and acceleration data calculated based on the measured data of the subject up to the previous day. A physical condition evaluation system characterized by calculating an evaluator's heart rate index. 5. The method according to claim 4 , further comprising an image display unit that displays a physical condition evaluation result, and wherein the image display unit displays the degree of deviation between the resting heart rate of the person to be evaluated and the heart rate index in normal times on a map. Physical condition evaluation system described. The physical condition evaluation system according to claim 4 , further comprising an image display unit that displays a physical condition evaluation result, and wherein the image display unit displays the transition of the heart rate index.