JP7264393B2 - Group environment evaluation method and group environment evaluation system - Google Patents

Description

The present application identifies multiple subjects under common environmental conditions as one group, and evaluates the environment in which the group is placed based on biometric information obtained from multiple subjects belonging to this group. It relates to a group environment evaluation method and a group environment evaluation system.

In recent years, the environment for connecting to the Internet such as wireless LAN has been improved, and the means to enable information transmission at short distances such as Bluetooth (registered trademark) has been developed. With the spread of small sensor devices that can measure body data such as heart rate, sweat rate, etc., the biological information of the subject acquired by the sensor device can be transmitted to a mobile device connected to the Internet, and the health of the subject can be monitored. Management systems have been put into practical use that manage conditions and prevent unexpected situations such as accidents caused by poor physical condition.

As an example of such a physical condition management system, there is known a system for managing the risk of heat disorders such as heat stroke, for which an increase in the risk of onset has become a social problem due to global warming. For example, by having the managed person wear a housing having an acceleration sensor, an ultraviolet sensor, a GPS receiver, an operation input unit, a display/audio notification unit, an Internet connection unit, etc., the amount of exercise of the managed person and the Determine the risk of developing heatstroke using the WBGT index based on weather conditions such as temperature and humidity obtained via the Internet, and determine the risk of heatstroke according to the determination results. A heat stroke onset prevention system has been proposed that prevents the onset of heat stroke by instructing a person to rest (see Patent Document 1).

In addition, weather data from a weather measuring device placed in an area where a plurality of assessees exercise, activity information obtained by an activity sensor carried by each of the plurality of assessees, and each of the plurality of assessees Based on the biometric information acquired by the biometric information sensor carried by the assessee, the physical condition level of each of the multiple assessees moving in the area is determined, and if it is determined that the assessee is in a dangerous state, There has been proposed a monitoring system that notifies to (see Patent Document 2).

JP 2012-210233 A JP-A-2013-85896

As described above, conventional systems for preventing the onset of heat stroke and monitoring systems for monitoring the physical condition of an evaluator grasp and manage the physical condition of multiple evaluators, but the evaluation results are the only evaluators. Staying on the subject of each.

In this way, by evaluating the physical condition of each person being evaluated, it is possible to understand individual differences and changes in the physical condition of the same person depending on time and place. In this case, a warning can be given to the person concerned. However, biometric information such as heart rate varies greatly among individuals, making accurate evaluation difficult. In order to reduce the influence of individual differences, it is necessary to evaluate using, for example, a heartbeat response model estimated from individual past accumulated data and large-scale empirical data, which requires complex algorithms and a large amount of data. there were.

In addition, such a system for evaluating an individual cannot evaluate a person who is not wearing a sensor. For example, even if there is a person who is in the same environment as the person being evaluated, i.e., a person who is doing the same work or exercise in the same place, if that person wears a sensor that measures biological information and the amount of activity, If the person is not an evaluation target of the physical condition evaluation system, the change in the physical condition level of the person cannot be grasped.

On the other hand, as an environmental index for grasping the magnitude of the thermal load on the human body, there is the WBGT (wet bulb globe temperature) index, which is also used in the heat stroke risk prevention system. The WBGT index is an index based on the measurement results at outdoor measurement points in a specific area, and when the conditions are different from the measurement points, such as indoor workers or workers in places exposed to direct sunlight. cannot be an accurate indicator for In addition, in recent years, the highest temperature in Japan has exceeded 40°C, and the summer heat is increasing due to the effects of global warming. It is difficult to say that we have been able to respond sufficiently as an evaluation.

The purpose of the present application is to solve the problems of the above-described conventional technology, and to accurately determine the work environment and exercise environment in which the subject is actually placed using biological information obtained from a plurality of subjects. It is an object of the present invention to provide a group environment evaluation method and a group environment evaluation system that can evaluate

In order to solve the above problems, the group environment evaluation method disclosed in the present application is characterized by evaluating the environmental risk in a group based on biological information obtained from a group of subjects.

In addition, the group environment evaluation system disclosed in the present application includes a measuring device that acquires biological information of a subject, and based on the biological information acquired from the plurality of subjects, an environment in a group of the plurality of subjects. and an evaluation determination unit that evaluates the risk.

With the above configuration, the group environment evaluation system disclosed in the present application can quantitatively evaluate the environment itself in which the group is actually active. environmental risk in the population can be accurately assessed without

In addition, in the group environment evaluation system disclosed in the present application, the evaluation determination unit can grasp the biological information of the subjects forming the group to be evaluated in real time, and the environmental risk in the group can be quickly evaluated. .

In addition, since environmental risks can be evaluated quantitatively, it is useful as a tool for visualizing the effects of on-site environmental improvements and countermeasures, such as the introduction of air-conditioning equipment and the setting of appropriate break times and rest areas.

FIG. 1 is an image diagram illustrating the overall configuration of a hot environment evaluation system described as an embodiment. FIG. 2 is a block diagram showing the configuration of each part of the hot environment evaluation system described as an embodiment. FIG. 3 is a diagram for explaining the configuration of an undershirt equipped with a biosensor, which is a measuring device for acquiring various types of information on a person to be managed. FIG. 3(a) shows the front side of the undershirt, and FIG. 3(b) shows the back side of the undershirt. FIG. 4 is a flow chart explaining a method for evaluating the risk of developing heat stroke in the hot environment evaluation system explained in this embodiment. FIG. 5 is a diagram showing a measurement result of a standard heartbeat response showing a heartbeat response to an acceleration deviation. FIG. 5(a) shows a plot of all about 3 million points of data, and FIG. 5(b) shows a standard heartbeat response obtained using the median heartbeat response to the acceleration data. FIG. 6 is a diagram explaining a method of estimating a heartbeat index and a physical strength index in the hot environment evaluation method according to the present embodiment. FIG. 7 is a diagram for explaining the first correction map for obtaining the work burden index in the work burden estimation method explained in this embodiment. FIG. 8 is a diagram for explaining a second correction map for obtaining a work load index in the work load estimation method described in this embodiment. FIG. 9 is an image diagram showing the core temperature and body temperature distribution of humans. Fig. 9(a) shows the resting state at a temperature of 20°C, Fig. 9(b) shows the resting state in a high temperature environment of 35°C, and Fig. 9(c) shows a high temperature environment of 35°C. It shows the state of working in FIG. 10 is a diagram showing changes in the average heart rate of a group acquired by the hot environment evaluation system according to this embodiment. FIG. 11 is a diagram showing changes in average heart rate across group rests, acquired by the hot environment evaluation system according to the present embodiment. FIG. 12 is a diagram showing changes in the average heart rate of a group for one day, acquired by the hot environment evaluation system according to this embodiment. FIG. 13 is a diagram showing changes in the average heart rate of a group, showing an example of environmental evaluation using the hot environment evaluation system according to this embodiment. FIG. 14 is a diagram showing an example of heatstroke risk assessment based on group average heart rate using the hot environment assessment system according to the present embodiment. FIG. 15 is a diagram showing an example of heatstroke risk assessment based on the average value of the work load index using the hot environment assessment system according to the present embodiment.

The group environment evaluation method disclosed in the present application evaluates environmental risks in a group based on biological information obtained from a group of subjects.

In this way, by performing a group environmental evaluation based on biometric information obtained from a plurality of subjects (evaluated persons), the group environment evaluation method disclosed in the present application can reduce individual differences among subjects and The environmental risk can be quantitatively evaluated based on the average biological response of the group regardless of the physical condition at the time of evaluation.

In the group environment evaluation method disclosed in the present application, the biological information is the heart rate of the subject, and the hot environment risk in the group is evaluated based on the representative value of the heart rate of the subject belonging to the group. is preferred. By doing so, it is possible to accurately evaluate a group's hot environment based on the group's heart rate, which is a common factor of hot environment risk.

In this case, it is preferable to use, as the representative value of the heart rate, any one of the average value, the median value, or the mode value of the heart rates of the plurality of subjects. An increase in heart rate indicates an increase in the core temperature of the human body in response to heat stress, and representative heart rate values obtained by these methods are highly reliable indices of heat stress.

Moreover, it is preferable that the group consists of a plurality of subjects having common environmental conditions. Here, "environmental conditions are common" means that the geographic conditions, weather conditions, work contents, etc. of a plurality of subjects are at the same level within a certain range. For example, a group may be formed by a plurality of subjects existing within a predetermined range such as the same municipality, the same building, the same site, or the same venue. Moreover, a group may be formed by a plurality of subjects engaged in the same work or the same service. By forming a group of subjects with common environmental conditions, more accurate environmental evaluation can be performed.

Further, the biological information includes heartbeat data of the subject and acceleration data indicating motion of the subject, and based on the heartbeat data and the acceleration data obtained from the plurality of subjects belonging to the group It is preferable to calculate a work burden index for each of the subjects, and evaluate a hot environment risk in the group based on a representative value of the work burden index of the subjects belonging to the group. By doing so, it is possible to evaluate the heat of the group in consideration of the magnitude of the workload, and to more accurately evaluate the risk of the heat environment of the group. The group environment evaluation system disclosed in the present application includes a measuring device that acquires biological information of a subject, and an environmental risk in a group of a plurality of subjects based on the biological information obtained from the plurality of subjects. and an evaluation determination unit for evaluation.

By doing so, the biological information of the subject can be acquired and evaluated at any time, so the environment to which the evaluation target group is exposed can be quickly evaluated.

Further, it is preferable to include information transmission means for transmitting the acquired biometric information to the evaluation determination unit.

In the group environment evaluation system disclosed in the present application, it is preferable that the evaluation determination section is installed in a server on a network. By installing the evaluation judgment part on a server on a network such as the Internet or an intranet, it is possible to operate the group environment evaluation system as a cloud service. It can be carried out. In addition, more accurate group evaluation can be performed by reflecting information of other groups placed in a similar environment in the evaluation results as necessary.

Moreover, it is preferable that the measuring device includes a heartbeat sensor for detecting heartbeat data worn by the subject and an acceleration sensor for detecting acceleration data. By doing so, for example, an optimal group can be formed based on the subject's position information, various attributes, and the like.

Moreover, it is preferable that the group forming means detect a plurality of subjects having common environmental conditions, and form the group with the detected plurality of subjects. By doing so, the environment in which the subject is placed can be detected in real time and a group can be formed dynamically.

Hereinafter, the collective environment evaluation method and the collective environment evaluation system disclosed in the present application will be described with reference to the drawings.

(Embodiment)
In the present embodiment, the group environment evaluation method and the group environment evaluation system disclosed in the present application use data obtained by a management system that manages the risk of developing heat stroke for an individual person to be evaluated. The content will be described in detail by exemplifying the case of evaluating the heat environment of a group of workers.

The heat environment evaluation as a group environment evaluation method disclosed in the present application is a measuring device that can measure at least the heart rate and the acceleration representing the movement of the body as biological information of each worker with workers at the construction site as the evaluated persons. is worn, and the thermal environment of workers as a group is evaluated based on the thermal load and work load applied to the workers who are the people to be measured.

[Overview of evaluation system]
The thermal environment evaluation system according to the present embodiment grasps as a group a plurality of subjects who can be judged to be under a common environment from the viewpoint of thermal conditions, work load, etc., and the subjects belonging to the group. It evaluates the heat environment of a group using the biological information of people. First, an overview of an evaluation system that acquires biometric information of a plurality of subjects and evaluates the risk of developing heat stroke for each subject, which is a premise of group evaluation, will be described.

FIG. 1 is an image diagram for explaining a schematic configuration of a hot environment evaluation system according to this embodiment.

FIG. 2 is a block diagram showing a configuration example of each part of the hot environment evaluation system according to this embodiment.

As shown in FIG. 1, a worker 10 working at a construction site uses a measuring device equipped with a three-dimensional acceleration sensor, which is an acceleration detection means for detecting the temperature in clothes, heartbeat data, and body movement. A person wears a certain biosensor 11 on his/her chest and has a smart phone 12 as a portable terminal that functions as an information transmitting unit that transmits various kinds of information obtained by the biosensor 11 to the outside. In the heatstroke risk management system, which is the premise of the hot environment evaluation system described in the present embodiment, the worker 10 is the person to be evaluated and corresponds to the subject of the group.

In the hot environment evaluation system described in this embodiment, the biosensor 11 that acquires various information about the worker 10 is attached to the chest of the undershirt worn by the worker 10 .

FIG. 3 is a diagram showing a configuration example of an undershirt worn by a worker in the hot environment evaluation system according to this embodiment. FIG. 3(a) shows the front side of the undershirt to which the biosensor is attached, and FIG. 3(b) shows the back side of the undershirt, that is, the side that faces and contacts the body surface of the worker.

As shown in FIG. 3, the biosensor 11 is arranged on the chest of the undershirt 18 worn by the worker 10 . More specifically, the biosensor 11 is connected to a data acquisition/transmission unit 11a arranged in the chest central portion of the front surface 18a of the undershirt 18, and connected to the data acquisition/transmission unit 11a. In other words, it is composed of the electrode portion 11b of the heartbeat sensor which is arranged to extend in the left-right direction on the portion on the side that contacts the skin.

In the hot environment evaluation system according to the present embodiment, the biosensor 11 detects the heartbeat, the temperature inside the clothes, and the movement of the worker 10. A heartbeat of the worker 10 can be detected more accurately by contacting the chest with a certain electrode. A temperature sensor (not shown) for detecting the temperature inside the clothes and an acceleration sensor chip (not shown) for detecting acceleration in three-dimensional directions are accommodated in the data acquisition/transmission unit 11a.

In addition, in the hot environment evaluation system described in this embodiment, an example of arrangement of the measuring device for acquiring the heart rate, temperature inside the clothes, and movement of the worker 10 is to attach the biosensor 11 to the undershirt 18 shown in FIG. The method is not limited. For example, a method in which the biosensor 11 is placed in a highly adhesive sheet-like attachment cover and this is directly attached to the chest, and a stretchable attachment belt capable of holding the biosensor 11 in close contact with the body is used. For example, a method of arranging it on the chest of a person can be adopted. However, according to the method of fixing the biosensor 11 to the undershirt 18 worn by the worker 10 as shown in FIG. You can get the information you need. In addition, even if the worker 10 perspires or twists during work, the biosensor 11 fixed to the undershirt 18 will not come off the body surface of the worker 10, and the worker 10 can wear it. The position can also remain substantially unchanged. Therefore, although part of the heartbeat of the worker 10 may not be obtained as heartbeat data, it is possible to avoid a situation in which heartbeat data cannot be obtained at all continuously.

In addition to the chest of the worker described above, the biosensor 11 for grasping the heart rate of the worker 10 may be arranged on the waist, back, upper arm, leg, or the like of the worker. can be adopted. In addition, it is not a system that manages the risk of developing heat stroke by using workers working at construction sites as evaluated persons, as described in the present embodiment, but for example, as a physical condition evaluation of athletes who are training. When evaluating the risk of onset, it is conceivable that the person to be evaluated wears sportswear, and in this case as well, it is most rational to place the biosensor on the chest of the clothing worn on the upper body.

The biosensor 11 and the smart phone 12 possessed by the worker 11 are always connected by short-range communication such as Bluetooth (registered trademark), and various types of information acquired by the biosensor 11 are sent to the smart phone 12 at any time. being sent.

The smartphone 12 transmits the information of the wireless LAN or the mobile phone by the evaluator information transmission unit 13, the data reception unit 15, and the data transmission unit 16 as information transmission means for transmitting the information of the worker 10 sent from the biosensor 11. It is always connected to the Internet 20 as a network environment using a carrier. Then, the smartphone 12 stores the temperature inside the clothes of the worker 10, the heartbeat data, and the measurement data of the acceleration sensor, which are the evaluated person information, in the cloud server 21, which is a server provided with the risk evaluation determination unit 22 installed on the Internet 20. to transmit.

The cloud server 21 includes a data receiving unit 23 and a data transmitting unit 26 inside, and can transmit and receive information via the Internet 20. receive measurement data from Then, each worker is classified into a group to which they belong, and the heat environment of the group is evaluated.

In addition, in the heat stroke risk management system, which is the premise of the hot environment evaluation system according to the present embodiment, the risk of heat stroke for each individual worker is managed, and when it is determined that the risk of heat stroke is particularly high , the information is transmitted to encourage the worker to take measures to reduce the risk of developing heat stroke, so the cloud server 21 evaluates and determines the risk of developing heat stroke, and determines the risk of developing heat stroke. If the risk is increasing, create warning information to warn the worker to that effect. The cloud server 21 also includes a data recording unit 24, which can record measurement data from each of the plurality of workers 10, generation history of warning information, and the like in chronological order.

Furthermore, the cloud server 21 has a weather information acquisition unit 25, acquires weather information from an information site that provides weather information via the Internet 20, and calculates the temperature in the area where the worker 10 is working. You can get weather conditions at the current time, such as , humidity, and amount of sunshine, as well as weather forecasts that anticipate changes in the next few hours.

The cloud server 21 is also connected via the Internet 20 to a personal computer 31 as a manager information terminal used by a site supervisor 30 who supervises the work of the worker 10 who is the person to be evaluated at the construction site. ing. For this reason, the site supervisor 30 at the work site where the worker 10 is working can use the data receiving unit 33 of the personal computer 31 to receive the measurement results obtained from the worker 10, which are transmitted from the cloud server 21 as needed, and the evaluation determination unit 22 It is possible to grasp whether or not warning information has been generated.

The evaluation determination unit 22 of the cloud server 21 evaluates the physical condition of the worker 10 based on the heartbeat data, acceleration data, and clothes temperature data obtained from the biosensor 11, which is a measuring device worn by the worker 10, Furthermore, a work load index is calculated, and a heatstroke risk index for the worker 10 is calculated by taking into consideration the temperature information inside the clothes and the environmental temperature information of the work area obtained via the Internet.

In addition, the heat environment evaluation of the group to be evaluated performed by the evaluation determination unit 22, the work burden estimation of the worker 10 performed as heat stroke risk management, the physical condition evaluation, and the heat stroke risk evaluation of the individual worker Specific details will be described later.

The cloud server 21 stores history data as past history information of the determination target worker 10 recorded in the data recording unit 24, weather information of the work area acquired by the weather information acquisition unit 25, and furthermore, determination target worker 10 Based on environmental information such as changes in various information acquired from workers other than the workers to be judged who work at the same site as the workers, the evaluation results of the heatstroke risk of 10 individual workers are corrected. Therefore, it is possible to manage the risk of developing heat stroke in a more realistic manner.

In addition, in the hot environment evaluation system exemplified in the present embodiment, the cloud server 21 is not the only one that includes the evaluation determination unit 22 . For example, various functions of the cloud server 21, including the group evaluation function and the risk determination function, may be implemented on the administrator information terminal or the management computer of the office. It does not matter where or on which device the is implemented.

The personal computer 31 of the on-site supervisor 30 manages whether or not various information obtained by the measuring device and warning information regarding the workers belonging to the work site supervised by the on-site supervisor 30 including the worker 10 have been generated. It has an information management unit 32 that Based on the information transmitted from the cloud server 21, the information management unit 32 always provides information that serves as a standard for evaluating the risk of developing heat stroke, whether information obtained from each worker 10 or warning information has been generated. I understand it as the latest information. In addition, the information management unit 32 outputs the evaluation determination result of the heat stroke onset risk of each worker and other environmental information obtained to the display image processing unit 35, and the display image processing unit 35 displays a display device such as a liquid crystal monitor. The screen content displayed on 36 is adjusted.

In this way, the site supervisor 30 grasps the information of the workers 10 working at the work site supervised by him or the risk of developing heatstroke in an integrated manner as a whole or as detailed information of each worker on an easy-to-view screen. can do. Furthermore, if the workers supervised by the site supervisor 30 constitute one group, the site supervisor 30 reports the group evaluation results of the group and other groups managed by the other site supervisors. When the workers belong to a plurality of groups, the group evaluation results of each group can be referred to, and the group evaluation results of other groups managed by other site supervisors can be referred to. It should be noted that the specific screen contents displayed on the display device 36 processed by the display image processing unit 35 need only be able to display the information required by the appropriately formed system in an easy-to-see manner. Detailed description is omitted.

Furthermore, the personal computer 31 of the site supervisor 30 receives various information obtained from the worker 10 after notification of the warning information and receipt confirmation of the warning information from the worker 10, thereby preventing the worker 10 from developing heat stroke. It is possible to check whether measures have been taken to prevent heat stroke, and if the worker 10 does not take measures to prevent the onset of heat stroke, the warning information is repeatedly sent to the target worker 10 It is possible to call the attention of the worker 10 by, for example, transmitting the

The on-site supervisor 30 can grasp the heat environment evaluation as a group for at least the workers he/she supervises, or the heat stroke risk evaluation result for each individual worker, which can be grasped by being displayed on the personal computer 31. Based on this, if it is possible to take measures to improve the work environment at the work site, such as air conditioning and ventilation, take appropriate measures to improve the hot environment at the work site that you supervise and prevent heat stroke. can prevent the onset of

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

The warning information generated by the evaluation determination unit 22 of the cloud server 21 or the personal computer 31 of the site supervisor 30 is transmitted from the data transmission 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 such as a mobile phone. is transmitted to the smart phone 12 equipped by the worker 10 via a network including the . The warning notification unit 14 of the smartphone 12 that has received the warning information uses various information transmission means such as sound, screen display, lighting or blinking of the lamp, and vibration to notify the worker 10 that he or she has developed heat stroke. to inform you that there is an increased risk of After confirming the warning information, the worker 10 reports that the warning information has been received through the touch panel or operation buttons of the smartphone 12, and takes measures to prevent heat stroke, such as stopping the work and taking a rest. .

The smart phone 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 heat stroke. You can confirm that you have taken action.

Furthermore, in the hot environment evaluation system described in this embodiment, the heat stroke risk data at the work site grasped by the site supervisor 30 is transmitted to the smartphone 12 of the worker 10, and the worker 10 It is possible to check the current status of the risk of developing heatstroke at the work site where people work. If it can be confirmed that the risk of developing heat stroke as a group including oneself is high, each worker can take measures to actively prevent the onset of heat stroke. In addition, by making it possible to grasp the heat stroke risk evaluation results for individual workers, for example, there is a worker in the group to which he belongs who has received warning information about the risk of heat stroke and interrupted his work. Knowing this, when the site supervisor 30 receives warning information addressed to him/herself, it can be expected that he or she will respond obediently.

Furthermore, the smartphone 12 owned by the worker 10 evaluates the health condition calculated from the change in the risk of developing heatstroke up to the present of the worker 10, and the own heart rate and acceleration data acquired by the biosensor 11. The results and related information such as calorie consumption can be displayed on the screen for the operator 10 to refer to. In addition, it is also possible to display the transition of the thermal environment evaluation results up to the present for the group including the worker on the display screen of the smartphone 12 owned by the worker 10 . By knowing the heat environment evaluation result of the group to which the worker 10 belongs, the worker 10 can more accurately grasp the environment in which he or she is placed, and can take measures to reduce the risk of developing heat stroke. can. Note that the display screen of the smartphone owned by the worker 10 only needs to be able to display necessary items in an easy-to-see manner according to each purpose, so a detailed description in this specification is omitted.

The cloud server 21 is also connected to a management computer 41 in the company or office 40 to which the worker 10 belongs via the Internet 20, and receives the measurement result information of the worker 10 transmitted to the personal computer 31 of the site supervisor 30, Various types of information used by the cloud server 21 to determine the risk of developing heatstroke are transmitted to the management computer 41 of the office 40 in real time. Since the management computer 41 of the office 40 has its own data receiving section 42 and data transmitting section 43, it is also connected to the personal computer 31 of the site supervisor 30 via the Internet. It is possible to confirm information such as whether the warning information has been correctly transmitted to the worker 10 and whether the worker 10 has taken preventive measures against heatstroke, and can issue a predetermined instruction as necessary. In addition, by grasping the heat evaluation results for one group at each site, or for multiple groups subdivided by differences in the work environment at one work site, it is possible to understand the work as a broader environment. Since the on-site situation can be grasped, countermeasures for each workplace or countermeasures for workers belonging to the same work environment but different workplaces can be considered, and the worker 10 can effectively avoid the risk of developing heat stroke. can be backed up.

Although not shown in FIG. 1, the cloud server 21, the personal computer 31 of the site supervisor 30, and the management computer 40 of the office 40 are connected via the Internet 20. It is possible to access the cloud server 21 from the cloud server 21, control the data processing content in the cloud server 21, update the determination program in the evaluation determination unit 22, and receive information necessary for heatstroke prevention management from the cloud server 21. It can be taken out as appropriate.

In the above explanation, smartphones are used as examples of mobile terminals equipped by workers, but the mobile terminals of workers are not limited to smartphones. A dedicated small terminal device capable of transmitting and receiving information can be used. In addition to the personal computers shown in the examples, especially the desktop personal computer shown in FIG. 1, the administrator information terminals operated by the site supervisors include notebook personal computers, tablet personal computers, small server devices, etc., which can be used to send and receive information through networks. Various information devices capable of displaying data, recording data, etc. can be employed.

Furthermore, in the above description, a configuration has been described in which warning information is transmitted from the site supervisor's manager information terminal to the worker's mobile terminal. The system can also be configured to send warning information directly from the device to the worker's mobile terminal.

Furthermore, the information transmission means connecting workers, site supervisors, and management departments in the office is not limited to the above examples, and it goes without saying that various data information communication means for transmitting and receiving data can be used.

[Method for evaluating the risk of developing heat stroke]
Next, with regard to the hot environment evaluation method performed by the hot environment evaluation system according to the present embodiment, first, the specific contents of the heat stroke onset risk evaluation for an individual worker will be described.

The method for assessing the risk of developing heat stroke according to this embodiment uses heartbeat data of the person to be evaluated detected by heartbeat detection means provided in a measuring device worn by the person to be evaluated, and acceleration data acquired by a three-dimensional acceleration sensor. A work burden index indicating the intensity of the work performed by the person to be evaluated is calculated based on the above. Also, the heat load index of the person to be evaluated is calculated based on the temperature inside the clothing of the person to be evaluated obtained from the measuring device and the environmental temperature of the site where the person to be evaluated is working. Then, based on the calculated work load index and heat load index, a heat stroke risk index indicating the risk of developing heat stroke is calculated.

In the following description of the method for evaluating the risk of developing heat stroke, each component of the heat stroke risk management system according to the present embodiment described with reference to FIG. 2 will be exemplified as appropriate.

FIG. 4 is a flow chart showing the flow of heat stroke risk evaluation in the evaluation determination unit in the heat stroke risk management system described in this embodiment.

In the heat stroke onset risk evaluation system according to the present embodiment, the evaluation determination unit 22, which is the control means provided in the cloud server 21 on the Internet, is the biosensor, which is the measurement device worn by the worker 10 who is the person to be evaluated. Based on the data obtained from 11 and the data obtained from each component in the cloud server 21, the work burden index and the heat load index of the worker 10 are calculated to calculate the heat stroke risk index. .

As shown in FIG. 4, when the evaluation by the evaluation determination unit 22 starts (START), the evaluation determination unit 22 starts calculating the work burden index of the person being evaluated.

In addition, the start (START) of the evaluation by the evaluation determination unit 22 is performed by turning the power switch of the biosensor 11, which is a measuring device, to "ON" by the worker 10 himself or the site supervisor 30 who is the manager. The biosensor 11 itself detects that the worker wears the undershirt 18 equipped with the biosensor 11, which is set so that the operation of the biosensor 11 automatically starts when the work start time comes. can be set in various ways, such as starting

In order to calculate the work load index, the evaluation determination unit 22 first determines whether history data, which is heartbeat data and acceleration data, is recorded in the data recording unit 24 as past data of the worker 10 to be evaluated. is confirmed (step S101).

When the worker 10 has been evaluated in the heatstroke risk management system described in the present embodiment in the past, and the history data of the worker 10 is recorded in the data recording unit 24 ("Yes" in step S101 ), a linear section in which the heart rate changes linearly with acceleration is obtained from the set of history data, and a regression line is obtained for the history data included in the linear section. A regression line obtained from this historical data represents the characteristics (individuality) of the heartbeat response of the worker. The slope of this regression line is defined as the heart rate response coefficient αr, and the intercept is defined as the intercept heart rate βr (step S102).

After that, the evaluation determination unit 22 detects heartbeat data of the worker 10 measured by the biosensor 11 (step S103).

On the other hand, if the history data of the worker 10 does not exist, or if the data exists but a certain period of time (one month as an example) has passed since the previous data was recorded, The evaluation determination unit 22 determines that the correct standardized heart rate of the worker 10 cannot be calculated, and calculates the work burden index of the worker 10 only from the acceleration data, not based on the heart rate data. The evaluation determination unit 22 calculates the acceleration deviation, which is a numerical value indicating the motion of the worker 10 (step S110), and calculates the work burden index of the worker 10 based only on the acceleration deviation (step S111). In this case, the acceleration deviation may be converted into a work load index using a predetermined formula, such as by multiplying the acceleration deviation by an appropriate coefficient.

When the history data of the worker 10 is recorded in the data recording unit 24 ("Yes" in step S101), the evaluation determination unit 22 ensures the reliability of the heartbeat data when detecting the heartbeat data. In the heat stroke onset risk management system of this embodiment, the biosensor is attached to the back surface 18b of the undershirt 18 worn by the worker 10 so that the heart rate data of the worker 10 who is the person to be evaluated can be obtained more satisfactorily as described above. 11 electrode portions 11b are arranged. However, the heartbeat may not be detected correctly due to the movement of the worker's body, perspiration on the body surface, and the like. For this reason, in the heatstroke risk management system of the present embodiment, if the heartbeat data of the worker 10 who is the person to be evaluated cannot be measured correctly, the work load index is calculated based on the incorrect data, and the onset of heatstroke is calculated. We check whether the heart rate data is acquired correctly so as not to make an error in the risk assessment.

First, the evaluation determination unit 22 calculates the heartbeat waveform detection rate in order to evaluate the reliability of the heartbeat data (step S104).

Raw data sampled from the biosensor may contain a certain percentage of noise (abnormal heartbeat data) due to poor contact between the subject's skin and electrodes. Therefore, for the data for each beat (heartbeat interval), for example, the heartbeat interval is 0.33 seconds or more and 1.33 seconds or less, and the difference from the previous data (differential heartbeat interval) is Data of 0.15 seconds or less are determined to be normal and labeled.

The threshold for judging normality/abnormality can be arbitrarily set, but an appropriate numerical value may be set so as to eliminate improbable heartbeat interval data based on a physiological point of view. Then, the measured data is divided into k sub-intervals with a predetermined time width, and the cardiac waveform detection rate Q is calculated for each sub-interval as the percentage of the data labeled as normal in the total data for each interval. .

Next, the evaluation determination unit 22 determines the heartbeat waveform detection rate for each partial interval (step S105).

If the heartbeat waveform detection rate is equal to or higher than a reference value (for example, 50%), the section is determined to be reliable ("Yes" in step S105), and the work load index is calculated using the heartbeat data (step S106).

On the other hand, if the heartbeat waveform detection rate is less than the reference value (50%), it is determined that there is no reliability ("No" in step S105), and the work load index is calculated for the section using the acceleration data. Proceed to step S110.

Note that the reference values in the above description are only examples, and may be appropriately adjusted depending on the performance of the biosensor, the occupation of the subject, and the like. For example, a low threshold may be set for occupations that require a lot of movement, and a high threshold may be set for occupations that require less movement.

When the heartbeat waveform detection rate is 50% or more ("Yes" in step S105), the evaluation determination unit 22 calculates the central heartbeat rate from the obtained heartbeat data (step S106). Here, for the partial intervals set in step S104, a representative value (median value) for each partial interval is used as central heart rate data. The representative value may be the interval mean value, but is preferably the interval median value. This is because even if the data obtained from the measuring device contains a small number of irregular values, the influence of such irregular values can be eliminated.

Further, the evaluation determination unit 22 simultaneously calculates an acceleration deviation, which is a numerical value indicating the operation status of the worker 10, from the acceleration data obtained from the biosensor 11 (step S107).

Next, the central heart rate is corrected based on the history data and the standard heart rate response model prepared in advance to obtain the standardized heart rate (step S108).

Specifically, using the heart rate response coefficient and the intercept heart rate, and the standard heart rate response coefficient and the standard intercept heart rate, which are the parameters of the standard heart rate response model, the median heart rate data is standardized by the following formula (equation 1). Convert to heart rate.

HR _S [k]=(αs/αr)(HR[k]−βr)+βs (Formula 1)
here,
・Central heart rate data: HR [k]
・Standardized heart rate: HR _S [k]
・ Heart rate response coefficient: αr
・Intercept heart rate: βr
・Standard heartbeat response coefficient: αs
・Standard intercept heart rate: βs
is. Here, k represents the number of the partial section.

A standard heartbeat response model is a heartbeat response model created based on large-scale data obtained from a large number of people. It is a model that expresses the standard human heartbeat response to acceleration (body movement), and can be expressed by various parameters and predetermined formulas.

An example of measurement results for determining the standard heart rate response model is shown in FIG.

FIG. 5(a) plots all of the large-scale data (approximately 3 million points), and the shading represents the density of the data. Line 51 shown in FIG. 5(a) is the 5% data line, line 52 is the 25% data line, line 53 is the 50% data line, line 54 is the 75% data line, line 55 indicates the 95% data line.

On the other hand, the median value of each interval is indicated by the x mark in FIG. 5(b), and the approximation curve F _HR (reference numeral 76) fitted to each median value represents the standard heart rate response model. .

The approximation curve F _HR can be obtained by various curve fitting techniques, and can be expressed as a function F _HR (A _RMS ) that gives an estimated standardized heart rate F _HR given the acceleration deviation A _RMS . In addition, the slope of the part where _FHR changes linearly (the interval between acceleration of around 0.05 and around 0.45) corresponds to the standard heart rate response coefficient, and the intercept of the approximation curve corresponds to the standard intercept heart rate. do.

Note that the large-scale data may be data of a plurality of workers at the site for the past several days, or may be accumulated data sampled in advance at another site. Preferably, a standard heartbeat response model is created based on large-scale data obtained by measuring a large number of workers engaged in the same work as the worker. This is a heartbeat response model optimized for the work in question, and is considered to represent a typical heartbeat response of a worker engaged in the work. There are no particular restrictions on the number of people on whom the large-scale data is based, but the larger the number of samples, the more accurately the heart rate response can be approximated. It is preferably 5 or more, more preferably 50 or more. There are no particular rules regarding the accumulation period, but it is preferable to acquire data for two days or more, more preferably five days or more, at the same site.

Based on the standardized heart rate and the acceleration deviation thus obtained, the evaluation determination unit 22 calculates the work burden index of the worker 10 (step S109).

At this time, the evaluation determination unit 22 determines whether to use the standardized heart rate or the estimated standardized heart rate using a correction map created based on the standardized heart rate response model. A specific method for determining the central heart rate and the acceleration deviation from the heart rate data obtained from the biosensor 11, which is a measuring device, and the numerical value of the three-dimensional acceleration sensor, and selection criteria for the heart rate data using the correction map, etc. will be described later. I will elaborate.

On the other hand, if the heartbeat waveform detection rate Q is not equal to or higher than the reference value (50% in the above example) ("No" in step S105), the evaluation determination unit 22 determines that the credibility of the obtained heartbeat data is low. Therefore, instead of calculating the central heart rate, the acceleration deviation, which is a numerical value indicating the operation status of the worker 10, is calculated from the acceleration data obtained from the biosensor 11 (step S110). In this case, the evaluation determination unit 22 calculates the work burden index of the worker 10 based only on the acceleration deviation (step S111).

The work load index obtained in step S111 is considered to be less accurate than the work load numerical value obtained in step S109 because the heartbeat data is not reflected. Therefore, it is preferable that the work burden index is obtained continuously rather than not calculating the work burden index during that period on the grounds that the heartbeat data is not obtained.

Furthermore, 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. (step S112). The environmental temperature data of the work site is the temperature data around the work site acquired by the weather information acquisition unit 25 of the cloud server 21, or the temperature sensor installed in the work site when the worker is working indoors. It can be obtained based on the obtained temperature information.

A specific procedure for calculating the heat load index based on the temperature data in clothes of the worker 10 and the environmental temperature data will be described in detail later.

Then, the evaluation determination unit 22 calculates the heat stroke risk of the worker 10 as a heat stroke risk index based on the obtained work load index and heat load index (step S113).

The heat stroke risk index in the heat stroke risk evaluation system shown in this embodiment can be determined as a linear sum of the work load index and the heat load index. Therefore, the greater the value of the heat stroke risk index, the higher the risk of the worker developing heat stroke. It can be ranked whether it is in a high (=dangerous) state, a slightly high (=caution) state, or a low (=safe) state. For this reason, depending on the rank of the heatstroke risk index calculated by the evaluation determination unit 22, the worker 10 himself or the site supervisor 30 who is the supervisor stops the work and takes a rest. It is possible to take countermeasures such as reducing the heat load by reducing the temperature inside the clothes or by lowering the temperature inside the clothes, thereby effectively avoiding the onset of heat stroke.

[Method for evaluating heatstroke risk]
Here, an algorithm for calculating a heat stroke risk index, which is a heat stroke risk evaluation index for each worker, performed in the heat stroke risk evaluation system according to the present embodiment will be described.

(Estimate of work load)
<a. Pretreatment>
First, heartbeat data and acceleration data are preprocessed to calculate a work load index.

As described with reference to the flowchart of FIG. 4, the preprocessing of the heartbeat data is to calculate the central heartbeat rate from the heartbeat data detected by the biosensor 11 worn by the worker 10 (step S106 in FIG. 4). is done in

More specifically, when the heart rate waveform detection rate of the partial section is 50% or more, the heart rate data acquisition interval included in the partial section is converted into the heart rate per partial section (for example, per past minute). to obtain the median heart rate HR.

On the other hand, for the acceleration data obtained by the acceleration sensor, the average value ΔA for the past one minute is obtained by the following procedure.

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

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

2) Removal of exponential moving average From the acceleration data of each axis, remove the above-mentioned exponential moving average and obtain detrended time-series acceleration. ”.

3) Calculation of the sum of squares Calculate the sum of squares at each time using the following formula (formula 2) for the detrended time-series acceleration

4) Average Acceleration per Minute Calculate the average value "ΔA ² _ave " of the sum of squares "ΔA ² (t)" obtained above per minute. Here, the average value is obtained by dividing by the number of data points. Also, the square root "ΔA _ave " of the mean square of acceleration "ΔA ² _ave " is calculated. where ΔA _ave is the acceleration deviation A _RMS .

<b. Removal of Outliers>
With respect to 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.

As for acceleration data, non-numerical data and data with ΔA of 0.05 or less or 0.55 or more are excluded as abnormal values.

<c. Calculation of Intercept Heart Rate and Heart Rate Response Coefficient>
A linear response interval in which the central heart rate changes linearly with respect to the acceleration deviation is set for a set of history data, and a regression line is obtained for the data included in the linear response interval. The slope of this regression line is the heart rate response coefficient αr, and the intercept is the intercept heart rate βr.

The method of fitting the regression line is not particularly limited. For example, a section in which the acceleration deviation is 0.05 to 0.4 is set as a linear response section, and is divided into m partial sections (m is 3 to 7, for example). Next, the median heart rate and the median acceleration deviation are determined for each partial interval. Then, a regression line is fitted to the median coordinates of the m points obtained.

<d. Calculation of Work Burden Index>
In FIG. 4, as shown in step S108, if there is history data of the worker 10 who is the subject, the standardized heart rate HR _S is calculated based on this history data and the standard heart rate response model. . By calculating the standardized heart rate HR _S , it is possible to correct individual differences in calculating the work load index from the heart rate data due to individual characteristics of the person being measured.

On the other hand, the estimated standardized heart rate estimates the standard heart rate from the subject's acceleration deviation A _RMS using the approximation formula F _HR (A _RMS ) of the standard heart rate response model. In calculating the actual workload index, the point is which of the standardized heart rate and the estimated standardized heart rate is more reliable. In this example, a correction map created based on a standard heart rate response model is used to determine which heart rate to select and obtain the corrected heart rate HR _s .

FIG. 7 is a first example of a correction map.

As shown in FIG. 7, the correction map describes an approximation curve F _HR 71 in which the y-axis intercept is the standard intercept heart rate βs and the slope of the straight line portion is the standard heart rate response coefficient αs. Here, the approximated curve F _HR 71 is used as the judgment line. It has been found that the determination line 71 ceases to be a straight line as shown in FIG. 7 from the portion where the acceleration deviation exceeds 0.45, and the degree of increase in the central heart rate with respect to the acceleration deviation decreases.

In the correction map shown in FIG. 7, a boundary line 72 is provided in a portion where the acceleration deviation indicating the motion of the worker who is the person to be measured is 0.2. In the area where the acceleration deviation is less than 0.2, the influence of emotion appears more than the change in the heart rate due to movement, and in the area where the acceleration deviation is greater than 0.2, the fluctuation of the heart rate due to body movement is large. This is because it is considered that

In the correction map shown in FIG. 7, the relationship between the heart rate and the acceleration deviation is corrected so as to fall within the hatched areas 73 and 77 in the map. For example, in the range of acceleration deviation up to 0.2, if the standardized heart rate is large and positioned above the judgment line 71, the numerical value of the judgment line 71, that is, the estimated standardized heart rate is used as the corrected heart rate HR _s , and if the standardized heart rate is smaller than the standard intercept heart rate βs, the value of the standard intercept heart rate βs is adopted as the corrected heart rate HR _s . If the standardized heart rate is equal to or less than the decision line 71 and equal to or greater than the standard intercept heart rate βs, the standardized heart rate is directly adopted as the corrected heart rate HR _s . By doing so, in a region where the acceleration deviation is less than 0.2, if a standardized heart rate greater than the estimated standardized heart rate is detected, it can be eliminated as an influence of emotion.

On the other hand, in the region where the acceleration deviation is greater than 0.2, the region where the heart rate value is judged to be too large is defined with the same slope as the above-mentioned standard heart rate response coefficient αs, that is, in parallel with the straight line portion of the approximated curve F _HR . A parallel line 76 is drawn, and it is determined that a correct heart rate has been detected within a region 77 sandwiched between the parallel line 76 and the determination line 71 . If this region 77 is applicable, the workload index is calculated using the standardized heart rate as it is as the corrected heart rate HR _s . If the standardized heart rate is greater than the upper limit parallel line 76, the value on the parallel line 76 is adopted as the corrected heart rate HR _s to eliminate the effect of error, as indicated by arrow 78 in the figure. In addition, the numerical value appearing in the area below the judgment line 71 is obtained by adopting the numerical value on the judgment line 71, that is, the estimated standardized heart rate as the corrected heart rate HR _s as indicated by an arrow 79 in the drawing. It is possible to avoid using a heart rate value that is too low for calculating the work load index even though the measurer is moving more than a certain amount.

The correction map shown in FIG. 8 is a correction map used when it is determined that the detected heartbeat data is more reliable.

A case where the reliability of the heartbeat data is high is a case where the detection rate of the heartbeat data acquired from the biosensor 11 is higher than the criterion (50% as an example), for example, when the state continues to exceed 80%. can be assumed.

The correction map shown in FIG. 8 is basically the same as the correction map shown in FIG. is different. As shown in FIG. 8, when the reliability of the heartbeat data is high, a boundary line 88 that defines the lower limit parallel to the judgment line 81 from the position of the standard intercept heart rate βs at the acceleration deviation of 0.2 is below the judgment line 81. , the standardized heart rate in the area 89 between the boundary line 88 and the judgment line 81 is used as the corrected heart rate HR _s , and when the standardized heart rate is smaller than the boundary line 88, the arrow 91 A value on the boundary line 88 as shown is taken as the corrected heart rate HR _s .

By doing so, it is possible to employ the standardized heart rate over a wide range and calculate a more accurate work load index.

<e. Evaluation of Work Burden>
Based on the corrected heart rate _HRc obtained using the correction map, the work load index W is calculated as follows.

First, the corrected heart rate HR _c is converted to the metabolic equivalent METs using the following formula (Formula 3).

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

Next, the metabolic equivalent METs is converted into a work burden index W using the following formula (Formula 4).

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

For example, when a _W =0, 2 and b _W =−0.2 are set, the work load is evaluated as follows. A large amount of work, i.e., when the numerical value of W is 1 or more, can be regarded as work with an extremely high metabolic rate, that is, work that imposes a very heavy burden on the worker.

(Evaluation of heat load)
A heat load index H is obtained by the following formula (Formula 5) using the temperature Ti obtained by the measuring device 11 and the outside air temperature To obtained as the environmental temperature.

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.

(Evaluation of heatstroke risk)
Using the work load index W and the heat load index H obtained by the above calculation, a heat stroke risk evaluation index R for the worker 10 to be evaluated is obtained as shown in the following formula (Formula 6).

Here, a is a numerical value defined corresponding to the heat acclimation of the worker to be evaluated. 3.

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

In addition, since it is not possible to verify the actual occurrence of heat stroke, when determining the criteria for the risk of developing heat stroke, it is necessary to make a more rigorous judgment of the risk of developing heat stroke, that is, to make decisions on the safer side. Should.

(Continuous evaluation of heatstroke risk)
Based on the measurement results obtained from the biosensor 11, which is a measuring device worn by the worker 10, when continuously evaluating the risk of developing heatstroke for the worker, the heat load index H and the work load index W Each exponential moving average value is obtained from the following formulas (Formula 7) and (Formula 8) with a sampling interval of 1 minute.

Here, w ₁ =2/31 and w ₂ =2/11.

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

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

(Display on 2D map)
As can be seen from the above formula (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 the sum of the heat load index H and the work burden index W for the worker 10. Expressed as a linear sum.

Using this fact, the heat stroke risk index can be displayed as a heat stroke risk index on a two-dimensional map with the heat load index and the work load index as axes. For example, by displaying on a two-dimensional map a symbol corresponding to the current heatstroke risk index for each of the workers 10 managed by the site supervisor 30 who is the manager, the site supervisor 30 can grasp the overall risk index of the workers to be managed at a glance. Note that a specific description of the display image that displays the degree of heatstroke risk of the worker 10 will be omitted.

[Evaluation of heat environment as a group]
Hereinafter, evaluation of a hot environment as a group in the hot environment evaluation system disclosed in the present application will be described.

What is explained below is based on the heart rate of the worker who is the subject (evaluated person) acquired in the heatstroke risk assessment system for workers working at construction sites whose contents were explained above. , is an example of evaluating the environmental heat load of the group to which the worker belongs.

In the heat environment evaluation disclosed in the present application, the thermal conditions at the work site and the work load added by the workers are evaluated, for example, the environment in which the group to be evaluated is placed It is possible to determine whether or not the worker is in a high-risk state, and the evaluation results can be used to reduce the risk of developing heat stroke in workers who work in environments where the risk of developing heat stroke is high. .

(About core temperature)
It is known to use core temperature to assess thermal load on humans.

The core temperature is the temperature inside the body, which is kept almost constant (about 37° C. at rest) in order to maintain the functions of important organs such as the brain and heart. In the region where the body's thermoregulatory function works effectively, the heat balance between heat radiation and heat production is maintained, so the core temperature remains almost constant even if environmental factors such as the outside temperature change. Here, heat dissipation includes transpiration due to perspiration, respiration, heat dissipation from the skin, and the like, and the degree of heat dissipation varies depending on the surface area of the body, the state of clothing, and environmental conditions such as temperature, humidity, and wind. On the other hand, thermogenesis includes muscle movement during exercise and exertion, muscle vibration (shivering), basal metabolism and thermoregulatory non-shivering thermogenesis, and heat influx from the environment such as solar radiation and high temperature environments.

FIG. 9 shows an image of a distribution example of the core temperature and the temperature of the peripheral part of the body, including the body surface, as a result of such a balance between heat dissipation and heat production.

In Fig. 9, Fig. 9(a) shows the state at rest at a temperature of 20°C, Fig. 9(b) shows the state at rest in a high temperature environment of 35°C, and Fig. 9(c) shows a state at a temperature of 35°C. It shows the distribution of body temperature during work in a high-temperature environment.

As shown in Fig. 9(a), when the air temperature is 25°C and the patient is at rest, the core temperature is maintained at 37°C. Recognize. In this way, when the outside air temperature is as low as 25°C, the core temperature of the core of the body is 37°C, but the temperature of the limbs is low, so even if the workload is applied, It does not lead to an increase in the core temperature, and it is possible to work while maintaining the core temperature at 37°C.

On the other hand, as shown in FIG. 9B, when the air temperature is as high as 35° C., the temperature of the peripheral part of the body is close to the core temperature of 37° C. even at rest (36° C. as an example). In such a state, the body cannot absorb the heat produced by the applied work load, and the body's heat release function such as sweating and transpiration is poor.

Therefore, as shown in FIG. 9(c), when the temperature is as high as 35.degree.

As described above, the core temperature is the temperature of the central part of the body, where important organs such as the brain and heart are located. Based on the results of previous research, it is thought that the upper limit of the target temperature for easy work is 38°C, and the limit value of basic heat load is 38.3°C. is desirable and above 39.2°C is considered an emergency requiring the cessation of further heat exposure. In this way, by grasping the core temperature, it is possible to determine whether it is permissible to continue working in that state, whether efforts should be made to lower the core temperature by taking breaks, etc., and whether it is necessary to immediately move to a cooler place, etc. It is possible to evaluate the heat environment, which is important in avoiding the onset of disease.

(Evaluation of core temperature based on heart rate)
On the other hand, it is known that there is a strong correlation between human core temperature and heart rate. Therefore, as in the above-described heatstroke risk evaluation system, the core temperature of the worker can be estimated by grasping the worker's heart rate at any time using a wearable biosensor.

At this time, although there is a correlation between the change in heart rate and the change in core temperature, there is individual variation in the specific values of the heart rate at which the core temperature is 37°C. big. As a result of examination based on these findings, the inventors divided (grouped) the workers, who are the target persons in the heatstroke risk assessment system, into groups according to their work environment and work load. By obtaining the average value (simple average) of the heart rate of workers belonging to a group, environmental evaluation based on the correlation between heart rate and core temperature is performed by absorbing individual differences in specific values of heart rate. I found that I can do it, and invented a hot environment evaluation method for a group.

(Formation of a group (= group))
In the hot environment evaluation method shown in this embodiment, first, groups (=groups) to be evaluated are formed by the group creating means. As described above, the heart rate of the worker, who is the subject, changes depending on the thermal load given by the surrounding environment such as the weather environment in which the worker is working and the workload that varies depending on the work content. At a construction site, a group of workers performing substantially the same work at the same work site is expected to be subjected to substantially the same thermal load and work load. As described above, in the hot environment evaluation method according to the present embodiment, a group to be evaluated is formed on the basis of the work place and the work content at the construction site.

Formation of the group is decided based on the size of the heat environment to be evaluated. Based on work areas such as subdivided sites, floors, etc., and based on obvious workloads such as whether you are engaged in work operating heavy machinery or carrying construction materials. Such settings can be formed as appropriate on the assumption that each group includes a plurality of target workers. In the hot environment evaluation system according to this embodiment, the function of the group forming means for forming groups based on these attributes of the subject is implemented, and the group is automatically formed based on the attribute information associated with the subject. can be formed.

Although there are no particular restrictions on the number of workers to be included in a group, a group of 5 to 6 or more workers is recommended for the purpose of reducing variations among individual workers through group evaluation. Desirably, groups of 10 or more are more preferred. In general, it is known that when the heart rate rises by about 20 (bpm), the core temperature rises by 1°C. In addition, since the individual difference in heart rate under almost the same conditions is about ±10 (bpm), the measurement accuracy depending on the number of measurement data (n number) is “±10/n ^1/2 ”, and the group is composed If the number of workers n is 10, the core temperature accuracy is about ±0.15°C, and if n is 100, the core temperature measurement accuracy is about ±0.05°C.

The group to be evaluated in the group evaluation method according to the present embodiment is not limited to workers whose heartbeats are being measured in real time. It is possible to acquire the heart rate data measured while the workers are working and treat them as the data of one worker who constitutes the group. Specifically, it is possible to evaluate the heat environment of a group of n=10 people using measurement data for two days under substantially the same temperature for groups of five people each.

In addition, the means for group formation is to subdivide workers placed in the same hot environment and work environment into groups by further subdividing them based on indicators such as age and the length of work experience, for example, so that workers with the same external environment It is possible to evaluate the heat environment under specific conditions, such as verifying the difference in heat load due to the individual conditions of the person being measured.

(Changes in heart rate values due to differences in thermal conditions)
Next, an example of data for hot environment evaluation acquired by the collective evaluation method according to the present embodiment will be described.

In each figure below, the group heart rate is the average value of the heart rate (bpm) per minute of the worker who is the subject, and is obtained from the heart rate data obtained in the above-mentioned heatstroke risk evaluation system. , is the heart rate value itself with noise removed. The average value is a simple arithmetic average of the heart rate values of a plurality of workers, averaging the heart rate values correctly obtained for 10 minutes to eliminate errors.

FIG. 10 is a diagram showing changes in average heart rate over time in a group of workers working at the same construction site.

The data in FIG. 10 show changes in average heart rate in a group of 10 workers from 13:00 to 15:00, which corresponds to 2 hours after the lunch break. In FIG. 10, the dashed line 101 indicates the data of the day when the average maximum temperature was 25° C., and the solid line 102 in FIG. This is the data on a very hot day.

The workers performing the work in the two data were almost the same, and the contents of the work were also the same. In this way, even though the load on the target worker was almost the same, in the data 102 of the extremely hot day in which the outside temperature exceeded 35°C, the average heart rate immediately increased from the start of the work. Especially after 14:00, it can be seen that the average heart rate is 15 bpm or more higher than the day when the temperature was average. As mentioned above, if the heart rate rises by about 20 bpm, the core temperature rises by 1°C. I understand that.

FIG. 11 is a diagram showing changes in the average heart rate of a group of workers who also work at a construction site.

FIG. 11 shows changes in the average heart rate for 2 hours from 14:00 to 16:00. change is shown.

In FIG. 11, the dashed line 111 indicates changes in the average heart rate of the group (12 persons) who used the electric fan during the rest period, and the solid line 112 in FIG. It shows the change in average heart rate of the group (13 people) who did not use the electric fan. The investigation was conducted in the same factory on the same day, and the ambient temperature exceeded 35°C.

As can be seen from FIG. 11, in the group using the electric fan, the average heart rate was 80 bpm at the end of the rest period, returning to the resting heart rate level before work. On the other hand, in the group that did not use the fan during the rest period, the average heart rate decreased immediately after the break, but the average heart rate 112 stopped decreasing at around 96 (bpm), and the 20-minute break It didn't drop below that even at the end of time. Then, the average heart rate 112 increased with the start of work after the rest period, and after the rest period, the average heart rate continued to be about 15 bpm higher than the group that used the electric fan during the rest period. From this, it was found that the core temperature can be lowered by about 0.6°C by using the electric fan during the break, even if the break time is the same.

As described above, according to the heat environment evaluation system according to the present embodiment, it is possible to grasp the heat load in a group to be evaluated according to differences in environmental conditions such as temperature and how to take a break. In this way, the magnitude of the heat load actually applied to the workers can be evaluated by grasping the core temperature through the average heart rate, so that the heat load as the environment in which the group is placed can be realistically evaluated. , can be evaluated accurately. In addition, by constantly grasping the heart rate of the target worker, it is possible to quickly evaluate the environment in real time, such as evaluating the hot environment immediately after taking a break.

Thus, by using the hot environment evaluation system according to the present embodiment, it is possible to perform accurate and quick hot environment evaluation, and to take more effective measures to prevent heatstroke. . In addition, it is possible to quantitatively visualize the effects of environmental improvements, such as installing fans in rest areas.

FIG. 12 is a diagram showing daily changes in the average heart rate of a group of subjects, obtained by the hot environment evaluation system according to the present embodiment.

FIG. 12 shows daily changes in the average heart rate of a group of 13 workers. In FIG. 12, the left diagram shows the average heart rate from 8:00 to 12:00 in the morning, the right diagram shows the average heart rate from 13:00 to 17:00 in the afternoon, and the average heart rate from 12:00 during the lunch break. Heartbeat data was not acquired until 1:00, so it is displayed as a gap. Also, in FIG. 12, the dashed line 121 indicates the day when the maximum temperature is 25° C., and the solid line 122 in FIG. is the data on the day when it was evaluated as necessary.

In FIG. 12, the reason why the average heart rate is high at around 8:30 is that the subjects were workers whose work intensity was high at the start of work. At this point, the increase in heart rate seen in mean heart rates 121 and 122 is primarily caused by work load.

However, there is a big difference in the heart rate after 8:30, and the average heart rate 121 on days with a maximum temperature of 25°C drops to about 95 bpm, whereas on days with a WBGT index of 31°C or higher, , the average heart rate 122 did not decrease, increased to about 110 bpm, and maintained that value (white arrow a in FIG. 12). In this way, if the evaluation value of the risk of developing heat stroke represented by the WBGT index such as outside temperature and humidity is high, it is difficult for the average heart rate of the worker to decrease, and it is judged that the risk of developing heat stroke is considerably high. , the average heart rate is around 110 bpm. At this time, it can be estimated that the worker's core temperature exceeds 38°C.

On any day, the worker takes a break for 15 minutes from 10:00 (the hatched portion on the left side of FIG. 12). At this time, both the average heart rate 121 on days when the maximum temperature is 25° C. and the average heart rate 122 on days when the WBGT index is 31° C. or higher are reduced to 80 bpm, which is evaluated as the resting heart rate. This was because the temperature had not yet risen completely in the morning, and the total working hours were short and the workers' physical strength was low. It is thought that this is because the temperature has decreased to 37°C of the state.

However, when work resumed after the rest period, the average heart rate 122 on days with a WBGT index of 31°C or higher increased sharply, and compared to the average heart rate on days with a maximum temperature of 25°C, It is higher by about 15 bpm (the part indicated by the white arrow b in FIG. 12).

As for the average heart rate during work in the afternoon on the right side of FIG. (the portion indicated by the white arrow c in FIG. 12). However, since the temperature is high in the afternoon, the average heart rate is about 105 bpm even on days when the maximum temperature is 25 ° C, and the heat load of the group of workers significantly increases the risk of developing heat stroke. It is judged to be in a state where In this way, even if the maximum temperature is 25°C, workers who work in construction sites and other workplaces that are subject to a strong physical load have a certain level of risk of developing heatstroke depending on the working hours. I can understand that.

In addition, due to the fact that the temperature is high and the accumulation of physical fatigue of workers is increasing, during the afternoon break (the hatched part on the right side of the figure), if the maximum temperature is 25 ° C On days when the WBGT index is 31°C or higher, the average heart rate is about 90 bpm at the end of the 15-minute rest period, which is 10 bpm higher than the resting heart rate. It stays in a high state (part of white arrow d in FIG. 12). In this way, when the average heart rate has not sufficiently decreased at the end of the rest period, the worker is in a state where fatigue due to the thermal load remains large, and the risk of developing heat stroke is high. It can be evaluated as a state.

As described above, the evaluation result by the hot environment evaluation method according to the present embodiment shows not only the external weather conditions such as the temperature and humidity represented by the WBGT index, but also the size of the work load on the worker and the It was confirmed that the heat environment in which workers are actually placed is being evaluated, such as recovery of physical strength.

(Effective evaluation of heat stroke risk reduction measures)
As described above, in the hot environment evaluation according to the present embodiment, it is possible to evaluate the environment in which a group of workers is actually placed, including not only external factors but also work loads. By using this fact, it is possible to evaluate the degree of effectiveness of various measures as measures against heatstroke.

FIG. 13 is a diagram showing changes in the average heart rate of workers during breaks.

More specifically, FIG. 13 shows the results of evaluating the average heart rate, that is, the degree of decrease in core temperature, by extending the rest period from 15 minutes to 30 minutes. The data in FIG. 13 are the heat environment evaluation for the group of 13 workers working at the construction site shown in FIG. An average heart rate 131 and an average heart rate 132 on days when the WBGT index is 31° C. or higher are shown.

As shown in Figure 13, the average heart rate drops almost linearly during the rest period. On the day when the maximum temperature is 25° C. and the external heat stress is low, the resting heart rate drops to around 80 bpm in about 20 minutes. On the other hand, on days when the WBGT index is 31°C or higher, where external heat stress is high, the average heart rate drops only to 85 bpm during a 30-minute rest period, and the core temperature drops to the resting level. I know it's not. On the other hand, it is clear that the longer the rest period, the more the average heart rate gradually decreases. A further decrease in heart rate can be expected.

In this way, by changing the external heat stress and understanding the average heart rate of the population, it is possible to adopt measures such as extending the rest period until the average heart rate of the population is sufficiently reduced. , It can be seen that the risk of developing heat stroke can be reduced. In addition, as shown in Figure 13, when the WBGT index is 31°C or higher, under conditions of great heat stress, the rest period should be lengthened, the temperature of the rest room should be lowered, and eaves should be installed in the rest area. It can be evaluated that it is necessary to improve the environment, such as blocking direct sunlight by using a light source, and to take breaks in a more effective state.

According to the heat environment evaluation method described in the present embodiment, even if there is a difference between the effect as a bodily sensation and the effective effect of actually lowering the core temperature and reducing the risk of developing heatstroke. Even if there is, it can be quantitatively evaluated as objective data.

(Evaluation result as a heatstroke risk evaluation index)
Next, as an evaluation result example of the heat environment evaluation according to the present embodiment, the evaluation of the core temperature from the collective average heart rate of the worker described above and the heartbeat data and Evaluation results using the average value of the hot work risk index (work burden index) of each worker obtained from the acceleration data will be described, including differences from the WBGT index.

FIG. 14 is a diagram showing an example of heatstroke risk assessment based on average heart rate using the hot environment assessment system according to the present embodiment. Moreover, FIG. 15 is a diagram showing an example of heat stroke onset risk evaluation based on the average value of the work burden index using the hot environment evaluation system according to the present embodiment.

FIG. 14 is a diagram showing changes in the worker's average heart rate 141 and the temperature 142 around the work site on a very hot day when the maximum temperature was 39°C. As shown in FIG. 14, the surrounding air temperature 142 is around 39° C. from 12:00 to 14:00. However, the average heart rate of the workers on this day exceeded line 143, which indicates a core temperature of 38°C, which is at an extremely high risk of developing heatstroke, around 9:00 in the morning and from 14:00 to 15:00 in the afternoon.

In this way, the worker takes a break twice a day in the morning and in the afternoon, and also takes a lunch break from 12:00 to 13:00. It can be seen that the change in temperature, especially the time period when the risk of developing heat stroke is high, does not depend only on the change in temperature.

In addition, the average value 151 of the hot work risk represented as the work burden index shown in FIG. , and around 14:00 in the afternoon, it greatly exceeds the line 154 with an index of 1.0, which is judged to be a "dangerous" state. In this way, based on both the acceleration data and the heartbeat data, which indicate the movement of the body, the work content and the It can be seen that a more accurate heat environment evaluation can be performed for a group of workers, taking into account the accumulation of fatigue due to the passage of working hours.

On the other hand, the WBGT index indicated by the solid line 152 in FIG. 15 shows little change in the numerical value in one day, and even though the temperature (142 in FIG. 14) exceeds 39°C, the maximum is 31°C. It's becoming This is probably because the WBGT index is a numerical value determined based on temperature and humidity, and the humidity on the day of measurement was as low as about 40%. In addition, the WBGT index is only an index for evaluating the hot environment as the external environment, and it is not possible to evaluate the hot environment inside the work clothes, which has a large effect on the action of lowering the body temperature of the worker, such as perspiration. Conceivable.

As described above, the WBGT index, which has been conventionally used as a hot environment evaluation numerical value for evaluating the risk of developing heatstroke, cannot be used as it is to perform a hot environment evaluation that follows the worker's work environment. Therefore, in evaluating the risk of developing heat stroke using the WBGT index, it is necessary to convert the values into heat environment evaluation values that are more suitable for the actual situation, taking into consideration the work situation and work clothes. However, this figure varies depending on how the actual work conditions are assumed. Not sure if it's done. In addition, as shown in the evaluation results of the hot environment shown in FIG. 15, the WBGT index is sufficient for evaluating the risk of developing heatstroke on extremely hot days when the maximum temperature is around 40 ° C, which has frequently occurred in Japan in recent years. It's hard to imagine that we're ready.

On the other hand, according to the method disclosed in the present application of grasping the biological information of workers as a group and evaluating the hot environment using the average value of the heart rate and the work load index, the group of workers is actually placed. It is possible to accurately evaluate the hot environment in which it is installed.

In the above-described embodiment, workers at a construction site are used as subjects, and biological information of workers obtained by an evaluation system that evaluates the risk of developing heat stroke is used (so to speak, as an "observation post"). , explained the evaluation method and evaluation system for assessing the heat environment risk as a group.

However, the group evaluation method and the group evaluation system disclosed in the present application are not limited to those exemplified above, and can acquire biometric information of a plurality of subjects that constitute a specific group. If it is possible to evaluate the environment of the group based on the evaluation, the physical condition of the individual subject will be evaluated.・Environmental assessment can be conducted as a group in addition to the management system. In addition, group evaluation is, of course, not an attachment to an evaluation system that evaluates the physical condition of an individual evaluator, but an evaluation system configured to conduct an environmental evaluation of a group of subjects. It can be carried out.

Also, a group can be formed dynamically and automatically by using short-range wireless communication such as Bluetooth (registered trademark), which has become popular in recent years. For example, it is possible to mount a BLE (Bluetooth Low Energy) device on each subject's biosensor and detect other nearby subjects by means of beacons. By installing a beacon receiver in the environment and combining it with the function of the evaluation judgment unit, it is possible to form a group and conduct a group environment evaluation even in a place where the communication environment such as the Internet cannot be used. In recent years, even more advanced standards such as Bluetooth Mesh have been put into practical use, enabling many-to-many communication between biosensors and realizing an environment evaluation system by an unspecified number of people. can.

The group evaluation method and the group evaluation system disclosed in the present application are, for example, a construction site, a transportation industry, etc., where workers are placed in a state where physical load and thermal load are large. It is possible to realize an evaluation method and an evaluation system capable of performing accurate and rapid evaluation.

10 Worker (evaluated person, target person)
11 biosensor (measuring device)
12 Smartphones (mobile terminals)
13 Evaluator Information Transmission Unit (Information Transmission Means)
22 Risk Judgment Department (Evaluation and Judgment Department)

Claims (11)

A group environment assessment method for assessing environmental risks in a group by a computer operated by a computer program,
For a group consisting of a plurality of subjects, a representative value of the heart rate of the group is calculated from the heart rate as heart rate data, which is biological information obtained from each of the plurality of subjects, and based on the obtained representative value , A group environment evaluation method, characterized by evaluating the heat environment risk in the group. 2. The group environment evaluation method according to claim 1, wherein any one of an average value, a median value, or a mode value of the heart rates of the plurality of subjects is used as the representative value of the heart rate of the group. 3. The group environment evaluation method according to claim 1, wherein said group consists of a plurality of subjects having common environmental conditions. further including acceleration data indicating the motion of the subject as the biometric information;
calculating a work burden index for each of the subjects based on the heartbeat data and the acceleration data obtained from the plurality of subjects belonging to the group;
The group environment evaluation method according to claim 1, wherein a hot environment risk in the group is evaluated based on a representative value of the group calculated from the work burden index of the subjects belonging to the group. a measuring device for acquiring biological information of a subject;
an evaluation determination unit that calculates a representative value of the biometric information in a group consisting of the plurality of subjects based on the biometric information obtained from the plurality of subjects, and evaluates the hot environment risk in the group. A group environment evaluation system, characterized by comprising: 6. The group environment evaluation system according to claim 5, further comprising information transmitting means for transmitting said acquired biometric information to said evaluation determination unit. 7. The group environment evaluation system according to claim 5, wherein said evaluation determination unit is installed in a server on a network. 8. The group environment evaluation system according to any one of claims 5 to 7, wherein said measuring device is a biosensor comprising a heartbeat sensor for detecting heartbeat data worn by said subject and an acceleration sensor for detecting acceleration data. . The group environment evaluation system according to any one of claims 5 to 8, further comprising group forming means for forming said group. 10. The group environment evaluation system according to claim 9, wherein said group forming means detects a plurality of subjects having common environmental conditions, and forms said group with said plurality of detected subjects. 11. The group environment evaluation system according to claim 10, wherein said group forming means detects other target persons existing near said target person as a plurality of target persons having said environmental conditions in common by means of short-range wireless communication means. .

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