JP2022142082A - Health management system using bio-information sensor, work burden determination program for health management system, and data structure for health management system - Google Patents

Abstract

To provide a health management system that integrally supports both work of a personnel management and health and safety management administrators perform, and, when an excessive work burden is predicted, issues detailed warnings to the administrator and workers to prevent industrial accidents and the like in advance, and is excellent in convenience for both the administrator and worker.SOLUTION: A health management system is the health management system in which a sensor 1, a gateway terminal 2, a server 3 and an information visualization system 4 cooperate thanks to an application. The health management system is configured to, as to bio-data the sensor 1 acquires, convert a core temperature, a heart rate, and a rate of change in a moving average value for each stress index into an evaluation point on the basis of, an item evaluation table, and, when a warning score totaling an evaluation point of four kinds obtained by converting a difference rate obtained in comparison of a moving average value of a respiratory rate with a set reference value into an evaluation point on the basis of the item evaluation table exceeds a first threshold, issue a first warning, and when the score exceeds a second threshold, issue a second warning.SELECTED DRAWING: Figure 1

Description

The present invention relates to a health care system using biosensors.

Work sites such as construction work and security work are often under harsh working environments such as outdoors in extreme heat or extreme cold, or closed spaces. In Japan, the aging of workers due to the declining birthrate and aging population is also an issue that needs to be addressed. Workers have various attributes such as age, gender, and physical strength, but compared to general office work, the physical and mental burden of field work is heavy, and there is a risk that workers will be exposed to sudden and excessive workloads. be. In fact, it has been confirmed that there are problems that are difficult for people to predict, such as workers who have been judged to be able to work without any abnormalities in preliminary medical examinations, but who have unexpectedly developed heatstroke.
On the other hand, on the side of a manager who employs many workers as employees, the responsibility of the user is a broad and serious responsibility. Among the management tasks that managers carry out on a daily basis while assuming such responsibilities, proper management of labor and occupational safety and health, which is directly linked to the health and life safety of workers, is extremely important and urgent management. has become an issue. In recent years, work style reform has been discussed in Japan, and awareness of such management work has increased. Realization is required.
Various research and development efforts have been made to contribute to the prevention of heat stroke, which is a serious occupational accident. It seeks to warn employees of the danger of heatstroke by monitoring core body temperature and heart rate. In Patent Document 2, while focusing on core body temperature and heart rate, the earplug-type heat stroke warning device is easy to use even in various usage environments as a small and light weight earplug type device.
Various proposals have also been made so far for devices for evaluating mental and physical stress, which is considered to be a disorder of the autonomic nervous system, although it has a purpose different from the prevention of heatstroke. The autonomic nerve function evaluation device of Patent Document 3 extracts a heartbeat cycle fluctuation component corresponding to respiratory fluctuation and a heartbeat cycle fluctuation component corresponding to blood pressure fluctuation to evaluate autonomic nerve function. It has been proposed as a device that is simpler and cheaper than a product. Further, as a technique for evaluating mental stress by analyzing heartbeat fluctuations, that is, heartbeat cycle fluctuations and breathing cycles, the apparatus of Patent Document 4 has also been proposed.

JP 2009-108451 A JP 2010-131209 A JP-A-10-328148 Japanese Patent Application Laid-Open No. 2010-234000

“Science of Stress and Autonomic Nervous System” (http://hclab.sakura.ne.jp/) Confirmed on February 1, 2021. “Study on Mental Stress Evaluation Method by Heart Rate Fluctuation” (Life Support vol.22 No.3 2010) Yoshiaki Matsumoto, Nobuaki Mori, Ryo Mitajiri, and Zhongwei Eg (https://www.jstage.jst.go.jp/article) /lifesupport/22/3/22_105/_pdf) Confirmed on February 1, 2021. "Rapid Response System (RRS) - Japanese Society for Emergency Medicine" Shinsuke Fujiwara, Takamitsu Kodama, Kazuaki Ataka, Masashi Nakagawa, Shigeki Fujitani (https://jsem.me/pdf/about_rrs_1301110.pdf) February 2021 1 day confirmation.

Regarding workers who engage in harsh work at remote work sites where it is difficult to directly manage, the appropriate and It is an object of the present invention to provide a health management system, a program used therein, and the like for effectively supporting efficient execution.
Regarding heat stroke prevention and stress evaluation, various proposals have been made, as in the above-mentioned patent documents, but before a major health risk such as heat stroke manifests, regardless of whether the worker himself is aware of it, excessive It is a continuous accumulation of physical and mental burdens. It is necessary to detect minute signs of increased risk at the earliest possible stage while responding to individual differences among workers and prevent the manifestation of risk. is in an unthinkable situation.
Furthermore, with the implementation of the new international standard (ISO45001), which requires the construction and continuous maintenance of an advanced occupational safety and health management system, we will strive to manage the working conditions and mental and physical health conditions of workers more appropriately than before. However, a highly convenient health management system that comprehensively supports these management tasks, is easy to handle for both managers and workers, and is highly convenient has not been realized.
For this reason, when an excessive increase in workload that adversely affects the health of workers is predicted, the workload can be determined more precisely than ever before, and warnings can be issued. This invention solves the problem by realizing a health management system that can prevent this in advance, provide comprehensive support for managers in both management work of labor management and occupational safety and health management on both sides of mind and body, and realize a health management system that is easy for both labor and management to use. This is an issue that should be addressed.

The present invention, which is means for solving the problems, is a health care system using a biological information sensor and a workload determination program used therein, as described below.
The health management system is a system in which sensors, gateway terminals, and servers cooperate through application software (hereinafter referred to as "apps"). An information visualization system will be incorporated to support the understanding.
The sensor collects biometric data related to the wearer's deep body temperature (C = Core Temperature), heart rate (H = Heart Rate), stress index (L = LF/HF), and respiratory rate (R = Respiratory Rate). and transmit various data including these to the gateway terminal over time. The gateway terminal analyzes the received biometric data as time-series data, sets it as a moving average value per predetermined unit time, and transmits it to the server together with the work data etc. input by the sensor wearer from the gateway terminal. The server receives various data including moving average values per predetermined unit time and working data related to these biometric data, and manages them in association with an identification code (ID) for each sensor wearer. For system users who access this system via an information communication network such as the Internet, a web page will be provided on the browser of the access terminal that can be used to query various data such as biometric data and employment data for each sensor wearer. offer.
In addition, the server includes an item rating table defining comparative values that determine scores for core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R). App is configured. Then, for each core body temperature (C), heart rate (H), and stress index (L), the rate of change obtained by comparing the moving average values of a predetermined time ago and the current time is converted into an evaluation score based on the item evaluation table. At the same time, the number of differences obtained by comparing the moving average value of the respiratory rate (R) before a predetermined time with the set reference value is converted into an evaluation score based on the item evaluation table. Next, a warning score is obtained by summing the four evaluation points of core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R), and when this exceeds the first threshold, the second One alert data is sent to the gateway terminal and the access terminal, and a second alert data is sent when the alert score exceeds the second threshold. That is, the workload determination function of this system is executed by the sensor, gateway terminal, and server cooperating with each other through an application.
In addition, an emergency notification function is added to this workload determination in order to predict the increase in risk more precisely in the previous stage and prevent its manifestation. Regarding core body temperature (C) and heart rate (H), each evaluation point is added (or Points are directly added to the "warning points". The same applies hereinafter.). Furthermore, if the same trend continues for more than a predetermined number of times, second warning data is sent to the gateway terminal and the access terminal. Further, the posture data of the person wearing the sensor is acquired, and if this is continuously confirmed as information indicating the lying state and exceeds a predetermined time, points are added to the warning score. Also, when the moving average value of the respiratory rate (R) exceeds a predetermined number of times, points are added to the evaluation points.
In addition to these emergency notifications, this system also reduces the workload related to warning issuance in order to issue warnings that emphasize safety or to suppress the issuance of warnings that are considered excessive for the work content. A correction function based on exercise intensity during work is installed to adjust the judgment. That is, the exercise intensity is calculated from the maximum heart rate set corresponding to the age of the sensor wearer and the actually measured heart rate (H), and the change in the moving average value of the exercise intensity per predetermined unit time. When the rate continues to increase for a predetermined number of times and the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times, the evaluation score is multiplied by a predetermined coefficient exceeding 1. is done. In addition to the method using the maximum heart rate, there are methods for calculating the exercise intensity based on the heart rate reserve or oxygen uptake, but the exercise intensity based on the maximum heart rate will be described below as an example .

Also, the workload determination program for this system executes information processing by the following processes.
First, a first process of obtaining each time-series data from four types of biological data on the sensor wearer's core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R); There is a second process of obtaining a moving average value for each predetermined unit time from the series data. Next, for each of the core body temperature (C), heart rate (H), and stress index (L), the rate of change obtained by comparing the moving average values between a predetermined time ago and the current time is calculated based on the item evaluation table. In addition to these conversion processes, for the respiratory rate (R), the number of differences obtained by comparing the set reference value and the moving average value before a predetermined time is calculated based on the item evaluation table. There is a third process of converting to evaluation points. And 4 related to core body temperature (C), heart rate (H), stress index (L) and respiratory rate (R) obtained in the first to third synchronized and continuously executed processes A workload determination comprising a fourth step of issuing a first warning when the total warning score obtained by summing the evaluation points of the items exceeds the first threshold, and further issuing a second warning when the second threshold is exceeded. It's a program.
And depending on the specifications, regarding the core body temperature (C) and the heart rate (H), each evaluation point when the rate of change of the moving average values of either increase or decrease continues for a predetermined number of times There is a fifth step of adding points to , and issuing a second warning when the consecutive number of times exceeds a predetermined number of times determined at a higher level. In addition, there is a sixth step of obtaining posture data from the person wearing the sensor, continuously confirming this as information indicating the lying state, and adding points to the warning points when the data exceeds a predetermined time. Further, the workload determination program has an emergency notification function and a seventh step of adding points to the evaluation points when the moving average value of the respiratory rate (R) exceeds a predetermined number of times. The processes from the fifth process to the seventh process are executed in synchronization with the workload judgment of the third process and the fourth process.
Furthermore, from the maximum heart rate set in advance corresponding to the age of the sensor wearer and the heart rate (H) measured by the sensor, the exercise intensity during work is analyzed, and the exercise intensity per predetermined unit time When the rate of change of the moving average value of the respiration rate (R) continues to increase for a predetermined number of consecutive times, and at the same time, the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times, a predetermined coefficient exceeding 1 is evaluated. It is a workload determination program equipped with an exercise intensity correction function having an eighth process as a correction process performed by multiplying by .
In addition, the data structure for the health management system, which is analyzed and processed in determining the workload of this system, is used in continuous accuracy improvement of the data accumulation table and the item evaluation table.

This system is capable of real-time monitoring and management of the health condition of worker W, who wears the sensor, and multifaceted analysis of physical and mental overload to detect signs of mental and physical disorders, including heat stroke, which is difficult to predict. , prevent the manifestation of those risks as early as possible.
At the same time, by supporting occupational safety and health management not only for physical aspects but also for both mental and physical aspects, it will become a health management system that conforms to new international standards, and will include complicated administrative procedures such as reports and confirmations for both labor and management. Since labor management is also simplified and integrated, it is possible to continue to carry out both of these management tasks effectively and efficiently.
Regarding the workload judgment related to warning issuance, in addition to core body temperature (C) and heart rate (H), which are greatly influenced by physical factors, as the pillars of evaluation items, mental factors also affect the physical aspect. The stress index (L) and respiratory rate (R) are used together as biometric data, and determination is made based on multifaceted evaluation items. In addition, emergency notification and exercise intensity correction make it possible to make more detailed judgments than ever before.
Then, under the cooperation of the item evaluation table and the data accumulation table, it has a highly expandable workload judgment function that can correspond to each type of work with different environments and contents, and for each worker with individual differences. did. In addition, based on the data structure for the health management system that is integrated and associated with this system on a large scale, the health management system can realize continuous improvement in the accuracy of the workload determination function.

It is an outline of the whole composition of a system. It is an example of data handled by the system. It is a flow of biometric data analysis processing. It is an outline of a workload judgment program. It is an example of an item evaluation table. It is an example of a data collection table. It is an example of a home screen. It is an example of a user management menu screen. It is an example of a work place management menu screen. It is an example of a work content management menu screen. It is an example of a measurement parameter management menu screen. It is an example of an attendance setting menu screen. It is an example of a mail setting menu screen. It is an example of the work start screen of a gateway terminal. It is an example of a work screen of a gateway terminal. It is an example of the core body temperature screen of the gateway terminal. It is an example of a warning confirmation screen. It is an example of a work viewer screen. It is a part of the graph display part of the sensor information screen. This is part of the data display section of the sensor information screen. It is an example of a work management screen. This is an example of a labor management form (work schedule).

The present invention will be described below with reference to the drawings.
FIG. 1 shows the basic configuration of this system forming an information network system. Both the manager M and the worker W are displayed at both ends of the network as system users in a broad sense. A worker W at the lower left is a sensor wearer who wears the sensor 1 and operates the gateway terminal 2 . A manager M on the upper left is a narrowly defined system user who receives direct support from this system for management work, and operates an access terminal 5 at a location separate from the worker W. FIG.
A typical worker W is outside the direct control of manager M, and works in a harsh working environment such as outdoors in the hot sun or extreme cold without air-conditioning equipment, or in closed spaces where physical and mental stress is excessive. is a person. Workers engaged in construction work, security work, and even decommissioning work at nuclear power plants fall under this category regardless of the type of employment. . The manager M is a person who is involved in the overall management of the business, including the labor affairs of the workers W and occupational safety and health.
Both of them can coexist with a large number of persons belonging to different hierarchies who are responsible for various duties. There is a many-to-many relationship in which multiple parties are related to each other.

In the health management system according to the present invention, the sensor 1, the gateway terminal 2 and the server 3 work together, but according to the specifications of the system, an information visualization system 4 is incorporated as a function improving tool. In FIG. 1, a sensor 1 worn by a worker W is a minute terminal for acquiring biometric data. The gateway terminal 2 is a mobile terminal for information processing that functions in cooperation with the sensor 1 . Both of them are operated by a worker W at the work site. The server 3 installed at a location away from the work site is in charge of data analysis processing, management, etc., and has a database function. The information visualization system 4 that cooperates with this is responsible for visual information processing, so-called visualization processing, for improving the user interface and enhancing the utility value of data. However, in many cases, the server 3 and the information visualization system 4 are functionally integrated. The access terminal 5 is an information terminal used by the administrator M for data communication with the server 3 in order to use the support service provided by this system. A manager M accesses this system by operating it in a management office or the like away from the work site.
Of these five devices, the devices that make up this system are the sensor 1 , gateway terminal 2 , server 3 and information visualization system 4 . Both of them are devices for executing information processing such as biometric data acquired from the worker W as a system in which hardware and application software for this system cooperate. In addition, as will be described from time to time below, in order to determine the optimum specifications of this system in consideration of the performance of each device, it is conceivable that the functions of the data analysis processing are appropriately shared among the devices. Therefore, as a variation of this system, it is assumed in advance that the specifications may be changed such that the functions are assigned differently among the devices, or the specifications may be omitted, for example, a part of the visualization processing function.

At the start of field work, the worker W wears the sensor 1 near the chest where biological data such as body temperature and electrocardiogram can be obtained. Since the sensor 1 is designed to be ultra-compact and lightweight, it does not interfere with work, but a fixing device for wearing is used as necessary. After wearing the sensor 1, the worker W performs the initial operation of the gateway terminal 2, and the sensor 1 acquires a plurality of biological data from the worker W who is working and transmits them to the gateway terminal 2 via wireless communication. At this time, along with the biological data, activity data such as the number of steps acquired by the sensor 1 and environmental data such as temperature are also transmitted.
The data transmitted by the sensor 1 is received by the gateway terminal 2 at the site. The gateway terminal 2 is a small terminal that is easy to carry and has data input/output, transmission/reception, processing, and management functions, and is equipped with an application for this system. The worker W can check the received data and the communication status at the gateway terminal 2, and also uses it to input working data such as the start of work and report data such as physical condition. Various data including biometric data acquired by the sensor 1 and transmitted to the gateway terminal 2, and working data and the like input by the worker W through the gateway terminal 2 are installed at a remote location from the work site via an information communication network. is sent to the server 3. At this time, the gateway terminal 2 converts, for example, the biometric data into a one-minute moving average value, and arranges the data flow between the sensor 1 and the server 3 .

The server 3 receives a large amount of data transmitted by multiple gateway terminals 2 from multiple work sites. These data are analyzed according to their type and managed in a database as a group of data that can be used in a timely manner. According to the specification of this system, mainly in the server 3, multifaceted analytical processing of biometric data is performed step by step and concurrently in part of the process. At that time, the analysis processing branched into a plurality of processes is also executed for the mental and physical workload that the worker W continuously accepts unconsciously. Then, if necessary, a step-by-step warning is issued to inform the manager M and the worker W of the high-risk excessive load state. Similarly, depending on system specifications, an information visualization system 4 that is functionally integrated with the server 3 and incorporated into the application performs visualization processing when information is provided.
Various data related to work and health accumulated in the server 3 through analysis processing are processed according to preset processing conditions or in response to individual requests from the gateway terminal 2 or the access terminal 5, and the manager M or the work provided to person W. An administrator M connects to the Internet using the access terminal 5 and accesses the system from a login screen on the web. Therefore, the manager M can access the system even outside the management office as long as the environment allows connection to the Internet. The manager M can confirm in real time the situation of the worker W who is working at a remote location, and the worker W can also know his own health condition and overload situation.

The sensor 1, the gateway terminal 2, the server 3, the information visualization system 4, and the access terminal 5 used by the manager M to connect to the system will be described individually.
The first component is sensor 1 . This system is mainly used to analyze biological data, namely core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R). It acquires it as data and transmits each data to the gateway terminal 2 in chronological order. The sensor 1 is a device called a so-called biometric information sensor. In order to reliably acquire biometric data, the electrodes of the sensor 1 are attached to the operator by using a fixing device specially developed for this system. Wear it close to W's chest. With the rapid progress in miniaturization and advanced functions, products that can continuously acquire electrocardiograms are being offered in order to visualize heart activity as an electrocardiogram. The multifunctional/highly functional sensor 1 can directly acquire biometric data such as body surface temperature from the worker W in addition to the electrocardiogram. , core body temperature (C), heart rate variability (also referred to as “heart rate fluctuation”; hereinafter, unified as “heart rate variability”), and other secondary biological data can be obtained. In addition, the same sensor 1 can simultaneously acquire activity data such as the number of steps of the worker W and changes in posture, and environmental data such as the environmental temperature, relative humidity and altitude of the work site.
As an example of an ultra-compact and high-performance sensor 1, a small, lightweight, power-saving wearable biosensor provided by Affordsense Co., Ltd. (hereinafter referred to as "Company A") is a terminal that can be used in this system. exist. In the course of this development, the applicant used the sensor 1 optimized for this system after being improved by Company A, and conducted demonstration tests at work sites. Its size is 6 cm x 3 cm x 1 cm in length x width x thickness, and its weight is about 15 g. It can operate continuously for a long time with a lithium-ion battery, etc., and can continuously transmit data via Bluetooth (registered trademark), one of the short-range wireless communication standards for digital devices. The sensor 1 calculates a heart rate (H), a heartbeat interval, and a heartbeat variability through an electrocardiographic analysis, and further calculates a stress index (L) by analyzing the heartbeat variability. The sensor 1 also estimates the core body temperature (C) from the body surface temperature and heat flow. The details of the stress index (L) will be explained later.

By the way, the conventional biological information sensor has a limit of information processing ability, and the amount of arithmetic processing and data processing that can be executed inside the sensor is also limited. Therefore, it is conceivable that the data is transmitted to devices after the gateway terminal 2 with high processing capability, and most of the complicated analysis is entrusted to the gateway terminal 2 and the server 3 . However, due to recent improvements in microprocessors (MCUs), the sensor 1 is equipped with the necessary storage and arithmetic units and has become more efficient. I am in a position to do so. As a result, the system specifications are optimized by assigning functions to each device in consideration of the processing capacity of each device, performing the necessary analysis processing inside the sensor 1, and only the minimum data is sent to the gateway terminal 2. All that is required is transmission, and the burden on both the transmitting side and the receiving side can be reduced. Against the backdrop of such improvements in the capabilities of the sensor 1, it is also possible to bring forward part of the analysis processing of the server 3 and allow the gateway terminal 2 to share part of its functions. From the point of view of nature, the following system will be described below.
That is, the operator W operates the gateway terminal 2, the connection between the sensor 1 and the gateway terminal 2 is established, the connection between the gateway terminal 2 and the server 3 is also established, and the sensor 1, the gateway terminal 2 and the server that constitute this system are established. Data communication becomes possible between 3. The biometric data acquired by the sensor 1 and transmitted to the gateway terminal 2 is analyzed by an application of the gateway terminal 2 and transmitted to the server 3 . As an example of this analysis processing, biometric data continuously transmitted from the sensor 1 is received, temporarily stored in the storage area of the gateway terminal 2, converted into time-series data of one-minute moving average values, and the communication data is converted to The data is arranged and transmitted to the server 3 after reducing the total amount of data. This has the meaning of optimally allocating the analysis processing from the sensor 1 to the server 3, improving the efficiency of the data flow, and reducing the load on the server 3 where data is accumulated on a large scale. Regarding the data accumulation in the server 3, the load can be further reduced by allowing the manager M to periodically download the necessary data to the access terminal 5 and deleting the old data in order. Then, based on the biometric data transmitted from many gateway terminals 2, the server 3 estimates the workload of the worker W by the workload determination function installed in the application, and the gateway terminal 2 and the access terminal 5 It will be explained as a system that issues a warning as necessary.

The second component of this system is the gateway terminal 2 . A worker W wearing the sensor 1 performs an initial operation on the gateway terminal 2 , pairs the sensor 1 and the gateway terminal 2 , and establishes a data communication path from the sensor 1 to the server 3 . The gateway terminal 2 receives and analyzes the biometric data transmitted from the sensor 1 over time, sets each biometric data to a moving average value per predetermined unit time, and obtains working data input from the gateway terminal 2 by the worker W. to the server 3 together with Each worker W carries the gateway terminal 2 together with the sensor 1, but unlike the sensor 1, the gateway terminal 2 is not worn directly on the body. Since the gateway terminal 2 has a built-in GPS, it is possible to grasp the current location and moving route of the worker W.
A dedicated terminal for this system may be used, but in consideration of cost reduction and portability, it is possible to utilize compact information communication terminals such as smartphones and tablets that are widely used in society, such as iOS and Android (registered trademark). A dedicated application running on the OS is installed. The operation and operation of the application and its functions will also be explained later as a specific method of using this system.
The worker W inputs working data from the gateway terminal 2 in order to report to the manager M the work engagement status such as start time and end time. The input employment data is transmitted to the server 3, linked with the biometric data, and managed by the server 3. The worker W can check the status of communication with the sensor 1 and the received biometric data at the gateway terminal 2 , which is also used when checking warnings issued from the server 3 . The worker W can also use the gateway terminal 2 for various business communications with the manager M.

The third component is, in many cases, a plurality of gateway terminals 2 and access terminals 5, and a server 3 connected via an information communication network such as the Internet. This server 3 has a database function, and receives biometric data converted into time-series data of a moving average value per predetermined unit time by the gateway terminal 2, working data input by the gateway terminal 2, and the like. Various data received in large quantities are analyzed by the server 3 and managed for each worker W, that is, each person wearing a sensor, and a web page is provided on which individual biometric data, work data, etc. can be appropriately inquired. Then, according to preset processing conditions or in response to a request from the manager M or the like, necessary information is extracted from the database in which the data is accumulated, and is displayed as data that can be displayed on the access terminal 5, or Send as data that can be printed by a printer or the like.
In addition, this system uses the time-series data obtained from the analysis of biological data and the workload determination function of the server 3 to estimate the physical and mental workload status of the worker W in real time, and issue warnings ( (YA=Yellow-Alert) and warning data (RA=Red-Alert) are transmitted to the worker W and the manager M. Note that the types of data processed by the applications installed in each device and the overview of the analysis processing will be described again as examples of data and the flow of data processing.
This server 3 can be installed in an individual company, placed in a remote location different from the location, or jointly installed for the purpose of centrally managing a large number of work sites of multiple companies. The administrator M and worker W who are the users of this system, the gateway terminal 2 and the access terminal 5 connected via the server 3 are users and terminals of one company, etc. The users may belong to different organizations, or the terminals may be managed individually by each organization. This system can be a health management system that can be shared by multiple companies beyond the framework of a single organization. can also be provided on the cloud.

When providing a health information management service by this system, the information visualization system 4 can be incorporated as a function improvement tool for improving the user interface and supporting the quick and accurate information acquisition and understanding of the manager M. . As an example of this, it is possible to partially modify an application that has already been put into practical use as a business intelligence (BI) tool. As a result, the information visualization system 4 functions together with the server 3, and in response to the request of the manager M, visualizes the results of the analysis processing of the biometric data of the worker W on the web space provided by this system in an easy-to-read manner. give me
As a specific example, when a large number of workers W are working at a plurality of sites, the map displayed on the screen of the access terminal 5 shows individual worker tabs based on the GPS data of the gateway terminal 2. It is displayed, and the manager M can immediately grasp the positions of the worker W and the work site. Also, when you click on the listed work place tab, a surrounding map including the work site is immediately displayed on the screen. Furthermore, when the sensor information tab displayed as a list is clicked, the biometric data for each worker W is displayed as a graph or list in an easy-to-read manner.

The access terminal 5 is a terminal used by the manager M to access the system, obtain information, and monitor and manage the status of the worker W in real time. General-purpose personal computers, tablets, and the like, which have already been widely used in society, can be used, and the models are not limited as long as the required specifications are satisfied. The administrator M connects the access terminal 5 to the Internet and enters the ID and password from the login screen on the web to access the system. Therefore, it is possible to access from outside the management office using a tablet or smartphone with an appropriate communication environment.
Typically, such terminals are pre-equipped with input/output devices, storage devices, arithmetic devices, and transmission/reception devices, or can be added or connected afterwards. Therefore, in the access terminal 5, biometric data, employment data, and the like transmitted from the gateway terminal 2 and the server 3 are graphically displayed on the monitor for easy viewing, and the data can be downloaded and saved. In addition, information processing suitable for data characteristics, such as outputting visually (images, etc.) and audibly (audio, etc.) warnings sent after the workload judgment has been performed, can be reliably recognized by the manager M, etc. executed. When the manager M needs such data in the management work of labor and occupational safety and health, it is possible to output it from a printer as a form such as a work schedule and a record book, and to browse and store it. .

Fig. 2 shows the main data handled by this system. The biometric data of the worker W shown on the left side is the core data of the analysis process.
As information on body temperature, in addition to the body surface temperature of the skin surface that is in direct contact with the sensor 1, the deep body temperature (C), which is less affected by the outside air temperature, is considered, and this system emphasizes the latter. The core body temperature (C) tends to fluctuate closely to values measured at the eardrum, rectum, etc., and can be estimated by correcting these values. It can also be estimated by performing conversion processing based on the measured body surface temperature and heat flow.
The sensor 1 acquires an electrocardiogram representing the activity state of the heart, and based on this, analyzes the heart rate (H), the respiratory rate (R) related to oxygen intake, and the like. As will be described later, heart rate (H) and heartbeat intervals can be obtained by electrocardiographic analysis processing, and information on heart rate variability can also be obtained. Further, the sensor 1 analyzes the heartbeat variability, which is used as a balance index of the autonomic nervous system, and can obtain a stress index (L) related to the physical and mental load of the worker W. These analysis processes can be executed by the sensor 1, but it is also possible to assign functions to other devices.
The respiratory rate (R) per unit time is understood as the reciprocal of the respiratory interval, and can be an index for determining whether the worker W is taking oxygen normally. Just as excessive mental and physical stress manifests itself as hyperventilation, this respiratory rate (R) is susceptible to both physical and mental loads, like the stress index (L) and heart rate (H). The wearable biosensor manufactured by Company A directly measures the body surface temperature and electrocardiogram of the worker W, and the real-time built-in signal processing algorithm analyzes and immediately obtains the biometric data necessary for this system. It is possible. The biometric data acquired by the sensor 1 is continuously transmitted to the gateway terminal 2 and analyzed and used in the subsequent information processing process.

In addition to the biometric data described above, there are activity data and environmental data that the sensor 1 acquires and transmits to the gateway terminal 2. In addition, there are device data such as the communication state of the sensor 1 and the remaining battery level. . The activity data, which is measured by an acceleration sensor or the like built in the sensor 1, includes the number of steps indicating the movement status of the worker W and information related to the posture including the living state such as standing up or lying down. The environmental data includes environmental temperature, relative humidity, atmospheric pressure, altitude, etc. at the work site and in the vicinity of the sensor 1 . The worker W is always physically and mentally affected by the heat, etc., and the work load is also affected. Numerical values such as the temperature measured by the sensor 1 are numerical values in the work clothes, but under harsh environments where the wearing of protective clothing is obligatory, the numerical values are higher than those under other conditions. The heat index (WBGT value), which indicates the risk of heatstroke, is also environmental data, but it can be analyzed from other acquired environmental data, and can also be obtained via the Internet through electronic information provision services and mail delivery services.
Furthermore, in addition to the data acquired by the sensor 1, there are working data and report data that the worker W inputs from the gateway terminal 2. FIG.

FIG. 3 shows an overview of the data flow, focusing on the main biometric data, as a flow of analysis processing. With regard to electrocardiogram and body temperature, which are the basis of data analysis in this system, the sensor 1 and the gateway terminal 2 work together to perform a plurality of analysis processes simultaneously and in parallel. Other biometric data, activity data, environmental data, employment data, and report data are also subjected to the necessary information processing according to the set analysis procedure. are omitted.
First, the flow of data processing in the sensor 1 will be described.
Biometric data is acquired from the body of the worker W by the sensor 1 paired with the gateway terminal 2 . It is automatically and continuously obtained by the cooperation of the applications installed on both devices, and is in the position where the data flow starts in this system. The biometric data acquired by the sensor 1 is sporadic data that is measured at equal intervals such as seconds, but is acquired over time and recorded to be used as time-series data.
An important piece of biological data is the electrocardiogram. The sensor 1 detects and amplifies the heartbeat activity of the worker W, specifically the weak current generated in association with the contraction activity of the myocardium from the body surface. An electrocardiogram is obtained by graphing the obtained electrocardiogram data in chronological order, and this serves as basic data for analyzing the heart rate (H) and heart rate variability.
After that, the process branches to a heart rate (H) analysis procedure shown in the upper part of FIG. 3 and a heart rate variability analysis procedure shown in the lower part, and these procedures are synchronized to perform concurrent analysis processing.

Analysis of the heart rate branched upward from the heartbeat interval of FIG. 3 will be described.
In the time-series data of the electrocardiogram, the peaks and valleys of the electrocardiogram appear in various sizes. These waves are named P-waves, Q-waves, R-waves, S-waves, T-waves, U-waves, and the like for each part of the waveform, indicating waveform components linked to the activity of the heart. For example, the R wave is seen in the middle of the QRS wave, which indicates the excitation of the ventricles, and is considered to be an electrical signal generated when blood is pumped out from the heart to the whole body due to the rapid contraction of the ventricles, and draws the sharpest peak in the electrocardiogram. . In general, the time difference between the occurrence time of the R wave and the occurrence time of the R wave immediately after that is calculated as the heartbeat interval (RRI = RR Interval), and the heartbeat rate (H) within the unit time from the heartbeat interval can be obtained.

Next, analysis of heart rate variability branched downward from the heart rate interval of FIG. 3 will be described.
The heart rate interval (RRI) is not always constant, but has periodic fluctuations called heart rate variability. Examples of graphs are shown in Figs. The heart rate interval (RRI) fluctuates finely up and down over time, and this heart rate variability can be observed even in a state of calm activity. occurs. According to Non-Patent Document 1, the relationship with autonomic nerves has been pointed out as a factor of heart rate variability. It is said that there is a factor. When the autonomic nervous system functions normally, both respiration-synchronized fluctuations and blood pressure-synchronized fluctuations appear in heart rate variability. It is By analyzing this heartbeat variability, there is a possibility that it is possible to grasp the tendency of both mental and physical stress that the worker W is unconsciously receiving, and this system also focuses on the effective use of this heartbeat variability. .

Furthermore, based on the data on heart rate variability, this system analyzes high frequency (HF) and low frequency (LF) components that contribute to heart rate variability. As described in Non-Patent Document 1, this system performs power spectral density (PSD) analysis to extract periodic structures from heart rate variability time-series data. The periodic structure of heart rate variability can be understood from the obtained power spectral density (PSD), and when the power spectral density (PSD) is analyzed using an autoregressive model, two fluctuation components, which are indicators of the balance of autonomic nervous system function, can be identified. Obtainable. That is, the high-frequency component (HF component) and the low-frequency component (LF component) correspond to respiratory fluctuations. appear in On the other hand, a low-frequency component (LF component) corresponding to blood pressure fluctuation appears in heart rate variability both when the sympathetic nerve is tense (during stress) and when the parasympathetic nerve is tense (during relaxation). Therefore, it has been conventionally proposed to use the ratio (LF/HF) of the high frequency component (HF component) and the low frequency component (LF component) as the stress index (L).

The analysis of body temperature shown at the bottom of FIG. 3 will be described.
The sensor 1 measures the worker W's body surface temperature and heat flow. A calculation formula set according to the specifications of the sensor 1 is used to analyze the core body temperature (C) as an estimated value after conversion to the body surface temperature. This analysis process has already been put to practical use in the biological information sensor manufactured by A company.
Regarding the acquisition of the deep body temperature, it is also possible to change the specifications of the sensor 1 and add a correction to the value directly measured from the body part of the worker W, as long as it does not interfere with the work. is.
As for the respiratory rate (R), data acquisition by the biological information sensor has already been put to practical use. From power spectral density (PSD) analysis for grasping the periodic structure of heart rate variability, a high frequency component (HF component) corresponding to respiratory variability can be obtained, and the respiratory rate (R) of worker W can be estimated.
Then, each data related to core body temperature (C), heart rate (H), respiratory rate (R) and stress index (L) obtained by acquisition and analysis of biological data by the sensor 1 is sent from the sensor 1 to the gateway terminal 2. to, over time via wireless communication.

When the gateway terminal 2 receives the biometric data transmitted from the sensor 1 and transfers it to the server 3, it converts the normal time series data into time series data of moving average values and then transmits the data to the server 3. This involves rectifying the biometric data flowing from the sensor 1 to the server 3, and averaging each data based on electrocardiographic analysis, which tends to be relatively large and easily fluctuating, to reduce the effects of singular values. The purpose is to avoid this and stabilize the warning determination. In addition, there is also the purpose of reducing the load on the server 3 in which data is accumulated on a large scale.

The four biological data received by the server 3, core body temperature (C), heart rate (H), respiratory rate (R), and stress index (L), are basic data for monitoring the health condition of the worker W. It is also used to determine whether or not to issue a warning regarding excessive workload.
Based on FIG. 4, an overview of information processing including a workload determination program, that is, a warning score algorithm, which is installed in the server 3 and is a data processing procedure for determining whether or not warning issuance is required will be described.
The app of the system has comparison values set for determining core body temperature (C), heart rate (H), stress index (L) and respiratory rate (R), as shown in FIG. An item evaluation table is provided.
In determining the workload of this system, the server 3 determines core body temperature (C), heart rate ( Determine scores for each of the four endpoints: H), respiratory rate (R) and stress index (L). Further, a warning score is calculated by summing them, and the necessity of warning issuance is determined by comparing the warning score with two thresholds that serve as criteria for issuing a warning. The procedure is the warning score algorithm shown in the center of FIG.

Regarding this warning score algorithm, we have conducted verification tests at actual work sites such as security, and found that the multifaceted biometric data used as evaluation items in the item evaluation table and the criteria for adding evaluation points in each evaluation item , i.e., the setting of the comparison values in FIG. Depending on these settings, there is a bias in the issuance of warnings, and inappropriate and overly sensitive warnings, which deviate from the level of work load that is actually assumed to be accepted based on hearing from worker W, frequently occur. I noticed a problem.
Based on such problems, for the selection of evaluation items, we selected four types of biological data: core body temperature (C), heart rate (H), respiratory rate (R) and stress index (L). Judgment was made based on time-series data of moving average values, not single-shot data. In addition, for the three evaluation items, core body temperature (C), heart rate (H), and stress index (L), there is no fixed numerical value as a reference for comparison. I came up with the idea that biometric data should be evaluated relative to each other in the time axis of work that is systematically repeated. Therefore, in this warning score algorithm, for each of core body temperature (C), heart rate (H), and stress index (L), the rate of change obtained by comparing the moving average values of a predetermined time ago and the current time is used as an item. Convert to evaluation points based on the evaluation table. In addition, regarding the respiratory rate (R), the number of differences obtained by comparing the set reference value and the moving average value a predetermined time ago is converted into an evaluation score based on the item evaluation table. there is

Regarding the item evaluation table referred to in the warning score algorithm in the application of this system, FIG. 5 exemplifies specific comparison criteria and evaluation points for each evaluation item. As for the core body temperature (C), the score is determined by the rate of change obtained by comparing the 1-minute moving average values at both the time points 15 minutes before and at the present time. Regarding the stress index (L), similarly to the core body temperature (C), the evaluation point is determined from the rate of change in the 1-minute moving average value comparing 15 minutes ago and the current time, and for the heart rate (H), An evaluation score is determined by the rate of change in the 1-minute moving average value between 3 minutes ago and the current time. On the other hand, with respect to the respiratory rate (R), a preset number of times is used as a reference value, and an evaluation score is determined by comparing this with the one-minute moving average value three minutes before.
In the item evaluation table, the core body temperature (C) is divided into 5 levels and the weight of the evaluation points is increased, and the minimum value (15%) of the heart rate (H) addition criterion is that of the stress index (L) (30%). followed by a relative assessment of the stress index (L) next to the heart rate (H). Furthermore, in the structure of the item evaluation table that continues to the absolute evaluation of respiratory rate (R), core body temperature (C) and heart rate (H ) is intended to complement the evaluation by In other words, in order to evaluate the work load in detail, we place more emphasis on changes in core body temperature (C) and heart rate (H), which are directly linked to physical effects. Multifaceted and realistic evaluation is realized by using the index (L) and the respiratory rate (R) together. In this case, the stress index (L) is relatively unstable and fluctuates widely, and the width of the comparison value (50%) for determining points is also large compared to that of the heart rate (H) (35%). numerical value. Respiratory rate (R) is generally accepted as a normal value, with a wide range of respiration rates from 9 to 20 breaths per minute. Therefore, an absolute evaluation was made by comparing with a numerical value set in advance as a reference value. The reference value of the respiratory rate (R) in FIG. The comparison criteria, comparison values, and thresholds set in the included item evaluation table can be changed as necessary.
In this way, the flow of obtaining four types of evaluation points, which become one of the basic data when monitoring the health condition of the worker W and are also used when determining the necessity of issuing a warning, is as follows. It is the function of the first half of the warning score algorithm illustrated in the middle of FIG.

Next, this warning score algorithm is obtained by summing the four evaluation points of core body temperature (C), heart rate (H), stress index (L) and respiratory rate (R) as a function of the second half. Calculate the number of warning points. Then, when the number of warning points that fluctuates from moment to moment exceeds the first threshold, the first warning data is transmitted to the gateway terminal 2 and the access terminal 5, and when the number exceeds the second threshold, the second warning data is transmitted. to send.
In the example of the item evaluation table in FIG. 5, the maximum evaluation score for each evaluation item is 5 points for core body temperature (C), which has a large weight, and other heart rate (H), stress index (L), and respiratory rate. (R) is 3 points each. Therefore, the warning score is 14 points when all the items are full marks.
With regard to addition of evaluation points based on the item evaluation table of FIG. 5, 1 point is added when the rate of change in core body temperature (C) reaches the comparative value of 0.5%, which is the criterion for addition of evaluation points. Furthermore, 0.8% gives a score of 2 points, 1.0% gives a score of 3 points, 1.3% gives a score of 4 points, and a rate of change of 1.5% or more gives a score of 5 points. Similarly, when the rate of change in heart rate (H) reaches the comparison value of 15%, the score is 1 point, when it reaches 25%, the score is 2 points, and when it reaches 35%, the score is 3 points. The stress index (L) is 1 point at 30%, 2 points at 40%, and 3 points at 50%. Respiratory rate (R) is 1 point when it reaches the comparative value of 17.6 times, which is the reference value of 15 plus 2.6 times, 2 points when it reaches 18.7 times, and 3 points when it reaches 20 times. becomes. Then, when the warning score, which is the total of these four types of evaluation points, reaches the first threshold of 9 points, a warning (YA) is issued, and when the second threshold of 11 points, a danger notice (RA) is issued. do.

In order to make more detailed judgments and prevent the manifestation of risks, an emergency notification function may be added to the workload judgment system of FIG. 4 to supplement the warning score algorithm. Regarding the change rate of the moving average value of the core body temperature (C) and the heart rate (H), when the change of the same trend, either increase or decrease, is confirmed continuously for a predetermined number of times, regardless of whether the worker W is aware of it. , assuming a one-way and rapid increase in risk, add points to each evaluation point. In addition, this is remarkable, and when reaching a predetermined number of consecutive times, the danger announcement (RA), which is the second warning, is sent to the gateway terminal 2 and the access terminal 5 regardless of the number of warning points. Run an emergency notification to send. As a specific example, 2 points are added to the evaluation score when there are 2 consecutive movements with the same tendency, either increase or decrease in core body temperature (C) or heart rate (H), 3 points for 3 consecutive, and 4 points for 4 consecutive. In , 4 points are added, and when these become 5 consecutive points, a hazard notice (RA) is issued immediately. Note that the function of monitoring the number of consecutive times has the same meaning as the function of monitoring the continuous time, and the same applies to the exercise intensity algorithm described below and later.
Moreover, one of the activity data acquired by the sensor 1 is posture data indicating whether the worker W is standing or lying down. If this posture data suggests that the worker W is in a continuous recumbent state, for example, if it is estimated that the state of falling will continue beyond the predetermined time of 5 minutes, 5 points are added to the warning points. to make an emergency notification. In addition, regarding the respiratory rate (R), which often shows a stable tendency, when the one-minute moving average value exceeds a predetermined number of times, for example, 25 times, it is assumed that the load on both sides of the mind and body has accumulated. An emergency notification is sent to add 3 points to the evaluation score.

In addition, the comparison value for each evaluation item, which is the condition for adding evaluation points in this item evaluation table, is variable, and is determined based on the data accumulation table shown in Fig. 6 in consideration of the safety margin to be secured. However, it is also possible to appropriately change the setting of these comparison values if necessary.
FIG. 6, which is shown as an example of a data accumulation table, shows changes in core body temperature (C) of a plurality of workers W under severe environmental conditions with a heat index (WBGT value) of 28°C or higher, which increases the risk of developing heatstroke. is displayed graphically. Clockwise from the upper right to the upper left is a periodic time axis from the start to the end of work, and a polygonal line showing the transition of the moving average value of core body temperature (C) of a plurality of workers W is superimposed and plotted. ing. Even under the same conditions, variations in core body temperature (C) vary due to differences in work content and individual differences. It is possible to obtain useful information when considering the safety margin in the workload judgment based on In this system, for each of the core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) evaluation items, the heat index (WBGT value) is less than or above A data collection table is prepared for a number of different work environments, such as below 28° C. as in 6 or above.
Also, for example, a plurality of data accumulation tables corresponding to work contents with different exercise intensities such as 0.8 (80%) and 1.2 (120%) are prepared. In addition, for each individual, the change status of biometric data for each individual, warning data, and report data to be transmitted to the manager M via the server 3 when the worker W becomes aware of an abnormality in his physical condition or when a warning is issued are linked and accumulated for management. In some cases, a data accumulation table is prepared. Depending on the specifications of the application, multiple data accumulation tables are incorporated, and the relationship between the fluctuation status of four types of biometric data, which are evaluation items for workload, and the risk of overload, which is centrally aggregated as warning points. It is used when analyzing the characteristics from various aspects, determining more appropriate point addition conditions, and setting and correcting them.
Then, depending on the specifications of this system, the manager M can select the safety margin presented from the data accumulation table of the server 3, and the rate of change of biometric data, which is the condition for adding evaluation points, that is, the comparison of the item evaluation table The system can be configured to arbitrarily set and change values. For example, for a worker W who is engaged in tough work with high exercise intensity under dangerous work conditions with a high heat index (WBGT value), an optimal data accumulation table can be selected from a predetermined setting screen, and linked to it. It is possible to switch to the appropriate item evaluation table to be used. In addition, as another specification, the relationship between the fluctuation of biometric data and the evaluation points and warning points that are risk-evaluated based on the warning point number algorithm and data accumulation table, based on the large-scale data accumulated in the server 3 It is also conceivable to execute machine learning and automate the setting of the comparison value as the point addition condition.

FIG. 4 also illustrates a mechanism for correcting this in order to improve the accuracy of the warning score algorithm. In order to issue alarms that ensure a more sufficient safety margin, or to suppress the issuance of alarms that are considered excessive compared to the work content, this system judges workload based on exercise intensity during work. is installed as necessary. Based on the maximum heart rate set in advance corresponding to the age of the worker W and the heart rate (H) of the worker W measured by the sensor 1, the exercise intensity of the work is calculated. A predetermined number exceeding 1 when the rate of change of the moving average value per predetermined unit time continues to increase for a predetermined number of times and the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times The evaluation score is multiplied by the correction factor of It is an exercise intensity correction function for ensuring the urgency and necessity of warning issuance, and is called an exercise intensity algorithm in this system.
That is, when the exercise intensity increases during work, generally, the respiration rate (R) of the worker W also tends to increase with the exercise intensity. Conversely, when the exercise intensity increases and the respiratory rate (R) continues to decrease, there is a strong possibility that the body of the worker W cannot adapt to the increase in load due to the exercise intensity, and a score of 1 is given. By multiplying the correction coefficient exceeding the value, there is a meaning of preliminarily issuing an early warning to strengthen the safety protection of the worker W. When the moving average value of the respiratory rate (R) increases as the exercise intensity increases and reaches the comparison value in the item evaluation table, the evaluation points are added according to the normal warning point algorithm. On the other hand, if the rate of change in the moving average value of the respiratory rate (R) fluctuates smoothly in response to the rate of change in exercise intensity, the data fluctuation is within the expected range, and the evaluation point is less than 1. It is conceivable to slow down the acceleration speed by multiplying the coefficient and avoid the frequent occurrence of overly sensitive warning issuances that deviate from the actual work load.
Further, in another specification, in a phase where both the exercise intensity and the respiratory rate (R) tend to rise, activity data indicating that the worker W is lying down or resting is continuously displayed at the same time as these data. If confirmed, the score shall also be multiplied by a correction factor greater than one. Furthermore, an exercise intensity correction function that multiplies the evaluation point by a correction factor greater than 1 is added even when the core body temperature (C) or respiratory rate (R) tends to increase while the exercise intensity tends to decrease.

Accordingly, the workload determination program used in the health care system of the present invention is basically as follows.
First, each time-series data is obtained from four types of biological data regarding core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) of worker W who wears the sensor. There is a first process. Next, there is a second process of obtaining a moving average value for each predetermined unit time from the time-series data. The third process has the following two procedures that are executed synchronously. One is the rate of change obtained by comparing the moving average values of a predetermined time ago and the current time for each core body temperature (C), heart rate (H), and stress index (L), and is evaluated based on the item evaluation table. This is the procedure for converting to The other is a procedure for converting the number of differences obtained by comparing the moving average value of the respiratory rate (R) before a predetermined time with a set reference value into an evaluation score based on an item evaluation table. Furthermore, the warning score obtained by summing the four types of evaluation points related to core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) obtained in the third process exceeds the first threshold. A fourth step of issuing a first alert when and a second alert when the second threshold is exceeded.
Also, depending on the specifications, the workload determination program has the following emergency notification process. Regarding core body temperature (C) and heart rate (H), each evaluation point is added when the rate of change of their moving average values is continuously measured as data that shows the same trend, either increasing or decreasing. I do. The process of issuing a second warning when this number exceeds a predetermined number of times is the fifth process. Further, there is a sixth step of obtaining the posture data of the person wearing the sensor and adding points to the warning points when the posture data indicating the lying state exceeds a predetermined time. Then, there is a seventh step of adding points to the evaluation points when the moving average value of the respiratory rate (R) exceeds a predetermined number of times. These processes are synchronized with the third process and the fourth process and executed concurrently.
Furthermore, this workload determination program analyzes the exercise intensity from the maximum heart rate corresponding to the age of the sensor wearer and the measured heart rate (R), and the rate of change of the moving average value of the exercise intensity tends to increase. a predetermined number of times in succession, and the rate of change of the moving average value of the respiratory rate (R) continues to decrease and continues the same predetermined number of times, the evaluation point is multiplied by a predetermined coefficient exceeding 1. An exercise intensity correction function equipped with an eighth process. Mount.

Finally, we will use the case of the security industry, for which we have conducted demonstration tests, to explain the operation and functions of the app as well as the specific usage of this system. However, since this is an example, the mode of the present system is not limited to this.
Hereinafter, the manager M is the manager, and the worker W is the security guard who wears the sensor 1 .
The manager of the management office manages a large number of security guards and performs various tasks such as management of labor affairs and safety and health. Business communication such as instructions and reports is carried out between the two on a daily basis. I often go straight home from the site.
This system was introduced to support the proper execution of administrative work by the management office director and to optimize the health management of security guards. It will be available at the administration office. Security guards can also make various reports at the site without visiting the management office.

In order to optimize the system for the company's business, the management office manager performs initial settings for the system as necessary. The management office manager activates a browser on the access terminal 5 connected to the Internet, displays the login screen of this system, and logs in by entering an ID and a password. After logging in, a home screen as shown in FIG. 7 is displayed, and the status of "work information", "warning" (displayed as "alarm" in FIG. 7), and "emergency call" can be confirmed.
At the top of the home screen, there is a home button (shown as "Coat" in Fig. 7) and multiple pull-down menus. Select the necessary management menu from the master maintenance menu to perform initial system settings. be able to.
The management center manager performs user registration using the user management menu shown in FIG. etc. can be set. The management office manager further sets the identification code, address, etc. of the work site using the work place management menu shown in FIG. 9, and uses the work content management menu shown in FIG. You will set the contents and their identification code. These tasks may also be associated with data aggregation tables and intensity algorithms. In the measurement parameter management menu of FIG. 11, for example, in order to improve the biometric data acquisition accuracy of the sensor 1, it is possible to set a correction coefficient or the like corresponding to the body type of the security guard. In the attendance setting menu shown in FIG. 12, it is possible to set a form such as a work schedule, daily work hours, break times, and the like. In the mail setting menu of FIG. 13, the contact information such as the telephone numbers of the management office manager and security guards, and the e-mail addresses for sending warning data from the server 3 to the terminals of both parties are set.
The initial settings are completed as described above, but it is possible to confirm these contents in a list or the like, and it is also possible to change or delete the setting contents.

A security guard who arrives at the site wears the sensor 1 in close contact with his or her chest using a fixing device for wearing before engaging in work. By tapping the icon of the gateway terminal 2 to start the application and entering the ID and password from the login screen, the login to the system is completed. Since the work start screen as shown in FIG. 14 is displayed on the gateway terminal 2, the guard inputs work data and report data. The work data here consists of the "start time" of the work, the name of the municipality and site where the work is to be selected from the parts displayed as "work place" and "work content", and the work content there. be. These are the ones registered in the initial settings earlier, and the security guard selects the appropriate one from among them. The report data is selected by tapping one of the five icons to the right of the "physical condition" that corresponds to one's own physical condition at the start of work. Note that the icons in FIG. 14 are displayed in five stages from left to right: "very good, good, average, not very good, not good".
By these initial operations of the gateway terminal 2, the sensor 1 and the gateway terminal 2 are automatically paired to enable data communication. At the same time, along with the biometric data acquired by the sensor 1 and continuously transmitted, the work data indicating the work start time, work location, and work content, and report data regarding physical condition are also transmitted from the gateway terminal 2 to the server 3. be done.

Security guards carry out traffic control and security patrols while wearing the sensor 1 . During breaks, the gateway terminal 2 can be operated to temporarily cancel data communication with the system. When resuming the work after the interruption, the security guard pairs the sensor 1 and the gateway terminal 2 again and inputs working data for resuming the work.
In general, biometric data immediately after the start of work is often unstable with a wide range of fluctuations. However, within a short period of time after the start of work, the physical and mental condition of the security guard begins to settle down, and the numerical values of the biometric data transmitted from the sensor 1 also stabilize. As a guideline, it is obtained from the result of the demonstration experiment that about 10 to 20 minutes have passed since the start of work. In addition, the data accumulation table, in which a large amount of data is accumulated by individual, work environment, and content, makes it possible to estimate the transitional tendency of biometric data under multiple different conditions and repeated time axes. Therefore, the accuracy of evaluating newly acquired biometric data will also improve over time.

The biological data of the security guard acquired by the sensor 1 is transmitted to the gateway terminal 2 by wireless communication. The biometric data at this time includes body surface temperature, core body temperature (C), electrocardiogram, heart rate (H), stress index (L), respiration rate (R), and the like. Along with the biological data, environmental data such as environmental temperature and relative humidity, and activity data such as the number of steps taken and living habits are acquired by the sensor 1 and transmitted to the gateway terminal 2 . A security guard who is working can check them from the work screen of the gateway terminal 2. - 特許庁In the center of the screen in FIG. 15, the warning points sent from the server 3 and the corresponding workload judgment results (“Safe”, “Caution”, “Warning”) are displayed. In this example, the warning points are 6. Because of the dot, the mark to its left is "safe". Below that, the latest heart rate (H) and core body temperature (C) values transmitted from the sensor 1 are displayed. If you tap the underlined "graph display" part in the heart rate (H) and core body temperature (C) display parts, the screen will switch to a screen as shown in FIG. Is displayed. In the upper portion of the screen in FIG. 15, the communication status with the sensor 1 and the remaining battery level can also be checked. The display of "Measuring" on the upper left side indicates the communication status with the sensor 1, etc., and the battery type icon on the upper right side indicates the remaining battery level of the sensor 1. FIG.
When a security guard issues a warning or feels unwell, the report menu (“relief request” (×), “work interruption” (△), “work From "Continue" (o)), the user can select one that is suitable for his or her condition, and can transmit the report data for the report or request to the management center manager via the server 3 . These report data are managed in association with the data accumulation table of the server 3, for example, by digitizing a relief request as "3" and continuing work as "1".

The data acquired by the sensor 1 and transmitted to the gateway terminal 2 and the data input from the gateway terminal 2 are transmitted from the gateway terminal 2 to the server 3, which is always in operation in many cases, and the workload is reduced by the warning score algorithm. Analysis processing such as determination is executed. At this time, the security guard's location information obtained by the acceleration sensor of the sensor 1 and the position information of the work site obtained by the GPS of the gateway terminal 2 are also transmitted. In addition, by receiving work data, it is possible to immediately confirm the arrival of security guards on site and the start of work.
The manager can access the system at any time in the same way as during the initial setting. This may be done each time the daily work is started, or may be always connected. Immediately after the access, the access terminal 5 is used to check whether there are any abnormalities in the system operating conditions such as data acquisition and communication, and in the biometric data of the security guard. If there is no abnormality, then the access terminal 5 can be checked as needed, and there is no need to constantly watch it.

After the management office manager has logged in, at the top of the home screen in FIG. 7 displayed on the screen of the access terminal 5, the home button, work viewer, work management, and master maintenance menu display can be confirmed from the left.
From the pull-down menu of the work viewer, it is possible to check the warning sent from the server 3 and the content of the emergency call, which is one of the report data sent from the gateway terminal 2 . These can also be confirmed from the links on both the "warning" and "emergency call" panels displayed at the bottom of the home screen. The "Work Information" panel displays the number of security guards working, and the "Warning" and "Emergency Call" panels display the number of unconfirmed cases with the number of those cases. At this time, measures such as blinking the number of unconfirmed cases are devised so that the management station manager can recognize the warning issuance without delay. Then, when the management office manager accesses the alarm confirmation screen, a list of worker names, contact addresses, alarm types, and confirmers for each occurrence time is displayed as shown in FIG. Similarly, on the emergency call confirmation screen, a list of senders, contacts, contents, and confirmers for each transmission time is displayed.

If you directly click the "Work Viewer" menu at the top of the home screen or click the "To Work Viewer" link in the "Work Information" panel, you can see the work status of multiple security guards on a map as shown in Figure 18. A working viewer for instant comprehension is displayed. The number of unconfirmed emergency calls and warnings is displayed in the upper left part of the screen, allowing the manager to quickly recognize anomalies in security guards. Below that, a list of security guards is displayed on the left side of the screen, and worker tabs for individual security guards are displayed on the map on the right side.
The worker list on the left shows the worker name, core body temperature (C), heart rate (H), work start and work end, etc. Click the worker tab displayed on the right side of the worker list. , the map display on the right side of the screen switches to a map display centered on the work site where the guard is working. When the sensor tab displayed on the right side of the worker tab is clicked, a sensor information screen is displayed, as shown in FIG. This screen displays data such as date of work, name of worker, contact information, place of work, working time, content of work, physical condition, and the like. In addition, sensor 1 such as body temperature data (surface body temperature and core body temperature (C)), environmental data (environmental temperature, relative humidity), stress index (L), respiratory rate (R), heart rate (H), etc. The acquired biometric data can be confirmed by display in a graph format or a list format.
In addition, in the sensor information screen of FIG. 19, the graph display below the body temperature data is omitted, but the graph display of biological data such as the heart rate (H) follows. Further below the plurality of graph displays, a list display screen such as that shown in FIG. 20 continues, on which the biometric data, which are also made into one-minute moving average values, can be listed in chronological order. The information displayed in FIG. 20 includes the data transmission time, the number of warning points, the exercise intensity, the habitual information for estimating a fall, the core body temperature (C), the heart rate (H), the stress index (L), and the respiration rate. The number (R), the number of steps, the surface temperature, the environmental temperature, the relative humidity, and the breakdown of the evaluation score (C/H/L/R).

When a warning is issued from the server 3, the manager of the management center can immediately know that the warning has been issued by blinking the screen, beeping sound, or the like on the home screen of the access terminal 5 that has received the warning. At this time, the security guard at the work site receives the warning from the server 3 at the gateway terminal 2 at almost the same time, and quickly recognizes the issuance of the warning by means of a warning sound or the like. At this time, the management center manager and the guards will check and contact each other, but the guards can report on the response to the warning issuance by tapping the "physical condition report" banner at the bottom right of the screen of the gateway terminal 2. Data can be sent to the management center manager via the server 3 . The report can be made by selecting an appropriate one from the display of the report menu (“relief request” (×), “work interruption” (△), “work continuation” (〇)), and the request can be made only by touching the screen. and reports can be made promptly, and responses such as work stoppages and temporary suspensions can be discussed. Also, when a warning is issued, a pop-up display prompting the security guard to confirm and respond may be displayed on the screen of the gateway terminal 2, and the warning sound may stop when the security guard responds to the pop-up display.
On the other hand, when the security work for the day is completed without interruption of work due to such a warning issuance, the security guard taps the work end banner at the bottom left of the screen. After that, the work data for transmitting the work end time is transmitted to the server 3, the fact is recorded in the work schedule, and the manager can confirm the work completion of the security guard. The guard removes the sensor 1 and powers off the gateway terminal 2 before leaving the work site. On the other hand, when the management center manager logs out after the work is completed, he can select logout from the pull-down menu on the right side of the user status display (user: system administrator) displayed on the right end of the home screen in FIG. can.

As explained so far, the use of this system makes it possible to quickly and effectively reduce health risks such as heatstroke at harsh work sites, and to realize a better occupational safety and health environment. In addition, by managing the working status and health status of security guards together, it is possible to reduce the burden of complicated administrative procedures such as reports and document preparation between the manager and the security guards.
Various data such as security guard biometric data, report data, activity data, work data, work site environment data, and report data when a warning is issued or when a person is in poor physical condition are collectively managed in this system.
FIG. 21 shows a management screen displayed when the work management menu is clicked on the home screen. The operator code, operator name, age, and measurement parameters of the selected security guard are displayed on the left side of the screen. Another security guard to be confirmed can be selected from the pull-down display section of "select worker" below. On the right side thereof, the security guard's work location, start time, end time, work confirmation, construction number, etc. are displayed for each date. Further, when the sensor information tab on the right is clicked, the sensor information of the security guard on that day is displayed as shown in FIGS. On this management screen, security guard work management and health management are centrally integrated, and by clicking the roster table tab, it is also possible to output the forms necessary for labor management and occupational health and safety management. An example of the report form output in this way is the work schedule in FIG.
In addition, by executing machine learning based on the large-scale data accumulated in the data accumulation table of the server 3, the accuracy of the workload judgment function of this system regarding newly acquired biometric data is improved over time. will be

1 sensor 2 gateway terminal 3 server 4 information visualization system 5 access terminal M administrator W worker

Claims (13)

A health management system in which a sensor, a gateway terminal, and a server cooperate with application software,
The sensor acquires biological data related to the core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) of the sensor wearer over time and transmits the biological data to the gateway terminal;
The gateway terminal transmits to the server a moving average value per predetermined unit time obtained by analyzing the time-series data of the biometric data and the employment data input from the gateway terminal by the sensor wearer,
The server manages the moving average value and the employment data in association with the identification code (ID) of the sensor wearer, and provides them so that they can be queried on a web page accessible by a system user using an access terminal. death,
The application software comprises an item rating table defining comparative values for determining scores for core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R); ), for each heart rate (H) and stress index (L), the rate of change obtained by comparing the moving average values of a predetermined time ago and the current time is obtained by converting based on the comparison values, and breathing rate (R) Core body temperature (C), heart rate (H), stress index (L), and respiratory rate obtained by converting the number of differences obtained by comparing the moving average value before a predetermined time and the set reference value based on the comparison values. When the warning score obtained by summing the evaluation points related to (R) exceeds the first threshold, the first warning data is generated, and when the second threshold is exceeded, the second warning data is generated. A health management system comprising a workload determination function that transmits data to the gateway terminal associated with a code (ID). 2. The application software has a data accumulation table for accumulating the moving average values and determining the comparison values, and the comparison values defined in the item evaluation table can be changed. The health management system described in . The application software adds points to the evaluation score when the rate of change comparing the moving average values of core body temperature (C) and heart rate (H) continues in the same trend, either increasing or decreasing, and The second warning data is transmitted to the gateway terminal linked to the access terminal and the identification code (ID) when the second warning data continues exceeding a predetermined number of times, and the posture data obtained from the sensor wearer is An emergency notification function is provided for adding points to the warning points when the recumbent state exceeds a predetermined time, and adding points to the evaluation points when the moving average value of the respiratory rate (R) exceeds a predetermined number of times. 3. A health care system according to claim 1 or claim 2. The application software obtains the exercise intensity from the maximum heart rate and the heart rate (H) set corresponding to the age of the sensor wearer, and the rate of change of the moving average value of the exercise intensity per predetermined unit time is An exercise intensity correction function that multiplies the evaluation score by a predetermined coefficient exceeding 1 when the rate of change of the moving average value of the respiratory rate (R) continues to increase for a predetermined number of consecutive times and the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times. 3. The health care system according to claim 1, comprising: A health management system in which a sensor, a gateway terminal, a server, and an information visualization system cooperate by application software,
The sensor acquires biological data related to the core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) of the sensor wearer over time and transmits the biological data to the gateway terminal;
The gateway terminal transmits to the server a moving average value per predetermined unit time obtained by analyzing the time-series data of the biometric data and the employment data input from the gateway terminal by the sensor wearer,
The server manages the moving average value and the employment data in association with the identification code (ID) of the sensor wearer,
The information visualization system provides the moving average value and the working data for each sensor wearer in a work viewer displayed on a map on a web page that can be accessed by a system user using an access terminal. ,
The application software comprises an item rating table defining comparative values for determining scores for core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R); ), for each heart rate (H) and stress index (L), the rate of change obtained by comparing the moving average values of a predetermined time ago and the current time is obtained by converting based on the comparison values, and breathing rate (R) Core body temperature (C), heart rate (H), stress index (L), and respiratory rate obtained by converting the number of differences obtained by comparing the moving average value before a predetermined time and the set reference value based on the comparison values. When the warning score obtained by summing the evaluation points related to (R) exceeds the first threshold, the first warning data is generated, and when the second threshold is exceeded, the second warning data is generated. A health management system comprising a workload determination function that transmits data to the gateway terminal associated with a code (ID). 6. The application software accumulates the moving average values and includes a data accumulation table for determining the comparison value, and the comparison value defined in the item evaluation table can be changed. The health management system described in . The application software adds points to the evaluation score when the rate of change comparing the moving average values of core body temperature (C) and heart rate (H) continues in the same trend, either increasing or decreasing, and The second warning data is transmitted to the gateway terminal linked to the access terminal and the identification code (ID) when the second warning data continues exceeding a predetermined number of times, and the posture data obtained from the sensor wearer is An emergency notification function is provided for adding points to the warning points when the recumbent state exceeds a predetermined time, and adding points to the evaluation points when the moving average value of the respiratory rate (R) exceeds a predetermined number of times. 7. A health care system according to claim 5 or claim 6. The application software obtains the exercise intensity from the maximum heart rate and the heart rate (H) set corresponding to the age of the sensor wearer, and the rate of change of the moving average value of the exercise intensity per predetermined unit time is An exercise intensity correction function that multiplies the evaluation score by a predetermined coefficient exceeding 1 when the rate of change of the moving average value of the respiratory rate (R) continues to increase for a predetermined number of consecutive times and the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times. 7. The health care system according to claim 5 or 6, comprising: Equipped with an item evaluation table defining comparative values for determining evaluation points for core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R), the core body temperature (C) of the sensor wearer , a first step of acquiring biological data relating to heart rate (H), stress index (L), and respiratory rate (R) over time to obtain time-series data; and analyzing the time-series data for a predetermined unit time. a second step of obtaining a moving average value per hour, and comparing the rate of change of comparing the moving average values of a predetermined time ago and the current time for each core body temperature (C), heart rate (H), and stress index (L); value, and the number of differences obtained by comparing the moving average value of the respiratory rate (R) before a predetermined time and the set reference value is converted based on the comparison value, core body temperature (C), heart rate (H) a third step of obtaining the evaluation points relating to the stress index (L) and the respiratory rate (R); and issuing a first warning when the total warning score of the evaluation points exceeds a first threshold; and a fourth step of issuing a second warning when the second threshold is exceeded. When the rate of change comparing the moving average values of core body temperature (C) and heart rate (H) continues in the same trend, either increasing or decreasing, points are added to the evaluation point, and the number of times exceeds a predetermined number of times. a fifth step of issuing the second warning when continuous, a sixth step of adding points to the warning points when the posture data obtained from the sensor wearer indicates a recumbent state exceeding a predetermined time, and a respiratory rate. 10. The workload determination program for a health management system according to claim 9, further comprising a seventh step of adding points to said evaluation points when said moving average value of (R) exceeds a predetermined number of times. The exercise intensity is obtained from the maximum heart rate and the heart rate (H) set corresponding to the age of the sensor wearer, and the rate of change of the moving average value of the exercise intensity per predetermined unit time tends to increase for a predetermined number of times. an eighth step of performing exercise intensity correction by multiplying the evaluation score by a predetermined coefficient exceeding 1 when the rate of change of the moving average value of the respiratory rate (R) continues to decrease for the same predetermined number of times consecutively; 11. A workload determination program for a health care system according to claim 9 or 10, characterized by comprising: A data structure for a health management system, an item rating table defining comparative values for determining scores for core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R) prepared,
Identification code (ID) of the sensor wearer, time-series data of biological data related to core body temperature (C), heart rate (H), stress index (L), and respiratory rate (R), and obtained by analyzing these including a moving average value per predetermined unit time,
A rate of change obtained by comparing the moving average values of a predetermined time ago and the current time for each core body temperature (C), heart rate (H), and stress index (L) is obtained by converting based on the comparison values, and breathing rate Core body temperature (C), heart rate (H), stress index (L), obtained by converting the number of differences in comparison between the moving average value and the set reference value a predetermined time before (R) based on the comparison values. ) and respiratory rate (R), the first warning data when the sum of the evaluation points exceeds the first threshold, the second warning data when the second threshold is exceeded, and the access terminal and a data structure for a health care system, which is used in a workload determination program that is transmitted to a gateway terminal associated with the identification code (ID). A data structure for a healthcare system, comprising:
13. A data structure for a health care system according to claim 12, comprising said first warning data and said second warning data associated with said identification code (ID).

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