KR-102962567-B1 - METHOD FOR ANALIZING MENTAL HEALTH BASED ON MULTI-SOURCE DATA FUSION

KR102962567B1KR 102962567 B1KR102962567 B1KR 102962567B1KR-102962567-B1

Abstract

A mental health analysis method of a mental health management server for analyzing and managing stress of a worker according to an embodiment of the present disclosure comprises: collecting multi-source data including survey information, biosignal information, schedule information, type of work, work environment information, work duration information, equipment usage time information, and periodic stress survey information for the worker; calculating a static mental health index from the survey information; calculating a dynamic mental health index based on the biosignal information, work duration information, equipment usage time information, work environment information, and periodic stress survey information; calculating a workload mental health index from the schedule information and the type of work; and generating a mental health index of the worker by combining the static mental health index, the dynamic mental health index, and the workload mental health index.

Inventors

김현숙
김민정
김정숙
박경현
윤대섭

Assignees

한국전자통신연구원

Dates

Publication Date: 20260511
Application Date: 20210115

Claims (10)

Regarding the mental health analysis method of a mental health management server for analyzing and managing worker stress: A step of collecting multi-source data including survey information, biosignal information, schedule information, type of work, work environment information, work duration information, equipment usage time information, and periodic stress survey information regarding the above-mentioned worker; A step of calculating a static mental health index based on the above survey information; A step of calculating a dynamic mental health index based on the above-mentioned biosignal information, work duration information, equipment usage time information, work environment information, and periodic stress survey information; A step of calculating a workload mental health index based on the above schedule information and the above type of work; and An analysis method comprising the step of generating a mental health index of the worker based on the static mental health index, the dynamic mental health index, and the workload mental health index.
In Article 1, The above survey information is an analysis method comprising at least one of the above worker's profile information, information on stress types, information on socio-psychological stress, and information on job stress.
In Article 2, The above static mental health index is an analysis method calculated by reflecting weights to stress information associated with an individual's profile, weekly stress information, and daily stress information, respectively.
In Article 1, The above dynamic mental health index is an analysis method calculated by reflecting weights to each of the biosignal-based stress information, work duration-based stress information, equipment usage time-based stress information, work environment-based stress information, and subjective stress survey information.
In Article 1, The above-mentioned workload mental health index is an analysis method calculated by reflecting weights to stress information based on business schedules and stress information based on work types, respectively.
In Article 1, The mental health index of the above-mentioned worker is an analysis method generated by reflecting weights to each of the static mental health index, the dynamic mental health index, and the workload mental health index.
In paragraph 1, The above periodic stress survey information is an analysis method comprising information obtained by conducting a survey over a 12-day period at time units set by the worker regarding at least one of the causes of stress currently felt by the worker, the degree of stress currently felt, the level of fatigue currently felt, opinions on rest currently felt, and the type of work currently performed.
A user terminal configured for use by a worker for work; A sensor configured to detect information about the above-mentioned worker; A network configured to receive multi-source data including survey information, biosignal information, schedule information, type of work, work environment information, work duration information, equipment usage time information, and periodic stress survey information regarding the worker from at least one of the user terminal, the sensor, and the work server, and to transmit the received multi-source data to a mental health management server; and A mental health management server configured to calculate a static mental health index based on the survey information regarding the worker, calculate a dynamic mental health index based on the biosignal information, the work duration information, the equipment usage time information, the work environment information, and the periodic stress survey information, calculate a workload mental health index based on the schedule information and the type of work, and generate a mental health index of the worker based on the static mental health index, the dynamic mental health index, and the workload mental health index. The above survey information regarding the above worker is a mental health management system including stress information associated with an individual's profile, weekly stress information, and daily stress information.
In Article 8, The above user terminal is a mental health management system comprising a user interface, a processor, a communication unit, and storage.
In Paragraph 8, A mental health management system in which the mental health index of the above-mentioned worker is generated by reflecting weights to each of the static mental health index, the dynamic mental health index, and the workload mental health index.

Description

Method for Analyzing Mental Health Based on Multi-Source Data Fusion The present disclosure relates to a method for analyzing the mental health of workers, and to a method and algorithm for generating a mental health index using multi-source data that affects mental health. While appropriate levels of stress in the course of performing work life can be effective in increasing productivity by fostering engagement and satisfaction, excessive stress can lead to a painful work life and cause fatigue, decreased productivity, or even illness. Exhaustion or burnout caused by workplace stress and excessive workload poses a high risk of leading to depression in workers. Furthermore, it is highly likely to result in various ailments such as chronic fatigue, shoulder pain, headaches, forward head posture, back disorders including herniated discs, and indigestion. Consequently, not only is there a loss of human resources, but medical costs and related insurance payouts are also increasing, leading to growing economic and industrial losses. Work environments, assignments, and schedules vary individually among employees. Therefore, managing stressors for employees and providing individuals with continuous and long-term mental health measurements and stress information within their personal workspaces can help improve job satisfaction, productivity, and health. Various technologies have been proposed to analyze or evaluate such worker stress. However, there is still an urgent need for mental health management technologies that comprehensively consider various information, such as the work environment and schedule, which directly or indirectly affect worker stress. FIG. 1 is a block diagram showing a mental health management system according to an embodiment of the present disclosure. FIG. 2 is a block diagram illustrating an exemplary user terminal of the present disclosure. FIG. 3 is a block diagram briefly showing the configuration and functions of the mental health management server illustrated in FIG. 1. Figure 4 is a table that exemplarily shows the periodic stress survey data illustrated in Figure 3. FIG. 5 is a diagram sequentially showing a procedure for calculating a worker mental health index according to an embodiment of the present disclosure. FIG. 6 is a diagram illustrating an exemplary method of providing feedback to a worker by the mental health management system of the present disclosure. FIG. 7 is a flowchart illustrating, exemplarily, the operation method of the mental health management system of the present disclosure. It should be understood that both the foregoing general description and the following detailed description are exemplary and should be considered as providing additional description of the claimed invention. Reference numerals are detailed in the preferred embodiments of the present disclosure, and examples thereof are shown in the reference drawings. Where possible, the same reference numerals are used in the description and drawings to refer to the same or similar parts. Hereinafter, embodiments of the present disclosure are described with reference to the accompanying drawings so that those skilled in the art may easily practice the technical concept of the present invention. FIG. 1 is a block diagram showing a mental health management system according to an embodiment of the present disclosure. Referring to FIG. 1, the mental health management system (1000) includes a user terminal (1100), a sensor (1200), a network (1300), and a mental health management server (1400). The user terminal (1100) can receive survey information from the user during work progress by the worker, or periodically or at specific times. The survey information entered by the worker will be transmitted to the mental health management server (1400) via the network (1300). Through the user terminal (1100), the worker can respond to periodic stress surveys conducted periodically, such as on a daily, weekly, or monthly basis. Alternatively, through the user terminal (1100), the worker can input information related to a demographic personal profile, socio-psychological stress survey information, job stress survey information, etc. The survey content answered by the worker can be stored in the database of the mental health management server (1400). The user terminal (1100) may be a computer or communication terminal used by the worker for work. The sensor (1200) detects the overall environment of the workplace where the worker is working and transmits the detected data to the mental health management server (1400) periodically or when a specific event occurs. The sensor (1200) may include, for example, a sensor that detects the color or illuminance of the workplace lighting, a temperature sensor that detects the temperature of the workplace, and a humidity sensor that detects the humidity of the workplace. In addition, the sensor (1200) may include an air quality sensor that detects the concentration of pollutants or