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학술대회 A Study on the Subjective Questionnaire-based Stress Assessment using k-means Clustering
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김현숙, 김민정, 김정숙, 박경현, 윤대섭, 조정희
International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.2131-2133
22PR3300, 지식근로자 대상 인공지능 기반 멘탈 웰빙/헬스 관리 솔루션 개발, 김현숙
The aim of this study is to find out whether stress and non-stress can be distinguished by boldsymbol{k}-means clustering method using subjective questionnaire information collected periodically while working at the workplace. The stress of workers increases not only human losses but also economic and industrial losses of the country. We built an experimental environment that collects questionnaires, bio-signals, environment, and schedule information in order to study a system that measures mental health at work and provides solutions for mental wellbeing during times of stress. We were able to determine whether or not they were stressed while working by performing boldsymbol{k}-means clustering using the participants' daily survey information. We propose that the clustering result using the subjective questionnaire can be used as label information for classifying the bio-signal data collected at work into a stress state and a non-stress state.
KSP 제안 키워드
Clustering method, Data collected, Label information, Mental wellbeing, Stress state, bio-signal, k-Means Clustering, mental health, stress assessment