Kyutacarは九州工業大学で生産された研究成果を オープンアクセスで提供する機関リポジトリシステムです。 Kyutacar is open-access repository of research by members of the Kyushu Institute of Technology.
Kyushu Institute of Technology
Kyushu Institute of Technology
Rice University
NTT Data Institute of Management Consulting, Inc.
Kyushu University
Kyushu Institute of Technology
抄録
In recent years, many organizations have prioritized efforts to detect and treat mental health issues. In particular, office workers are affected by many stressors, and physical and mental exhaustion, which is also a social problem. To improve the psychological situation in the workplace, we need to clarify the cause. In this paper, we conducted a 14-day experiment to collect wristband sensor data as well as behavioral and psychological questionnaire data from about 100 office workers. We developed machine learning models to predict psychological indexes using the data. In addition, we analyzed the correlation between behavior (work content and work environment) and psychological state of office workers to reveal the relationship between their work content, work environment, and behavior. As a result, we showed that multiple psychological indicators of office workers can be predicted with more than 80% accuracy using wearable sensors, behavioral data, and weather data. Furthermore, we found that in the working environment, the time spent in “web conferencing”, “working at home (living room)”, and “break time (work time)’ had a significant effect on the psychological state of office workers.
内容記述
3rd International Conference on Activity and Behavior Computing, ABC 2021, 22 October 2021 through 23 October 2021, Online
雑誌名
Smart Innovation, Systems and Technologies
巻
291
ページ
1 - 26
発行年
2022-05-04
出版者
Springer
ISSN
2190-3026
2190-3018
ISBN
978-981-19-0360-1
978-981-19-0361-8
DOI
https://doi.org/10.1007/978-981-19-0361-8_1
権利
Copyright (c) 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. This is a post-peer-review, pre-copyedit version of an article published in Smart Innovation, Systems and Technologies. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-19-0361-8_1
Toward the Analysis of Office Workers’ Mental Indicators Based on Wearable, Work Activity, and Weather Data
LaSEINE-2021_060.pdf
(989.85KB)
