An unsupervised learning method for perceived stress level recognition based on office working behavior

Worawat Lawanont, Masahiro Inoue

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

The health issues in office workers regarding of working environment and working behavior have raised many concerns, both in medical field and technological field. For medical field, the concerns were related to physical injuries and stress due to either bad environment or bad working behaviors. In technological field, the main concern was to find a proper solution to prevent and raise awareness to these issues. In this paper, we discussed the possibility of using unsupervised learning for clustering office working behavior to show the relationship of the working behavior and stress level. We used the data collected from the device which include both behavior data and environment data. The results successfully demonstrated the two clusters that represents the working behavior related to either high or low stress level. The results can be used further to develop a classification model and to raise awareness in office workers.

本文言語English
ホスト出版物のタイトルInternational Conference on Electronics, Information and Communication, ICEIC 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1-4
ページ数4
ISBN(電子版)9781538647547
DOI
出版ステータスPublished - 2018 4月 2
イベント17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States
継続期間: 2018 1月 242018 1月 27

出版物シリーズ

名前International Conference on Electronics, Information and Communication, ICEIC 2018
2018-January

Other

Other17th International Conference on Electronics, Information and Communication, ICEIC 2018
国/地域United States
CityHonolulu
Period18/1/2418/1/27

ASJC Scopus subject areas

  • 情報システム
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 信号処理
  • 電子工学および電気工学

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