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

Worawat Lawanont, Masahiro Inoue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationInternational Conference on Electronics, Information and Communication, ICEIC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
Volume2018-January
ISBN (Electronic)9781538647547
DOIs
Publication statusPublished - 2018 Apr 2
Event17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States
Duration: 2018 Jan 242018 Jan 27

Other

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

Fingerprint

Unsupervised learning
Health

Keywords

  • Monitoring System
  • Perceived Stress
  • Unsupervised Learning
  • Working Behavior

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Lawanont, W., & Inoue, M. (2018). An unsupervised learning method for perceived stress level recognition based on office working behavior. In International Conference on Electronics, Information and Communication, ICEIC 2018 (Vol. 2018-January, pp. 1-4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ELINFOCOM.2018.8330700

An unsupervised learning method for perceived stress level recognition based on office working behavior. / Lawanont, Worawat; Inoue, Masahiro.

International Conference on Electronics, Information and Communication, ICEIC 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lawanont, W & Inoue, M 2018, An unsupervised learning method for perceived stress level recognition based on office working behavior. in International Conference on Electronics, Information and Communication, ICEIC 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 17th International Conference on Electronics, Information and Communication, ICEIC 2018, Honolulu, United States, 18/1/24. https://doi.org/10.23919/ELINFOCOM.2018.8330700
Lawanont W, Inoue M. An unsupervised learning method for perceived stress level recognition based on office working behavior. In International Conference on Electronics, Information and Communication, ICEIC 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4 https://doi.org/10.23919/ELINFOCOM.2018.8330700
Lawanont, Worawat ; Inoue, Masahiro. / An unsupervised learning method for perceived stress level recognition based on office working behavior. International Conference on Electronics, Information and Communication, ICEIC 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-4
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