An Unobtrusive Stress Recognition System for the Smart Office

Bin Yu, Biyong Zhang, Pengcheng An, Lisheng Xu, Mengru Xue, Jun Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

This paper presents a novel approach to monitor office workers' behavioral patterns and heart rate variability. We integrated an EMFi sensor into a chair to measure the pressure changes caused by a user's body movements and heartbeat. Then, we employed machine learning methods to develop a classification model through which different work behaviors (body moving, typing, talking and browsing) could be recognized from the sensor data. Subsequently, we developed a BCG processing method to process the data recognized as 'browsing' and further calculate heart rate variability. The results show that the developed model achieved classification accuracies of up to 91% and the HRV could be calculated effectively with an average error of 5.77ms. By combining these behavioral and physiological measures, the proposed approach portrays work-related stress in a more comprehensive manner and could contribute an unobtrusive early stress detection system for future smart offices.

Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers
Pages1326-1329
Number of pages4
ISBN (Electronic)9781538613115
DOIs
Publication statusPublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
- City Cube Berlin, Berlin, Germany
Duration: 23 Jul 201927 Jul 2019
https://embc.embs.org/2019/

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
Abbreviated titleEMBC 2019
Country/TerritoryGermany
CityBerlin
Period23/07/1927/07/19
Internet address

Keywords

  • Algorithms
  • Heart Rate
  • Humans
  • Monitoring, Physiologic
  • Movement
  • Pressure

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