An interpretable machine learning approach to multimodal stress detection in a simulated office environment.

Journal: Journal of biomedical informatics
Published Date: Jan 30, 2023

Abstract

BACKGROUND AND OBJECTIVE: Work-related stress affects a large part of today's workforce and is known to have detrimental effects on physical and mental health. Continuous and unobtrusive stress detection may help prevent and reduce stress by providing personalised feedback and allowing for the development of just-in-time adaptive health interventions for stress management. Previous studies on stress detection in work environments have often struggled to adequately reflect real-world conditions in controlled laboratory experiments. To close this gap, in this paper, we present a machine learning methodology for stress detection based on multimodal data collected from unobtrusive sources in an experiment simulating a realistic group office environment (N=90).

Authors

  • Mara Naegelin
    Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Chair of Technology Marketing, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland. Electronic address: mnaegelin@ethz.ch.
  • Raphael P Weibel
    Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Chair of Technology Marketing, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland.
  • Jasmine I Kerr
    Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Chair of Technology Marketing, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland.
  • Victor R Schinazi
    Department of Psychology, Bond University, 14 University Drive, Robina, 4226, Australia; Future Health Technologies, Singapore-ETH Centre, 1 Create Way, Singapore, 138602, Singapore.
  • Roberto La Marca
    Centre for Stress-Related Disorders, Clinica Holistica Engiadina, Plaz 40, Susch, 7542, Switzerland; Chair of Clinical Psychology and Psychotherapy, Department of Psychology, University of Zurich, Binzmuehlestrasse 14, Zurich, 8050, Switzerland.
  • Florian von Wangenheim
    Chair of Technology Marketing, Department of Management, Economics, and Technology, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8092, Switzerland; Future Health Technologies, Singapore-ETH Centre, 1 Create Way, Singapore, 138602, Singapore.
  • Christoph Hoelscher
    Future Health Technologies, Singapore-ETH Centre, 1 Create Way, Singapore, 138602, Singapore; Chair of Cognitive Science, Department of Humanities, Social and Political Sciences, ETH Zurich, Clausiusstrasse 59, Zurich, 8092, Switzerland.
  • Andrea Ferrario
    ETH Zurich, Zurich, Switzerland.

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