Detecting moments of stress from measurements of wearable physiological sensors

Research output: Contribution to journalArticle

Authors

  • Bernd Resch
  • Kalliopi Kyriakou
  • Gunther Sagl
  • Andreas Petutschnig
  • Christian Werner
  • David Niederseer
  • Michael Liedlgruber
  • Frank Wilhelm
  • tess osborne

Colleges, School and Institutes

External organisations

  • University of Salzburg
  • Harvard University
  • University Hospital of Zurich
  • university of groningen

Abstract

There is a rich repertoire of methods for stress detection using various physiological signals and algorithms. However, there is still a gap in research efforts moving from laboratory studies to real-world settings. A small number of research has verified when a physiological response is a reaction to an extrinsic stimulus of the participant’s environment in real-world settings. Typically, physiological signals are correlated with the spatial characteristics of the physical environment, supported by video records or interviews. The present research aims to bridge the gap between laboratory settings and real-world field studies by introducing a new algorithm that leverages the capabilities of wearable physiological sensors to detect moments of stress (MOS). We propose a rule-based algorithm based on galvanic skin response and skin temperature, combing empirical findings with expert knowledge to ensure transferability between laboratory settings and real-world field studies. To verify our algorithm, we carried out a laboratory experiment to create a “gold standard” of physiological responses to stressors. We validated the algorithm in real-world field studies using a mixed-method approach by spatially correlating the participant’s perceived stress, geo-located questionnaires, and the corresponding real-world situation from the video. Results show that the algorithm detects MOS with 84% accuracy, showing high correlations between measured (by wearable sensors), reported (by questionnaires and eDiary entries), and recorded (by video) stress events. The urban stressors that were identified in the real-world studies originate from traffic congestion, dangerous driving situations, and crowded areas such as tourist attractions. The presented research can enhance stress detection in real life and may thus foster a better understanding of circumstances that bring about physiological stress in humans.

Details

Original languageEnglish
Article number3805
Number of pages26
JournalSensors
Volume19
Issue number17
Publication statusPublished - 3 Sep 2019

Keywords

  • stress detection, rule-based algorithm, physiological wearable sensors, real-world field studies, perceived stress