In Search of Harmful Stress

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

Abstract

Human body produces different physiological stress reaction when you hit a toe to a doorstep than when you panic at a job interview. The impact for body's homeostasis varies depending on the reaction type and some reactions are harmful to our health. Currently, stress estimation is focused on binary identification between stress and non-stress stages. More detailed separation of stress reaction types is needed for detecting harmful stress. In this study, the Extreme Gradient Boosting algorithm was used to classify a baseline condition and physiological and psychosocial stress, based on psychophysiological signals monitored using a wrist sensor device. Classification was robust in separating the two stress states from baseline and from each other. The results provide support for novel approaches utilizing fine-grained estimation of stress type from wearable sensor data.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2021 - Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery ACM
Pages215-217
Number of pages3
ISBN (Electronic)978-1-4503-8461-2
DOIs
Publication statusPublished - 21 Sep 2021
MoE publication typeA4 Article in a conference publication
Event2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2021 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2021 - Virtual, Online, United States
Duration: 21 Sep 202125 Sep 2021

Conference

Conference2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2021 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period21/09/2125/09/21

Keywords

  • psychophysiology
  • stress detection
  • wearable sensing

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