University of Oulu

Zhaodong Sun, Alexander Vedernikov, Virpi-Liisa Kykyri, Mikko Pohjola, Miriam Nokia, and Xiaobai Li. 2022. Estimating Stress in Online Meetings by Remote Physiological Signal and Behavioral Features. In Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp/ISWC ’22 Adjunct), September 11–15, 2022, Cambridge, United Kingdom. ACM, New York, NY, USA, 5 pages.

Estimating stress in online meetings by remote physiological signal and behavioral features

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Author: Sun, Zhaodong1; Vedernikov, Alexander1; Kykyri, Virpi-Liisa2;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Finland
2Department of Psychology, University of Jyväskylä, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
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Language: English
Published: Association for Computing Machinery, 2022
Publish Date: 2023-06-19


Work stress impacts people’s daily lives. Their well-being can be improved if the stress is monitored and addressed in time. Attaching physiological sensors are used for such stress monitoring and analysis. Such approach is feasible only when the person is physically presented. Due to the transfer of the life from offline to online, caused by the COVID-19 pandemic, remote stress measurement is of high importance. This study investigated the feasibility of estimating participants’ stress levels based on remote physiological signal features (rPPG) and behavioral features (facial expression and motion) obtained from facial videos recorded during online video meetings. Remote physiological signal features provided higher accuracy of stress estimation (78.75%) as compared to those based on motion (70.00%) and facial expression (73.75%) features. Moreover, the fusion of behavioral and remote physiological signal features increased the accuracy of stress estimation up to 82.50%.

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ISBN: 978-1-4503-9423-9
Pages: 216 - 220
DOI: 10.1145/3544793.3563406
Host publication: UbiComp/ISWC 2022 Adjunct : Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers
Conference: ACM International Joint Conference on Pervasive and Ubiquitous Computing
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: The study was supported by the Finnish Work Environment Fund (Project 200414 and 200337) and the Academy of Finland (Project 323287 and 345948).
Academy of Finland Grant Number: 323287
Detailed Information: 323287 (Academy of Finland Funding decision)
345948 (Academy of Finland Funding decision)
Copyright information: © 2022 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.