A4 Artikkeli konferenssijulkaisussa
Estimating Stress in Online Meetings by Remote Physiological Signal and Behavioral Features (2022)

Sun, Z., Vedernikov, A., Kykyri, V.-L., Pohjola, M., Nokia, M., & Li, X. (2022). Estimating Stress in Online Meetings by Remote Physiological Signal and Behavioral Features. In UbiComp/ISWC '22 Adjunct : Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers (pp. 216-220). ACM. https://doi.org/10.1145/3544793.3563406

JYU-tekijät tai -toimittajat

Kykyri, Virpi-Liisa
Pohjola, Mikko
Nokia, Miriam

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Sun, Zhaodong; Vedernikov, Alexander; Kykyri, Virpi-Liisa; Pohjola, Mikko; Nokia, Miriam; Li, Xiaobai

Emojulkaisu: UbiComp/ISWC '22 Adjunct : Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers

Konferenssi:

ACM international joint conference on pervasive and ubiquitous computing

Konferenssin paikka ja aika: Cambridge, United Kingdom, 11.-15.9.2022

eISBN: 978-1-4503-9423-9

Julkaisuvuosi: 2022

Ilmestymispäivä: 24.04.2023

Artikkelin sivunumerot: 216-220

Kustantaja: ACM

Kustannuspaikka: New York

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1145/3544793.3563406

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/86616

Tiivistelmä

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%.

YSO-asiasanat: stressi; psykofysiologia; etäseuranta; syke; sykemittarit; ilmeet; katseenseuranta; etäkokoukset