Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned

Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned

BackgroundEarly detection of elevated acute stress is necessary if we aim to reduce consequences associated with prolonged or recurrent stress exposure. Stress monitoring may be supported by valid and reliable machine-learning algorithms. However, investigation of algorithms detecting stress severit...

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Main Authors: Marketa Ciharova, Khadicha Amarti, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Mieke Schulte, Eirini Karyotaki, Pim Cuijpers, Heleen Riper
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Psychiatry
Subjects:
stress
machine learning
multimodal
acoustic
verbal
video
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1548287/full
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https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1548287/full

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