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This paper is in the following e-collection/theme issue:

Data Science (735) New Methods (1896) Design and Usability of Medical Devices (248) Methods and New Tools in Mental Health Research (965) Wearable Devices and Sensors (1685) Anxiety and Stress Disorders (1676) Diagnostic Tools in Mental Health (462) Machine Learning (3402)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80450, first published .
Woman experiencing chest pain while exercising on a treadmill

Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation Study

Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation Study

Authors of this article:

Buelent Uendes1 Author Orcid Image ;   Alex Antonides1 Author Orcid Image ;   Sjors van de Ven2 Author Orcid Image ;   Denise Johanna van der Mee2 Author Orcid Image ;   Eco de Geus2 Author Orcid Image ;   Mark Hoogendoorn1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Uendes B, Gisbert C, Hoogendoorn M. Beyond supervision: Evaluating contrastive self-supervised learning techniques for ECG-based mental stress detection. Biomedical Signal Processing and Control 2027;131:111731 View

Conference Proceedings

  1. K D, R C. 2026 7th International Conference On Computational Vision and Bio Inspired Computing (ICCVBIC). Multimodal Deep Learning for Mental Health Assessment: A Comprehensive Survey of Stress, Emotion, and Depression Detection View