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

Digital Health Reviews (1742) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2145) Wearable Devices and Sensors (1150) Digital Biomarkers and Digital Phenotyping (291) Transdiagnostic Mental Health Interventions (210) mHealth for Data Collection and Research (1207) Machine Learning (2095)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77066, first published .
Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Authors of this article:

ShiYing Shen1 Author Orcid Image ;   Wenhao Qi1 Author Orcid Image ;   Jianwen Zeng1 Author Orcid Image ;   Sixie Li1 Author Orcid Image ;   Xin Liu1 Author Orcid Image ;   Xiaohong Zhu1 Author Orcid Image ;   Chaoqun Dong1 Author Orcid Image ;   Bin Wang1 Author Orcid Image ;   Yankai Shi1 Author Orcid Image ;   Jiani Yao1 Author Orcid Image ;   Bingsheng Wang1 Author Orcid Image ;   Xiajing Lou1 Author Orcid Image ;   Simin Gu2 Author Orcid Image ;   Pan Li3 Author Orcid Image ;   Jinghua Wang4 Author Orcid Image ;   Guowei Jiang5 Author Orcid Image ;   Shihua Cao1, 6 Author Orcid Image
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Journals

  1. Ghonge M, Shukla V, Pradeep N, Solanki R, Ghonge M, Shukla V, Garg L, Liu H, Tran T. Recent Advances in Multimodal Deep Learning for Stress Prediction: Toward Cycle-Aware and Gender-Sensitive Health Analytics. EPJ Web of Conferences 2025;341:01059 View