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

Digital Health Reviews (1812) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2250) Wearable Devices and Sensors (1206) Digital Biomarkers and Digital Phenotyping (319) Transdiagnostic Mental Health Interventions (216) mHealth for Data Collection and Research (1252) Machine Learning (2221)

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
Article Authors Cited by (14) Tweetations (1) Metrics

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  2. Pandian V, Rahimibashar F, Arabfard M, Alhalaiqa F, Vahedian-Azimi A. The role of AI-driven communication in delirium prevention, detection, and care for critically ill ICU patients: A systematic review with inductive thematic synthesis. Intensive and Critical Care Nursing 2026;93:104323 View
  3. Qi L, Liu J. Advancing digital inclusion and cognitive monitoring for older adults. Asian Journal of Psychiatry 2026;117:104839 View
  4. Ha S, Lee T, Seo H, Yoon S, Lee H. A Selective RAG-Enhanced Hybrid ML-LLM Framework for Efficient and Explainable Fatigue Prediction Using Wearable Sensor Data. Bioengineering 2026;13(1):58 View
  5. Bohnert A, Fritsche L, Sen S. Precision approaches for scalable digital and clinic-based interventions in mental health. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2026 View
  6. Salomez-Ihl C, Liaigre L, Dala W, Davat A, Barbado M, Chanoine S, Py P, Schmitt D, Defaye P, Bedouch P. Role of the Pharmacist in Supporting the Use of Connected Health Devices: Example of Connected Watches. Pharmacy 2026;14(1):28 View
  7. Partey-Newman V, Baiden I, Phil-Othihiwa S, Dudzilah G. Digital Biomarkers for Early Cognitive Decline: Clinical Promise, Limitations, and Validation Pathways. Journal of Mental Health and Psychology 2026;1(1):10 View
  8. Tolosa E, Ihianle I, Machado P, Yahaya S, Lotfi A. From Patterns to Deviations: Detecting Behavioural Drift for Mental Health Monitoring Using Smartphone and Wearable Data. Electronics 2026;15(4):885 View
  9. Hertlein K, Rajaei A. Integrating Artificial Intelligence in Systemic Therapy: Strategies for Effective Clinical Practice. International Journal of Systemic Therapy 2026:1 View
  10. Busshart L, Petrovic M, Amin R, Hegerl U. Distinguishing Common Digital Phenotyping and Self-Report Parameters for Monitoring and Predicting Depression: Scoping Review. JMIR mHealth and uHealth 2026;14:e70840 View
  11. Dong P, Zhang S, Zheng X, Yuan W, Wu L, Chen Y. Artificial intelligence robots for mental health applications: a scoping review. Psychiatry Research 2026;360:117059 View
  12. Su K, Chen S, Chang J. The digital pandemic in youth: unpacking the algorithmic impact on mental health in an urbanized world. Current Opinion in Psychiatry 2026 View
  13. Xu Y, Zhao Z, Zhu H, Lai S, Jia Y, Liu G. Machine Learning-Empowered Depression Detection With Wearable Skin Electronics: A Review. IEEE Sensors Journal 2026;26(6):7949 View
  14. Zhao Y, Zuo L, Yu D, Pan R, Fu L, Lu Y, Zhang H. Mobile systems for healthcare 5.0: Applications, challenges and opportunities. High-Confidence Computing 2026:100392 View