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

Digital Health Reviews (1546) Machine Learning (1764) Anxiety and Stress Disorders (1198) Wearable Devices and Sensors (1010) Mobile Health (mhealth) (3176) Artificial Intelligence (1768) AI Applications in Biomedical Engineering (11)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52622, first published .
The Performance of Wearable AI in Detecting Stress Among Students: Systematic Review and Meta-Analysis

The Performance of Wearable AI in Detecting Stress Among Students: Systematic Review and Meta-Analysis

The Performance of Wearable AI in Detecting Stress Among Students: Systematic Review and Meta-Analysis

Authors of this article:

Alaa Abd-alrazaq1 Author Orcid Image ;   Mohannad Alajlani2 Author Orcid Image ;   Reham Ahmad2 Author Orcid Image ;   Rawan AlSaad1 Author Orcid Image ;   Sarah Aziz1 Author Orcid Image ;   Arfan Ahmed1 Author Orcid Image ;   Mohammed Alsahli3 Author Orcid Image ;   Rafat Damseh4 Author Orcid Image ;   Javaid Sheikh1 Author Orcid Image
Article Authors Cited by (8) Tweetations (3) Metrics

Journals

  1. Chen J, Yuan D, Dong R, Cai J, Ai Z, Zhou S. Artificial intelligence significantly facilitates development in the mental health of college students: a bibliometric analysis. Frontiers in Psychology 2024;15 View
  2. Benouis M, Andre E, Can Y. Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy–Added Federated Learning Settings: Quantitative Study. JMIR Mental Health 2024;11:e60003 View
  3. Yıldız E. AI–Augmented Psychosocial Interventions: A Bibliometric Review and Implications for Nursing. Journal of Psychosocial Nursing and Mental Health Services 2025;63(6):11 View
  4. LeBlanc V, Mastoras G, Hicks C, MacGregor P, O'Rielly C, Petrosoniak A, Tavares W. The stressed heart: Validity evidence supporting mobile heart rate variability applications to detect psychological stress in healthcare learners. Medical Education 2025 View
  5. Adams M, Bowness J, Nelson A, Hurley R, Narouze S. A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements. Current Opinion in Anaesthesiology 2025 View
  6. Lialiou P, Maglogiannis I. Students’ Burnout Symptoms Detection Using Smartwatch Wearable Devices: A Systematic Literature Review. AI Sensors 2025;1(1):2 View

Books/Policy Documents

  1. Soni A, Shaikh Z, Taqi M, Bijja V, Ratnakaram S. Wearable Devices and Smart Technology for Educational Teaching Assistance. View
  2. Ghosh R, Singh G, Sharma N. Harnessing AI and Machine Learning for Precision Wellness. View