Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58187, first published .
Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis

Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis

Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis

Journals

  1. Hong M, Kang R, Yang J, Rhee S, Lee H, Kim Y, Lee K, Kim H, Lee Y, Youn T, Kim S, Ahn Y. Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study. Journal of Medical Internet Research 2024;26:e65994 View
  2. Pinilla L, Chai‐Coetzer C, Eckert D. Diagnostic Modalities in Sleep Disordered Breathing: Current and Emerging Technology and Its Potential to Transform Diagnostics. Respirology 2025;30(4):286 View
  3. Bhatt A, Sengupta S, Abolhassani A, Brower D, Forehand C, Keats K, Kwon Y, Healy W. Awakening Sleep Medicine: The Transformative Role of Artificial Intelligence in Sleep Health. Current Sleep Medicine Reports 2025;11(1) View
  4. Zhang H, Bo S, Zhang X, Wang P, Du L, Li Z, Wu P, Chen X, Jiang L, Fang Z. Event-Level Identification of Sleep Apnea Using FMCW Radar. Bioengineering 2025;12(4):399 View
  5. Dang T, Kim S, Choi M, Hwan S, Min H, Bien F. An Automated Algorithm for Obstructive Sleep Apnea Detection Using a Wireless Abdomen-Worn Sensor. Sensors 2025;25(8):2412 View