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

Journal: Journal of medical Internet research
PMID: 39255014

Abstract

BACKGROUND: Early detection of sleep apnea, the health condition where airflow either ceases or decreases episodically during sleep, is crucial to initiate timely interventions and avoid complications. Wearable artificial intelligence (AI), the integration of AI algorithms into wearable devices to collect and analyze data to offer various functionalities and insights, can efficiently detect sleep apnea due to its convenience, accessibility, affordability, objectivity, and real-time monitoring capabilities, thereby addressing the limitations of traditional approaches such as polysomnography.

Authors

  • Alaa Abd-Alrazaq
    College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
  • Hania Aslam
    AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.
  • Rawan AlSaad
    AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.
  • Mohammed Alsahli
    Health Informatics Department, College of Health Science, Saudi Electronic University, Riyadh, Saudi Arabia.
  • Arfan Ahmed
    AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.
  • Rafat Damseh
  • Sarah Aziz
    AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.
  • Javaid Sheikh
    AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.

Keywords

External Resources

Popular Topics
Recent Journals