A perspective on automated rapid eye movement sleep assessment

Article Properties
  • Language
    English
  • DOI (url)
  • Publication Date
    2024/04/23
  • Indian UGC (Journal)
  • Refrences
    67
  • Mathias Baumert Discipline of Biomedical Engineering, School of Electrical and Mechanical Engineering The University of Adelaide Adelaide Australia ORCID (unauthenticated)
  • Huy Phan Amazon Cambridge Massachusetts USA
Abstract
Cite
Baumert, Mathias, and Huy Phan. “A Perspective on Automated Rapid Eye Movement Sleep Assessment”. Journal of Sleep Research, 2024, https://doi.org/10.1111/jsr.14223.
Baumert, M., & Phan, H. (2024). A perspective on automated rapid eye movement sleep assessment. Journal of Sleep Research. https://doi.org/10.1111/jsr.14223
Baumert M, Phan H. A perspective on automated rapid eye movement sleep assessment. Journal of Sleep Research. 2024;.
Journal Categories
Medicine
Internal medicine
Neurosciences
Biological psychiatry
Neuropsychiatry
Medicine
Internal medicine
Neurosciences
Biological psychiatry
Neuropsychiatry
Neurology
Diseases of the nervous system
Description

Can technology accurately track our dreams? This article offers a perspective on the use of automated systems for rapid eye movement (REM) sleep assessment, highlighting how biomedical signals associated with REM sleep can be harnessed for automated sleep staging. The accuracy of these systems now rivals human expert scorers, promising to revolutionize sleep studies. The paper summarizes key developments in automated sleep staging, exploring their potential role in clinical settings. It also discusses the emerging use of consumer sleep trackers for REM sleep assessment, enabling unprecedented sleep data collection on a global scale. The authors explore the accuracy of current consumer devices. The article concludes with a forward-looking view on computerized REM sleep assessment and the potential for AI systems to enhance sleep research and clinical practice. It offers insights into the future of sleep monitoring and its impact on our understanding of sleep's role in health and well-being.

Published in the Journal of Sleep Research, this article is directly relevant to the journal's scope, which focuses on sleep, biological rhythms, and related areas. The review offers a perspective on automated sleep assessment techniques, including their application in clinical and consumer settings. It highlights the use of artificial intelligence in sleep, a key focus of sleep research.

Refrences