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

Sleep Monitoring, Sleep Quality, Sleep Disorders (356) New Methods (1824) Design and Usability of Medical Devices (236) Wearable Devices and Sensors (1614) Insomnia and Sleep Hygiene (313) Design and Usability of Consumer Health Tech and Home Monitoring Devices (462) Development of Novel Medical Devices and Innovations for Existing Devices (155)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62959, first published .
iPhone screen displaying Health Data app with Activity, Sleep, Nutrition, and Mindfulness sections.

Developing a Sleep Algorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study

Developing a Sleep Algorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study

Authors of this article:

Jeffrey M Cochran1 Author Orcid Image
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Journals

  1. Vandegriffe A, Samaranayake V, Thimgan M, da Costa J. WACSAW: An adaptive, statistical method to classify movement into sleep and wakefulness states. PLOS One 2025;20(12):e0333417 View
  2. Lima W, Pataca A, Al-jumaili S, Reis A, Vieira A, Lopes M, Coelho P, Albuquerque C, Pires I, Velez F. Sensors and computational methods for sleep quality assessment: A systematic review. Results in Engineering 2026;32:112291 View
  3. Wang Z, Tan Z, Zhang Y, Li Y, Lin J, Xu Y, Li Y, Chen T. Exercise-induced neuropeptidergic and neurochemical neuroadaptation in stress regulation and emotional disorders. Acta Neurologica Belgica 2026 View

Conference Proceedings

  1. Pawar P, Jadhav R, Jadhav R, Kadam Y, Jadhav V. 2026 13th International Conference on Computing for Sustainable Global Development (INDIACom). A Survey on Sleep State Classification Using Multimodal Physiological Signals and Advanced Classification Techniques View