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

Development and Evaluation of Research Methods, Instruments and Tools (854) Methods and Instruments in Medical Informatics (226) Wearable Devices and Sensors (1245) Sleep Monitoring, Sleep Quality, Sleep Disorders (289) Digital Biomarkers and Digital Phenotyping (340) Validity, Reliability, and Bias (120)

Published on in Vol 9 (2025)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70778, first published .
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Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study

Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study

Authors of this article:

Darshan Panesar1 Author Orcid Image ;   Aashish Vichare2 Author Orcid Image ;   Jason Goncalves3 Author Orcid Image ;   Robyn Stremler4 Author Orcid Image
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Journals

  1. Oloko-Oba M, Esenogho E, Aruleba K. From Biosignals to Bedside: A Review of Real-Time Edge Machine Learning for Wearable Health Monitoring. Bioengineering 2026;13(5):559 View