Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study
The findings of this study establish that these traditional actigraphy algorithms can, with high accuracy, detect sleep and wake in large, diverse population samples, including older adults or populations at risk of health conditions. However, these algorithms may carry difficulty for precise assessment of sleep metrics, especially in cases of sleep disorders or irregular sleep.
Authors
- Darshan Panesar (ORCID: https://orcid.org/0000-0003-1174-4438)
- Robyn Stremler (ORCID: https://orcid.org/0000-0002-8800-2857)
- J.G.M. Gonçalves (ORCID: https://orcid.org/0009-0006-5778-2295)
- Aashish Vichare (ORCID: https://orcid.org/0009-0008-1058-5985)
Institutions
- University of Toronto (CA)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-12-11
- DOI
- https://doi.org/10.2196/70778
- Primary Topic
- Sleep and related disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- Canadian Institutes of Health Research
- National Heart, Lung, and Blood Institute
- National Center for Advancing Translational Sciences