Automatic Sleep/Wake Identification From Wrist Activity

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ID: 291339
1992
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Ranked #110 of 189 articles by views in Sleep & breathing = Schlaf & Atmung

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Abstract
The purpose of this study was to develop and validate automatic scoring methods to distinguish sleep from wakefulness based on wrist activity. Forty-one subjects (18 normals and 23 with sleep or psychiatric disorders) wore a wrist actigraph during overnight polysomnography. In a randomly selected subsample of 20 subjects, candidate sleep/wake prediction algorithms were iteratively optimized against standard sleep/wake scores. The optimal algorithms obtained for various data collection epoch lengths were then prospectively tested on the remaining 21 subjects. The final algorithms correctly distinguished sleep from wakefulness approximately 88% of the time. Actigraphic sleep percentage and sleep latency estimates correlated 0.82 and 0.90, respectively, with corresponding parameters scored from the polysomnogram (p < 0.0001). Automatic scoring of wrist activity provides valuable information about sleep and wakefulness that could be useful in both clinical and research applications.
Reference Key
openalex_W117545607 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Roger J. Cole, Daniel F. Kripke, William Gruen, Daniel J. Mullaney, J. Christian Gillin
Journal Sleep & breathing = Schlaf & Atmung
Year 1992
DOI
10.1093/sleep/15.5.461
URL
https://academic.oup.com/sleep/article-pdf/15/5/461/13688763/sleep-15-5-461.pdf
Keywords Keywords not found

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