Research
Adherence
Automatic scoring algorithms applied to wrist actigraphy data can distinguish sleep from wakefulness with approximately 88% accuracy, providing reliable estimates of sleep latency, total sleep time, and sleep efficiency comparable to polysomnography.
Wrist actigraphy with automated scoring is a reliable, non-invasive tool for monitoring sleep patterns in clinical and research settings. It offers accuracy comparable to expensive lab-based polysomnography for key metrics like sleep latency and total sleep time, making it a practical choice for long-term sleep assessment.
GoodSupportsHIGH confidence
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).
Why this rating
Prospective validation on a diverse sample (n=41) with high correlation to gold-standard PSG.
Source
Automatic Sleep/Wake Identification From Wrist Activity
Roger J. Cole et al. · SLEEP · 1992
cross_sectional · n=41Cited 1,932×
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