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Posts tagged #SleepAlgorithms

JMIR Publications

@jmirpub.bsky.social

3 months ago

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Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study Background: For decades, the measurement of sleep and wake has relied upon watch-based Actigraphy as an alternative to expensive, obtrusive, clinical monitoring. To date, we have relied upon a handful of algorithms to score actigraphy data as sleep or wake. However, these algorithms have largely been tested and validated with only small samples of young healthy individuals. Objective: To address this issue, this study established the accuracy and agreement of conventional and traditional actigraphy algorithms against polysomnography the clinical standard using the diverse MESA sleep dataset. As a secondary objective, we examined algorithm and polysomnography agreement for key sleep metrics including total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO). Methods: We assessed 5 well established algorithms including Cole-Kripke, UCSD scoring, Kripke 2010, Philips-Respironics, and Sadeh, with and without rescoring across 1440 individuals (Mage=69.36+/-8.97) from the MESA sleep dataset. We conducted epoch-by-epoch comparison assessing accuracy, confusion matrix analyses, Receiver Operator Characteristic Curves, Area Under the Curve, and Bland Altman analyses for agreement. Results: Primary results indicated all algorithms demonstrated accuracy between 78%-80% with the highest accuracy by the Kripke 2010 (80%) algorithm and closely by Cole-Kripke (80%) and Philips-Respironics (80-79%) algorithms. In addition, moderate Cohens kappa agreement and moderate positive Matthews correlations were demonstrated by all algorithms. Further, all algorithms demonstrated significant mean difference across sleep metrics. Conclusions: 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.

JMIR Formative Res: Comparison and Validation of Actigraphy Algorithms Using a Large Community Dataset: Algorithm Validation Study #SleepStudy #Actigraphy #Polysomnography #DataValidation #SleepAlgorithms

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