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Factors that May Influence the Classification of Sleep-Wake by Wrist Actigraphy: The MrOS Sleep Study

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References

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2003

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Further Validation of Actigraphy for Sleep Studies

587 cited

2006Actigraphy Validation with Insomnia502 cited

2007Wake Detection Capacity of Actigraphy During Sleep352 cited

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2019A Review of Approaches for Sleep Quality Analysis106 cited
2014A comparison of radio-frequency biomotion sensors and actigraphy versus polysomnography for the assessment of sleep in normal subjects95 cited
2013Sleep Disturbances and Risk of Depression in Older Men94 cited
2022The 103,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes75 cited
2020Multidimensional sleep health domains in older men and women: an actigraphy factor analysis74 cited
2014Assessment of Sleep in the National Social Life, Health, and Aging Project64 cited
2023Selecting a sleep tracker from EEG-based, iteratively improved, low-cost multisensor, and actigraphy-only devices60 cited
2019The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient‐ and device‐specific factors57 cited