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• W2956190908 abstract "To assess the sleep detection and staging validity of a non-contact, commercially available bedside bio-motion sensing device (S+, ResMed) and evaluate the impact of algorithm updates.Polysomnography data from 27 healthy adult participants was compared epoch-by-epoch to synchronized data that were recorded and staged by actigraphy and S+. An update to the S+ algorithm (common in the rapidly evolving commercial sleep tracker industry) permitted comparison of the original (S+V1) and updated (S+V2) versions.Sleep detection accuracy by S+V1 (93.3%), S+V2 (93.8%), and actigraphy (96.0%) was high; wake detection accuracy by each (69.6%, 73.1%, and 47.9%, respectively) was low. Higher overall S+ specificity, compared to actigraphy, was driven by higher accuracy in detecting wake before sleep onset (WBSO), which differed between S+V2 (90.4%) and actigraphy (46.5%). Stage detection accuracy by the S+ did not exceed 67.6% (for stage N2 sleep, by S+V2) for any stage. Performance is compared to previously established variance in polysomnography scored by humans: a performance standard which commercial devices should ideally strive to reach.Similar limitations in detecting wake after sleep onset (WASO) were found for the S+ as have been previously reported for actigraphy and other commercial sleep tracking devices. S+ WBSO detection was higher than actigraphy, and S+V2 algorithm further improved WASO accuracy. Researchers and clinicians should remain aware of the potential for algorithm updates to impact validity.A commentary on this article appears in this issue on page 935." @default.
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• W2956190908 date "2019-07-15" @default.
• W2956190908 modified "2023-10-01" @default.
• W2956190908 title "Sleep Validity of a Non-Contact Bedside Movement and Respiration-Sensing Device" @default.
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• W2956190908 doi "https://doi.org/10.5664/jcsm.7892" @default.
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