Are different consumer sleep technologies measuring the same essential aspects of sleep?

Study objectives Consumer sleep technologies (CSTs) enable low-burden longitudinal sleep monitoring, and their output measures are often interpreted as equivalent to polysomnography (PSG) measures. We applied a measurement reliability-aware approach to determine whether CST-derived 'sleep' measures (1) are interchangeable or device-specific, (2) can reliably assess trait-like sleep characteristics of an individual, (3) can be reduced to latent principal components of sleep, and (4) can be used for classification and biomarker discovery. Methods Data from 74 older adults (20 people living with dementia [PLWD]) were collected at-home (upto 14 nights; Total=752nights) using four tools simultaneously: research-grade actigraphy (Axivity), a wearable (Withings Watch), a nearable (Withings Sleep Analyzer) and Sleep Diary, followed by one in-lab PSG assessment. We used repeated-measures correlation analyses, intraclass correlation coefficients (ICC), principal component analysis (PCA) and binary classification models to address our objectives. Results Single-night between-device correlations and correlations with PSG were moderate (0.3[&le;]r<0.7) for some duration- and timing-related measures, but other associations were weak (r<0.3). Seventy-one percent of sleep measures reached acceptable reliability (ICC[&ge;]0.7) within seven nights of aggregation, but the required aggregation window varied across measures, tools and between PLWD and Controls. Reliability-filtered PCA yielded stable and interpretable principal components, but Duration was the only component showing moderate between-device association. Principal components were successfully used to classify PLWD vs Controls but feature importance varied across devices. Conclusions Aggregation of CST derived measures across 7-14 nights, yielded reliable measures, most of which were device-specific, with duration being the only essential aspect transferable between devices.