In-home validation of wrist- and waist-worn devices against portable electroencephalography for sleep assessment in older adults

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Abstract Sleep health is essential for older adults. However, validity of wrist- and waist-worn devices for assessing sleep under free-living conditions remains unclear. This study evaluated the accuracy of a wrist-worn smartwatch (Silmee W22) and a waist-worn activity monitor (MTN-221) in measuring key sleep parameters, using portable electroencephalography (EEG; Insomnograf K2) as the reference. Healthy older adults wore all devices simultaneously for at least three nights. Total sleep time, sleep onset latency, wake after sleep onset, and sleep efficiency were analyzed using Bland– Altman plots, multilevel models, and intraclass correlation coefficients (ICCs). Fifty-five participants completed the study, yielding valid EEG-paired data for 49 participants with Silmee W22 (238 nights) and 53 with MTN-221 (265 nights). Silmee W22 overestimated total sleep time by 35 min and sleep efficiency by 8.1%, whereas MTN-221 overestimated it by 3 min and sleep efficiency by 1.0%. Both devices underestimated sleep onset latency and wake after sleep onset, with greater discrepancies observed as the estimated values increased. ICCs for total sleep time were 0.60–0.75 for Silmee W22 and 0.66–0.79 for MTN-221, while agreement for sleep onset latency and wake after sleep onset remained lower. While Silmee W22 did not provide sufficiently accurate estimates of total sleep time, MTN-221 yielded estimates that may offer practical benefits for large-scale sleep monitoring in older adults. In both devices, estimates of sleep onset latency, wake after sleep onset, and sleep efficiency should be interpreted with caution due to misclassification of quiet wakefulness. Further algorithm refinement is warranted.

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