Performance evaluation of an under-mattress sleep sensor versus polysomnography in >400 nights with healthy and unhealthy sleep

Abstract

Consumer sleep trackers provide useful insight into sleep. However, large scale performance evaluation studies are needed to properly understand sleep tracker accuracy. This study evaluated performance of an under-mattress sensor to estimate sleep and wake versus polysomnography in a large sample, including individuals with and without sleep disorders and during day versus night sleep opportunities, across multiple in-laboratory studies. 183 participants (51/49% male/female, mean[SD] age=45[18] years) attended the sleep laboratory for a research study including simultaneous polysomnography and under-mattress sensor (Withings Sleep Analyzer [WSA]) recordings. Epoch-by-epoch analyses determined accuracy, sensitivity, and specificity of the WSA versus polysomnography. Bland-Altman plots examined bias in sleep duration, efficiency, onset-latency, and wake after sleep onset. Overall WSA sleep-wake classification accuracy was 83%, sensitivity 95%, and specificity 37%. The WSA significantly overestimated total sleep time (48[81]minutes), Sleep efficiency (9[15]%), sleep onset latency (6[26]minutes), and underestimated wake after sleep onset (54[78]minutes). Accuracy and specificity were higher for night versus daytime sleep opportunities in healthy individuals (89% and 47% versus 82% and 26% respectively, p<0.05). Accuracy and sensitivity were also higher for healthy individuals (89% and 97%) versus those with sleep disorders (81% and 91%, p<0.05). WSA performance is comparable to other consumer sleep trackers, with high sensitivity but poor specificity compared to polysomnography. WSA performance was reasonably stable, but more variable in daytime sleep opportunities and in people with a sleep disorder. Contactless, under-mattress sleep sensors show promise for accurate sleep monitoring, noting the tendency to over-estimate sleep particularly where wake time is high.