Performance Evaluation of the Verily Numetric Watch Sleep Suite for Digital Sleep Assessment Against In‐Lab Polysomnography

The goal was to evaluate the performance of a suite of 12 sleep measures generated by a multi-sensor wrist-worn wearable device, the verily numetric watch (VNW), in a diverse cohort. We used polysomnography (PSG) as reference during one-night simultaneous recording in a sample of N = 41 (18 male, age range: 18-78 years). We performed epoch-by-epoch comparisons for all measures. Key specific analyses were: core accuracy metrics for sleep versus wake classification; bias for continuous measures (Bland-Altman); unweighted Cohen's kappa and accuracy for sleep stage classifications and mean count difference and linearly weighted Cohen's kappa for count metric. In addition, we performed exploratory subgroup analyses by sex, age, skin tone, body mass index and arm hair density. Sensitivity and specificity (95% CI) of sleep versus wake classification were 0.97 (0.96, 0.98) and 0.66 (0.61, 0.71), respectively. Mean total sleep time bias was 14.55 min (1.61, 27.16); wake after sleep onset, -11.77 min (-23.89, 1.09); sleep efficiency, 3.15% (0.68, 5.57); sleep onset latency, -3.24 min (-9.38, 3.57); light-sleep duration, 3.78 min (-7.04, 15.06); deep-sleep duration, 3.91 min (-4.59, 12.60) and rapid eye movement-sleep duration, 6.94 min (0.57, 13.04). Mean difference for the number of awakenings, 0.17: (95% CI: -0.32, 0.71) and overall accuracy of sleep stage classification, 0.78 (0.51, 0.88). Most measures showed statistically significant proportional biases and/or heteroscedasticity. Exploratory subgroup results appeared largely consistent with the overall group, although small samples precluded strong conclusions. These results support the use of VNWs in classifying sleep versus wake, sleep stages and overnight sleep measures.