Performance of a commercial smart watch compared to polysomnography reference for overnight continuous oximetry measurement and sleep apnea evaluation

Abstract

Study objectives: We evaluated the accuracy and precision of continuous overnight oxygen saturation (SpO₂) measurement by a commercial wrist device (WD) incorporating high-grade sensors and investigated WD estimation of sleep-disordered breathing by quantifying overnight oxygen desaturation index compared to polysomnography (PSG) oxygen desaturation index and apnea-hypopnea index (AHI) with and without sleep questionnaire data to assess the WD's ability to detect obstructive sleep apnea and determine its severity.

Methods: Participants completed sleep questionnaires, had a WD (Samsung Galaxy Watch 4) placed on their wrist, and underwent attended, in-laboratory overnight PSG (Nihon Kohden) with a pulse oximetry probe secured either to a finger or an ear lobe. PSG data were scored by a single experienced registered PSG technologist. Statistical analysis included demographic characteristics, continuous SpO₂ measurement WD vs PSG root-mean-square error with Bland-Altman plot and linear regression associations. Predictive models for PSG oxygen desaturation index and AHI severity were built using logistic regression with probability cutoffs determined via receiver operating curve characteristics.

Results: The 51 participants analyzed had a median age of 49 (range, 22-78) years; 66.7% were male, with median body mass index of 28.1 (range, 20.1-47.3) kg/m² with a race/ethnicity distribution of 49.0% Caucasian, 25.5% Hispanic, 9.8% African American, 9.8% Asian, and 5.9% Middle Eastern. WD vs PSG continuous SpO₂ measurement in percentage points demonstrated a bias of 0.91 (95% confidence interval, 0.38, 1.45), standard deviation of 2.37 (95% confidence interval, 2.36, 2.38), and root-mean-square error of 2.54 (95% confidence interval, 2.34, 2.73). WD area under the curve receiver operating curve characteristics for predicting PSG were 0.882 oxygen desaturation index > 15 events/h, 0.894 AHI > 30 events/h, 0.800 AHI > 15 events/h, and 0.803 AHI > 5 events/h. WD plus select sleep questionnaire areas under the curve for predicting PSG were 0.943 AHI > 30 events/h, 0.868 AHI > 15 events/h, and 0.863 AHI > 5 events/h.

Conclusions: The WD conducted reliable overnight continuous SpO₂ monitoring with root-mean-square error < 3% vs PSG. Predictive models of PSG AHI based on WD measurements alone, or plus sleep questionnaires, demonstrated excellent to outstanding discrimination for obstructive sleep apnea identification and severity. Longitudinal WD use should be evaluated promptly based on the WD's potential to improve accessibility and accuracy of obstructive sleep apnea testing, as well as support treatment follow-up.

Citation: Browne SH, Vaida F, Umlauf A, Kim J, DeYoung P, Owens RL. Performance of a commercial smart watch compared to polysomnography reference for overnight continuous oximetry measurement and sleep apnea evaluation. J Clin Sleep Med. 2024;20(9):1479-1488.

Keywords: overnight oximetry; pulse oximetry; sleep apnea; smart watch; wearable device.