Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep MedicineApr 23, 2024

How a Commercial Smartwatch Measures Overnight Oxygen Levels and Detects Sleep Apnea Compared to Standard Sleep Tests

GLP-1 Therapies Weekly Brief ↗PubMed ↗DOI ↗

Updated Mar 31, 2026

Abstract

The wrist device showed a root-mean-square error of 2.54% in oxygen saturation measurement compared to polysomnography.

The wrist device demonstrated a bias of 0.91 percentage points in continuous oxygen saturation measurements.
Receiver operating curve analysis indicated the wrist device had an area under the curve of 0.882 for predicting an oxygen desaturation index greater than 15 events per hour.
When combined with select sleep questionnaire data, the wrist device's predictive model for apnea-hypopnea index (AHI) showed an area under the curve of 0.943 for AHI greater than 30 events per hour.
The findings suggest that the wrist device may reliably monitor overnight oxygen saturation and aid in identifying obstructive sleep apnea severity.

Simplified

STUDY OBJECTIVES: We evaluated the accuracy and precision of continuous overnight oxygen saturation (SpO) 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. 2

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 SpOmeasurement 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. 2

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/mwith 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 SpOmeasurement 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. 2 2

CONCLUSIONS: The WD conducted reliable overnight continuous SpOmonitoring 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. 2

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.2024;20(9):1479-1488. J Clin Sleep Med.

Funding

Competing interests

All authors have seen and approved this manuscript. Work for this study was performed at the University of California, San Diego. The authors report the following funding: S.H. Browne: Samsung Electronics Research Grant 30119640, NIH R01 MH110057S, US Non-profit Specialists in Global Health 2982; F. Vaida: Samsung Electronics Research Grant 30119640, NIH R01 MH110057S, US Non-profit Specialists in Global Health 2982; A. Umlauf: Samsung Electronics Research Grant 30119640, NIH R01 MH110057S, Specialists in Global Health 2982; J. Kim: Samsung Electronics Research Grant 30119640, NIH R01 MH110057S, Specialists in Global Health; P. DeYoung: Samsung Electronics Research Grant 30119640, NIH R01 HL142114; R.L. Owens: Samsung Electronics Research Grant 30119640, NIH R01 HL142114, Nitto Denko Asia.

PubMed

How a Commercial Smartwatch Measures Overnight Oxygen Levels and Detects Sleep Apnea Compared to Standard Sleep Tests

Abstract

Funding

Competing interests

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