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Comparative Study
. 2024 Sep 1;20(9):1479-1488.
doi: 10.5664/jcsm.11178.

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

Affiliations
Comparative Study

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

Sara H Browne et al. J Clin Sleep Med. .

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.

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Conflict of interest statement

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.

Figures

Figure 1
Figure 1. Bland–Altman plot of SpO2 error for wrist device SpO2 values, obtained under optimal alignment, against polysomnography (PSG) SpO2 values.
The red line indicates overall bias, with dotted lines corresponding to bias ± 2 standard deviations. The green line indicates bias as a function of SpO2.
Figure 2
Figure 2. ROC curves for prediction of ODI and AHI values.
(A) ROC curve for predicting PSG ODI > 15 events/h from ODI values measured by the Smart Watch. (B) ROC curves for predicting AHI > 15 events/h from sleep questionnaires. AHI = apnea-hypopnea index, AUC = area under the curve, ODI = oxygen desaturation index, PSG = polysomnography, ROC = receiver operating curve, WD = wrist device.
Figure 3
Figure 3. ROC curves for predicting AHI values.
ROC curves for predicting (A) AHI > 30 events/h, (B) AHI > 15 events/h, and (C) AHI > 5 events/h, from ODI estimates by wrist device (WD), Berlin Questionnaire positive categories, and STOP-BANG total score. AHI = apnea-hypopnea index, AUC = area under the curve, ROC = receiver operating curve, WD = wrist device.

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