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. 2023 Sep 19;23(18):7976.
doi: 10.3390/s23187976.

Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring

Hyunjun Jung  1 , Dongyeop Kim  2 , Jongmin Choi  1 , Eun Yeon Joo  3
Affiliations

Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring

Hyunjun Jung et al. Sensors (Basel). .

Abstract

Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation. A total of 195 participants visiting our sleep clinic underwent overnight polysomnography while wearing the GW, and the RR estimated by the GW was compared with the reference RR obtained from the nasal thermocouple. For all participants, the root mean squared error (RMSE) of the average overnight RR and continuous RR measurements were 1.13 bpm and 1.62 bpm, respectively, showing a small bias of 0.39 bpm and 0.37 bpm, respectively. The Bland-Altman plots indicated good agreement in the RR measurements for the normal, mild, and moderate OSA groups. In participants with normal-to-moderate OSA, both average overnight RR and continuous RR measurements achieved accuracy rates exceeding 90%. However, for patients with severe OSA, these accuracy rates decreased to 79.45% and 75.8%, respectively. The study demonstrates the GW's ability to accurately estimate RR during sleep, even though accuracy may be compromised in patients with severe OSA.

Keywords: accelerometer; obstructive sleep apnea; photoplethysmography; respiratory rate; sleep monitoring; wearable device.

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Conflict of interest statement

The authors of this paper (H.J., J.C.) are affiliated with Samsung Electronics, the company that manufactures the device used in the study. This study was funded by Samsung Electronics. To maintain transparency and uphold the integrity of the research process, the authors declare their associations and acknowledge the possible influence of these relationships on the outcomes of the study. The authors have undertaken their best efforts to conduct the study impartially and objectively, adhering to rigorous scientific standards.

Figures

Figure 1
Figure 1
Representative traces of accelerometer- and photoplethysmography-derived breathing signals from a wrist-worn device, when the device was far away (A) or close (B) to the trunk.
Figure 2
Figure 2
Examples of comparison of estimated respiration rate from the wearable device with the reference derived from nasal thermocouple of polysomnography in patients with mild (A) and moderate (B) obstructive sleep apnea. Reference respiration rate (RR) is represented in two ways: the log-scaled time-frequency analysis spectrum (upper panel) and a line depicting zero-crossing rate using a five-minute window with a one-minute shift (lower panel). In mild OSA (A), a continuous high-power band appears in the spectrogram with high-accuracy RR estimation by the watch. However, in moderate OSA (B), there is a weak power band and large variability in the spectrogram (arrowheads) with low-accuracy RR estimation.
Figure 3
Figure 3
Correlation and Bland–Altman plots comparing the average overnight respiration rate between the watch and reference for the apnea-hypopnea index < 30 group (A) and all subjects (B).
Figure 4
Figure 4
Correlation and Bland–Altman plots comparing continuous respiration rate measurements between the watch and reference for apnea-hypopnea index < 30 group (A) and all subjects (B).
Figure 5
Figure 5
Bland–Altman plots comparing the average overnight respiration rate depending on obstructive sleep apnea severity.
Figure 6
Figure 6
Bland–Altman plots comparing the continuous respiration rate measurements depending on obstructive sleep apnea severity.
See this image and copyright information in PMC

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