Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire

• Published in: PloS one Vol. 16; no. 10; p. e0258040
• Main Authors: Yeh, Eric, Wong, Eileen, Tsai, Chih-Wei, Gu, Wenbo, Chen, Pai-Lien, Leung, Lydia, Wu, I-Chen, Strohl, Kingman P., Folz, Rodney J., Yar, Wail, Chiang, Ambrose A.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 11.10.2021; Public Library of Science (PLoS)
• Subjects: Accelerometers; Adult; Algorithms; Analysis; Apnea; Artificial intelligence; Biology and Life Sciences; Calcium antagonists; Cardiac arrhythmia; Cohort Studies; Computer science; Correlation coefficient; Correlation coefficients; Critical care; Data acquisition; Desaturation; Diagnosis; Female; Heart rate; Humans; Male; Medicine; Medicine and Health Sciences; Middle Aged; Neural networks; Performance assessment; Physical Sciences; Questionnaires; Random Allocation; Research and Analysis Methods; Sensitivity; Sensitivity and Specificity; Sleep; Sleep apnea; Sleep apnea syndromes; Sleep Apnea, Obstructive - diagnosis; Sleep disorders; Stokes, Louis; Surveys and Questionnaires; Wearable Electronic Devices; Wearable technology; Taiwan; Hong Kong China; Ohio; United States > US; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0258040

Many wearables allow physiological data acquisition in sleep and enable clinicians to assess sleep outside of sleep labs. Belun Sleep Platform (BSP) is a novel neural network-based home sleep apnea testing system utilizing a wearable ring device to detect obstructive sleep apnea (OSA). The objective of the study is to assess the performance of BSP for the evaluation of OSA. Subjects who take heart rate-affecting medications and those with non-arrhythmic comorbidities were included in this cohort. Polysomnography (PSG) studies were performed simultaneously with the Belun Ring in individuals who were referred to the sleep lab for an overnight sleep study. The sleep studies were manually scored using the American Academy of Sleep Medicine Scoring Manual (version 2.4) with 4% desaturation hypopnea criteria. A total of 78 subjects were recruited. Of these, 45% had AHI < 5; 18% had AHI 5–15; 19% had AHI 15–30; 18% had AHI ≥ 30. The Belun apnea-hypopnea index (bAHI) correlated well with the PSG-AHI ( r = 0.888, P < 0.001). The Belun total sleep time (bTST) and PSG-TST had a high correlation coefficient ( r = 0.967, P < 0.001). The accuracy, sensitivity, specificity in categorizing AHI ≥ 15 were 0.808 [95% CI, 0.703–0.888], 0.931 [95% CI, 0.772–0.992], and 0.735 [95% CI, 0.589–0.850], respectively. The use of beta-blocker/calcium-receptor antagonist and the presence of comorbidities did not negatively affect the sensitivity and specificity of BSP in predicting OSA. A diagnostic algorithm combining STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h demonstrated an accuracy, sensitivity, specificity of 0.938 [95% CI, 0.828–0.987], 0.944 [95% CI, 0.727–0.999], and 0.933 [95% CI, 0.779–0.992], respectively, for the diagnosis of moderate to severe OSA. BSP is a promising testing tool for OSA assessment and can potentially be incorporated into clinical practices for the identification of OSA. Trial registration: ClinicalTrial.org NCT03997916 https://clinicaltrials.gov/ct2/show/NCT03997916?term=belun+ring&draw=2&rank=1