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

PLoS One. 2021 Oct 11;16(10):e0258040. doi: 10.1371/journal.pone.0258040. eCollection 2021.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cohort Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Random Allocation
  • Sensitivity and Specificity
  • Sleep Apnea, Obstructive / diagnosis*
  • Surveys and Questionnaires
  • Wearable Electronic Devices*

Associated data

  • ClinicalTrials.gov/NCT03997916

Grants and funding

This clinical research was supported by grant BL2018/1001 from the Belun Technology Company Limited, Hong Kong. https://urldefense.com/https://beluntech.com. The Belun Sleep platform devices used in this study were provided by the company. Belun Technology agreed with the design of the study and had no role in the data collection. The sponsor did contribute to the data analysis, decision to publish, and manuscript preparation. The funder, Belun Technology Company, provided support in the form of salaries for authors C. W. Tsai, W. Gu, and L. Leung, but did not have any additional role other than described above. The specific roles of these authors are articulated in the Author Contributions section. This commercial affiliation does not alter our adherence to PLOS ONE policies on sharing data and material.