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

Author

Listed:
  • Eric Yeh
  • Eileen Wong
  • Chih-Wei Tsai
  • Wenbo Gu
  • Pai-Lien Chen
  • Lydia Leung
  • I-Chen Wu
  • Kingman P Strohl
  • Rodney J Folz
  • Wail Yar
  • Ambrose A Chiang

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

Suggested Citation

  • Eric Yeh & Eileen Wong & Chih-Wei Tsai & Wenbo Gu & Pai-Lien Chen & Lydia Leung & I-Chen Wu & Kingman P Strohl & Rodney J Folz & Wail Yar & Ambrose A Chiang, 2021. "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, Public Library of Science, vol. 16(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0258040
    DOI: 10.1371/journal.pone.0258040
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