Peer-Reviewed Publication
PLoS One2021;16(10):e0258040.January 1, 2021Journal Article
Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire.
Eric Yeh1, Eileen Wong1, Chih-Wei Tsai2, Wenbo Gu2,3, Pai-Lien Chen4, Lydia Leung2, I-Chen Wu3, Kingman P Strohl1,5, Rodney J Folz1, Wail Yar6, Ambrose A Chiang1,5
1Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center and Department of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America.
2Belun Technology Company Limited, Sha Tin, Hong Kong.
3Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
4FHI360, Durham, NC, United States of America.
5Division of Sleep Medicine, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America.
6Department of Family Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio United States of America.
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…
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