Belun Ring Platform: a novel home sleep apnea testing system for assessment of obstructive sleep apnea

Abstract

Study Objectives: The objective of the study is to validate the performance of Belun Ring Platform, a novel home sleep apnea testing system using a patented pulse oximeter sensor and a proprietary cloud-based neural networks algorithm. Methods: The Belun Ring captures oxygen saturation, photoplethysmography, and accelerometer signals. The Belun Ring total sleep time is derived from features extracted from accelerometer, oxygen saturation, and photoplethysmography signals. The Belun Ring respiratory event index is derived from Belun Ring total sleep time and features extracted from heart rate variability and oxygen saturation changes. A total of 50 adults without significant cardiopulmonary or neuromuscular comorbidities and heart rate affecting medications were evaluated. In-lab sleep studies were performed simultaneously with the Ring and the studies were manually scored using the American Academy of Sleep Medicine Scoring Manual 4% desaturation criteria. Results: The Belun Ring respiratory event index correlated well with the polysomnography-apnea-hypopnea index (AHI; r = .894, P < .001). The sensitivity and specificity in categorizing AHI ≥ 15 events/h were 0.85 and 0.87, respectively, and the positive predictive value and negative predictive value were 0.88 and 0.83, respectively. The Belun Ring total sleep time also correlated well with the polysomnography-total sleep time (r = .945, P < .001). Although the Belun Ring Platform has a good overall performance, it tends to overestimate AHI in individuals with AHI under 15 events/h and underestimate AHI in those with AHI over 15 events/h. Conclusions: In this proof-of-concept study, the Belun Ring Platform demonstrated a reasonable accuracy in predicting AHI and total sleep time in patients without significant comorbidities and heart rate-affecting medications.

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

“…A total of 336 consecutive subjects who were referred to the American Academy of Sleep Medicine (AASM)-accredited University Hospitals Cleveland Medical Center labs (Beachwood and Cleveland, Ohio) for evaluation of sleep disorders were screened; 206 adult subjects met the eligibility criteria; 113 signed informed consent and participated in the study. Seventy-eight subjects who passed the 2-step ring size optimization protocol and had a recording time ≥ 4 hours were enrolled ( Fig 2 ) [ 32 ]. Patients who were on heart-rate altering medications such as beta-blockers and/or calcium channel antagonists were included in this study.…”

“…In this study, the neural network algorithm used in the BSP is the same as that used in the proof-of-concept study [ 32 ]. The BSP ring captures oxygen saturation (SpO2), photoplethysmography (PPG), and accelerometer signals.…”

“…The bTST is derived from features extracted from accelerometer, SpO2, and PPG signals. The bAHI is derived from bTST and features extracted from heart rate variability and SpO2 changes [ 32 ].…”

“…There are seven different ring sizes (sizes 5, 7, 9, 10, 11, 13, and 15) available. A 2-step ring selection approach was used to ensure the appropriate ring size as described in the proof-of-concept study [ 32 ]. Once the ring selection is optimized, the ring is securely placed on the proximal phalanx of the non-dominant hand index finger and left in place overnight.…”

“…A recent proof-of-concept study in adult subjects not taking heart-rate affecting medications and having no significant comorbidities showed a good correlation between the Belun apnea-hypopnea index (bAHI) and the PSG-AHI as well as good sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in categorizing AHI ≥ 15 events/h. The Belun total sleep time (bTST) also correlated well with the PSG-TST [ 32 ].…”