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.
- Home sleep apnea testing
- Obstructive sleep apnea
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine
- Clinical Neurology