Belun Ring (Belun Sleep System BLS-100): Deep learning-facilitated wearable enables obstructive sleep apnea detection, apnea severity categorization, and sleep stage classification in patients suspected of obstructive sleep apnea.
Sleep Health
; 9(4): 430-440, 2023 08.
Article
em En
| MEDLINE
| ID: mdl-37380590
ABSTRACT
GOAL AND AIMS:
Our objective was to evaluate the performance of Belun Ring with second-generation deep learning algorithms in obstructive sleep apnea (OSA) detection, OSA severity categorization, and sleep stage classification. FOCUS TECHNOLOGY Belun Ring with second-generation deep learning algorithms REFERENCE TECHNOLOGY In-lab polysomnography (PSG) SAMPLE Eighty-four subjects (M F = 11) referred for an overnight sleep study were eligible. Of these, 26% had PSG-AHI<5; 24% had PSG-AHI 5-15; 23% had PSG-AHI 15-30; 27% had PSG-AHI ≥ 30.DESIGN:
Rigorous performance evaluation by comparing Belun Ring to concurrent in-lab PSG using the 4% rule. CORE ANALYTICS Pearson's correlation coefficient, Student's paired t-test, diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, Cohen's kappa coefficient (kappa), Bland-Altman plots with bias and limits of agreement, receiver operating characteristics curves with area under the curve, and confusion matrix. COREOUTCOMES:
The accuracy, sensitivity, specificity, and kappa in categorizing AHI ≥ 5 were 0.85, 0.92, 0.64, and 0.58, respectively. The accuracy, sensitivity, specificity, and Kappa in categorizing AHI ≥ 15 were 0.89, 0.91, 0.88, and 0.79, respectively. The accuracy, sensitivity, specificity, and Kappa in categorizing AHI ≥ 30 were 0.91, 0.83, 0.93, and 0.76, respectively. BSP2 also achieved an accuracy of 0.88 in detecting wake, 0.82 in detecting NREM, and 0.90 in detecting REM sleep. CORECONCLUSION:
Belun Ring with second-generation algorithms detected OSA with good accuracy and demonstrated a moderate-to-substantial agreement in categorizing OSA severity and classifying sleep stages.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Apneia Obstrutiva do Sono
/
Dispositivos Eletrônicos Vestíveis
/
Aprendizado Profundo
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Sleep Health
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos