ArticleSleep & breathing = Schlaf & Atmung2025
Belun Sleep Platform versus in-lab polysomnography for obstructive sleep apnea diagnosis.
Article in Sleep & breathing = Schlaf & Atmung, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy of Artificial Intelligence in Diagnosing Obstructive Sleep Apnea Using Photoplethysmography: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Diagnostic value of wearable and contactless technologies for detecting obstructive sleep apnea: a systematic review and meta-analysis.Sleep & breathing = Schlaf & Atmung · 2025Pooled it
- Artificial intelligence for sleep-disordered breathing: a taxonomy of methods, data modalities, and clinical applications.Frontiers in sleep · 2026Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to compare the Belun Sleep Platform (BSP), an artificial intelligence-driven home sleep testing device, with polysomnography (PSG) for diagnosing obstructive sleep apnea. The BSP analyzes oxygen saturation, heart rate, and accelerometry patterns.
methodsParticipants scheduled for PSG and with no significant cardiovascular or neuromuscular comorbidities were recruited. They underwent simultaneous in-laboratory, full-night PSG with the BSP. We assessed diagnostic properties, including sensitivity, specificity, positive predictive value, negative predictive value, and accuracy.
resultsA total of 40 participants (54.3% male) with a mean age of 49.9 years were enrolled. For an apnea-hypopnea index (AHI) cutoff of ≥ 15 events/h, BSP showed an accuracy of 68.5%, sensitivity of 35.2%, and specificity of 100% under American Academy of Sleep Medicine criteria 1 A and 1B. For AHI thresholds of ≥ 5 and ≥ 30 events/h, sensitivity was 82.1% and 33.3%, respectively, while specificity was 14.2% and 100%, respectively. BSP-AHI correlated moderately with PSG-AHI (intraclass correlation coefficient [ICC] = 0.737). BSP's oxygen desaturation index (ODI) showed a strong correlation with PSG-ODI (ICC = 0.882). Moderate correlations were observed between BSP and PSG for non-rapid eye movement sleep duration (ICC = 0.736), rapid eye movement sleep duration (ICC = 0.664), total sleep time (ICC = 0.617), and sleep efficiency (ICC = 0.719).
conclusionsThe BSP's high specificity but low sensitivity suggests it serves better as a confirmatory tool rather than a primary screening method. Its moderate concordance with PSG underscores its potential in settings where PSG is unavailable. However, further investigation is needed to refine its clinical applications.
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