Belun Ring Platform With an Improved Algorithm for OSA Assessment

Study Overview
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Brief Summary
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OSA is commonly diagnosed with either attended in-lab polysomnography (PSG) or unattended home sleep apnea testing (HSAT). The BLS-100 (Belun Technology Company Limited, Hong Kong) is a novel neural network-based HSAT platform consists of a ring shape pulse oximeter sensor, a cradle, and an improved proprietary analytic algorithm. This study investigates the hypothesis that the BLS-100 is a reasonable HSAT device for OSA assessment.

Official Title
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Belun Ring Platform (BLS-100) Home Sleep Apnea Testing Device With an Improved Algorithm for Assessment of Obstructive Sleep Apnea: A Comparison to In-Lab Polysomnography

Conditions
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Sleep-Disordered Breathing, Sleep Architecture

Intervention / Treatment
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* Device: Belun Ring
* Diagnostic Test: PSG


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Provision of signed and dated informed consent form. Age 18-80 Clinically assessed and suspicious for OSA Exclusion Criteria: Full night PAP titration study On home O2, noninvasive ventilator, diaphragmatic pacing, or any form of nerve stimulator Having atrial fibrillation-flutter, pacemaker/defibrillator, LVEF < 55%, left ventricular assist device (LVAD), or status post cardiac transplantation Patients taking narcotics Recent hospitalization or recent surgery in the past 30 days Unstable cardiopulmonary status on the night of the study judged to be unsafe for sleep study by the sleep tech and/or the on-call sleep physician An individual who meets the above criteria but fails to have at least 4 hours of technically valid sleep based on BLS-100 in a diagnostic study or at least 3 hours of technically valid sleep during the diagnostic portion of a split night study will be excluded from statistical analyses.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: UH-Participant<br>Potential participants with suspected OSA will be identified from the schedule of the UH Beachwood and Bolwell sleep labs.Those subjects who satisfy the study inclusion and exclusion criteria will be approached and invited to participate in the study. | Device: Belun Ring<br>* The Belun Ring sensor will be applied to the proximal phalanx of the index finger in the non-dominant hand of the participating individuals prior to their sleep onset in the sleep lab and will be removed upon awakening at the end of the sleep period on the following morning. The attended in-lab sleep study will be performed simultaneously in a standard fashion.<br>Diagnostic Test: PSG<br>* All patients scheduled for attended overnight in-lab polysomnography (PSG) in our 2 sleep labs will undergo PSG testing. On the same night of the PSG testing, these same patients will also wear the Belun Ring device. After the study, we will compare results of the Belun Ring device vis-à-vis with the results of the PSG on the same patient.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| REI parameters | To determine the overall accuracy, sensitivity, and specificity of the BLS-100 in assessing OSA by comparing to the attended in-lab PSG in individuals referred to the sleep labs with clinical suspicion of OSA. | 1 year | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sleep stage parameters | To determine the accuracy of BLS-100 sleep stage parameters to classify the human sleep stage (Wake, REM and Non-REM) by comparing to the classification results of in-lab PSG. | 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Validation, Obstructive Sleep Apnea, Wearable, Home Sleep Apnea Testing, Photoplethysmography, Artificial Intelligence