Home Sleep Test - Resource for Clinics

Thank you for choose Belun Ring home sleep test. This page will give you the resource for running the test and interpreting the results. Feel free to contact us by Email or WhatsApp if you have any questions.

Procedure

Operating procedure - If you have Belun Ring at your clinic, this is the procedure you will go through before and after the test.
If you do not have Belun Ring at your clinic, order a delivery here.
Ring size - Make sure you choose a tight fit Ring size for the patient to secure data quality for analysis and reporting.
Sleep test step-by-step 睡眠測試步驟 - The procedure your patient will go through during the test. Video guide for sleep test is also available.
Troubleshooting - Common errors and preventative measures
Status lights of Belun Ring

Test Duration

Minimum 4 hours of sleep is required for a valid sleep study. 6-hour recording is recommended.
Testing for 3 nights is recommended for suspected Obstructive Sleep Apnea. Multiple night testing help reduce first-night effect and compare night-to-night variation.

Exclusion Criteria

Patients on home oxygen, non-invasive ventilator, diaphragmatic pacing, or nerve stimulator
Patients with pacemaker, defibrillator, left ventricular assist device, or status post cardiac transplantation
Patients with atrial fibrillation

Preparation

Avoid alcohol and caffeine during the afternoon and evening before test.
Don't nap during the day.
Effect of sleep medicines should be noted. Certain classes of sleep medicines induce muscle relaxation and more respiratory events.

Interpretation

How to interpret the results in a sleep report

Sample Report

Clinical Validation

Gu W, Leung L, Kwok KC, Wu I-C, Folz RJ, Chiang AA. Belun Ring Platform: a novel home sleep apnea testing system for assessment of obstructive sleep apnea. J Clin Sleep Med. 2020;16(9):1611–1617. https://doi.org/10.5664/jcsm.8592
Yeh E, Wong E, Tsai C-W, Gu W, Chen PL, Leung L, et al. (2021) Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire. PLoS ONE 16(10): e0258040. https://doi.org/10.1371/journal.pone.0258040