Snore Sound Analysis Can Detect the Presence of Obstructive Sleep Apnea Specific to NREM or REM Sleep

Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine
Shahin AkhterCraig Hukins

Abstract

Severities of obstructive sleep apnea (OSA) estimated both for the overall sleep duration and for the time spent in rapid eye movement (REM) and non-rapid eye movement (NREM) sleep are important in managing the disease. The objective of this study is to investigate a method by which snore sounds can be analyzed to detect the presence of OSA in NREM and REM sleep. Using bedside microphones, snoring and breathing-related sounds were acquired from 91 patients with OSA (35 females and 56 males) undergoing routine diagnostic polysomnography studies. A previously developed automated mathematical algorithm was applied to label each snore sound as belonging to either NREM or REM sleep. The snore sounds were then used to compute a set of mathematical features characteristic to OSA and to train a logistic regression model (LRM) to classify patients into an OSA or non-OSA category in each sleep state. The performance of the LRM was estimated using a leave-one-patient-out cross-validation technique within the entire dataset. We used the polysomnography-based diagnosis as our reference method. The models achieved 80% to 86% accuracy for detecting OSA in NREM sleep and 82% to 85% in REM sleep. When separate models were developed for females ...Continue Reading

Citations

Jun 20, 2020·Physiological Measurement·Jing LuoXiaoyong Ren
Apr 30, 2020·International Journal of Environmental Research and Public Health·Shota HayashiYasunari Miyazaki
Oct 19, 2020·International Journal for Numerical Methods in Biomedical Engineering·Jinxiang XiHaibo Dong
Nov 26, 2020·Sleep & Breathing = Schlaf & Atmung·Berk GürpınarYavuz Uyar
May 21, 2021·Computer Methods and Programs in Biomedicine·Dalibor CimrJan Slegr

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