Obstructive Sleep Apnea Screening Using a Piezo-Electric Sensor.
10.3346/jkms.2017.32.6.893
- Author:
Urtnasan ERDENEBAYAR
1
;
Jong Uk PARK
;
Pilsoo JEONG
;
Kyoung Joung LEE
Author Information
1. Department of Biomedical Engineering, School of Health Science, Yonsei University, Wonju, Korea. lkj5809@yonsei.ac.kr
- Publication Type:Original Article
- Keywords:
Obstructive Sleep Apnea;
Snoring Index;
Pulse Rate Variability;
Piezo-Electric Sensor;
Support Vector Machine
- MeSH:
Heart Rate;
Humans;
Mass Screening*;
Methods;
Sensitivity and Specificity;
Sleep Apnea, Obstructive*;
Sleep Wake Disorders;
Snoring;
Support Vector Machine
- From:Journal of Korean Medical Science
2017;32(6):893-899
- CountryRepublic of Korea
- Language:English
-
Abstract:
In this study, we propose a novel method for obstructive sleep apnea (OSA) detection using a piezo-electric sensor. OSA is a relatively common sleep disorder. However, more than 80% of OSA patients remain undiagnosed. We investigated the feasibility of OSA assessment using a single-channel physiological signal to simplify the OSA screening. We detected both snoring and heartbeat information by using a piezo-electric sensor, and snoring index (SI) and features based on pulse rate variability (PRV) analysis were extracted from the filtered piezo-electric sensor signal. A support vector machine (SVM) was used as a classifier to detect OSA events. The performance of the proposed method was evaluated on 45 patients from mild, moderate, and severe OSA groups. The method achieved a mean sensitivity, specificity, and accuracy of 72.5%, 74.2%, and 71.5%; 85.8%, 80.5%, and 80.0%; and 70.3%, 77.1%, and 71.9% for the mild, moderate, and severe groups, respectively. Finally, these results not only show the feasibility of OSA detection using a piezo-electric sensor, but also illustrate its usefulness for monitoring sleep and diagnosing OSA.
