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http://dx.doi.org/10.9718/JBER.2014.35.4.75

Sleep Apnea Detection Using a Piezo Snoring Sensor: A Pilot study  

Urtnasan, Erdenebayar (Department of Biomedical Engineering, Yonsei University)
Lee, Hyo-Ki (Department of Biomedical Engineering, Yonsei University)
Kim, Hojoong (Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine)
Lee, Kyoung-Joung (Department of Biomedical Engineering, Yonsei University)
Publication Information
Journal of Biomedical Engineering Research / v.35, no.4, 2014 , pp. 75-80 More about this Journal
Abstract
This paper proposed a method that can automatically classify sleep apnea by using features extracted from pulse rate variability(PRV) signals induced from piezo snoring sensor for patients with obstructive sleep apnea(OSA). We have extracted eight features(NN, SDNN, RMSSD, NN10, NN50, LF, HF and LF/HF ratio) based on time and frequency analyses of PRV. Sleep apnea was classified by a linear discriminant analysis(LDA). A performance was evaluated using snore recordings from 13 patients with OSA (ages: $54.5{\pm}10.5$ years, body mass index: $26.3{\pm}2.5kg/m^2$, apnea-hypopnea index: $19.2{\pm}6.0/h$). The sensitivity and specificity were $78.9{\pm}0.9%$ and $78.9{\pm}0.9%$ for training set and $77.7{\pm}10.9%$ and $79.0{\pm}2.8%$ for test set, respectively. Our study demonstrated the feasibility of implementing a piezo snoring sensor based on a portable device as a simple and cost-effective solution for contributing to the OSA screening.
Keywords
Sleep apnea; OSA screening; piezo snoring sensor;
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