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A snoring classifier based on heart rate variability analysis
Ieong C.-I.1; Dong C.1; Nan W.1; Rosa A.1,2; Guimaraes R.3; Vai M.-I.1; Mak P.-I.1; Wan F.1; Mak P.-U.1
Conference NameConference on Computing in Cardiology
Source PublicationComputing in Cardiology
Conference DateSEP 18-21, 2011
Conference PlaceHangzhou, PEOPLES R CHINA

The effect of snoring on the cardiovascular system is not well-known. In this study we analyzed the Heart Rate Variability (HRV) differences between light and heavy snorers. The experiments are done on the full-whole-night polysomnography (PSG) with ECG and audio channels from patient group (heavy snorer) and control group (light snorer), which are gender- and age-paired, totally 30 subjects. A feature Snoring Density (SND) of audio signal as classification criterion and HRV features are computed. Mann-Whitney statistical test and Support Vector Machine (SVM) classification are done to see the correlation. The result of this study shows that snoring has close impact on the HRV features. This result can provide a deeper insight into the physiological understand of snoring. © 2011 CCAL.

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Indexed BySCI
WOS Research AreaCardiovascular System & Cardiology ; Computer Science
WOS SubjectCardiac & Cardiovascular Systems ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000305132500088
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Document TypeConference paper
Affiliation1.Department of Electrical and Computer Engineering, University of Macau, Macao S.A.R., China
2.Evolutionary Systems and Biomedical Engineering Lab, Technical University of Lisbon, Portugal
3.Department of Neurology, UNESP, Botucatu, Brazil
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ieong C.-I.,Dong C.,Nan W.,et al. A snoring classifier based on heart rate variability analysis[C],2011:345-348.
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