Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43078
Title: Cepstrum feature selection for the classification of Sleep Apnea-Hypopnea Syndrome based on heart rate variability
Authors: Ravelo-Garcia, A. G. 
Navarro-Mesa, J. L. 
Hernadez-Perez, E.
Martin-Gonzalez, S. 
Quintana-Morales, P. 
Guerra-Moreno, I. 
Julia-Serda, G.
UNESCO Clasification: 3314 Tecnología médica
Keywords: electrocardiography
medical signal processing
medical disorders
sleep
statistical analysis
Issue Date: 2013
Journal: Computing in Cardiology 
Conference: 40th Annual Meeting on Computing in Cardiology (CinC) 
Abstract: Cepstrum Coefficients are analyzed in order to study its performance in Sleep Apnea Hypopnea Syndrome (SAHS) screening. A forward feature selection technique is applied in order to know for one thing, what cepstrum parameters can extract better information about the influence of breath sleep disorder on the heart rhythm, and on the other hand, trying to detect apneas based on the RR series obtained from the electrocardiogram (EKG). © 2013 CCAL.
URI: http://hdl.handle.net/10553/43078
ISBN: 9781479908844
ISSN: 2325-8861
Source: Computing in Cardiology[ISSN 2325-8861],v. 40 (6713538), p. 959-962
Appears in Collections:Actas de congresos
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