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Title: Cepstrum feature selection for the classification of Sleep Apnea-Hypopnea Syndrome based on heart rate variability
Authors: Ravelo García, Antonio Gabriel 
Navarro Mesa, Juan Luis 
Hernadez-Perez, E.
Martín González, Sofía Isabel 
Quintana-Morales, P. 
Guerra-Moreno, I. 
Julia-Serda, G.
UNESCO Clasification: 3314 Tecnología médica
Keywords: electrocardiography
medical signal processing
medical disorders
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.
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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