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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Cepstrum Coefficients of the RR Series for the Detection of Obstructive Sleep Apnea Based on Different Classifiers
verfasst von : Antonio Ravelo-García, Juan L. Navarro-Mesa, Sofía Martín-González, Eduardo Hernández-Pérez, Pedro Quintana-Morales, Iván Guerra-Moreno, Javier Navarro-Esteva, Gabriel Juliá-Serdá
Erschienen in: Computer Aided Systems Theory - EUROCAST 2013
Verlag: Springer Berlin Heidelberg
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Two automatic statistical methods for the classification of the obstructive sleep apnoea syndrome based on the cepstrum coefficients of the RR series obtained from the Electrocardiogram (ECG) are presented. We study the effect of working with Linear Discriminant Analysis (LDA) and compare its performance with a reference detector based on Support Vector Machines (SVM). These classifications methods require two previous stages: preprocessing and feature extraction. Firstly, R instants are detected previous to the feature extraction phase thanks to a preprocessing over the ECG. Secondly, Cepstrum Coefficients over the RR signal is applied to extract the relevant characteristics specially those related to the system modelled by the filter-type elements concentrated in the low time lag region.