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http://hdl.handle.net/10553/43078
| Título: | Cepstrum feature selection for the classification of Sleep Apnea-Hypopnea Syndrome based on heart rate variability | Autores/as: | Ravelo García, Antonio Gabriel Navarro Mesa, Juan Luis Hernadez-Perez, E. Martín González, Sofía Isabel Quintana-Morales, P. Guerra-Moreno, I. Julia-Serda, G. |
Clasificación UNESCO: | 3314 Tecnología médica | Palabras clave: | electrocardiography medical signal processing medical disorders sleep statistical analysis |
Fecha de publicación: | 2013 | Publicación seriada: | Computing in Cardiology | Conferencia: | 40th Annual Meeting on Computing in Cardiology (CinC) | Resumen: | 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 | Fuente: | Computing in Cardiology[ISSN 2325-8861],v. 40 (6713538), p. 959-962 |
| Colección: | Actas de congresos |
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