Analysis of non-linear respiratory influences on sleep apnea classification
In this paper we propose the use of Kernel Principal Component Regression (KPCR) in order to model the nonlinear interaction between heart rate (HR) and respiration. We used wavelets in order to decompose the respiratory signal in 2 different frequency bands; namely, the low frequency band (LF) 0-0....
| Autores Principales: | , , |
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| Formato: | Artículo (Article) |
| Lenguaje: | Inglés (English) |
| Publicado: |
Engineering in Medicine and Biology Society
2014
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| Materias: | |
| Acceso en línea: | https://repository.urosario.edu.co/handle/10336/28432 |