Application of kernel principal component analysis for single-lead-ECG-derived respiration

Recent studies show that principal component analysis (PCA) of heartbeats is a well-performing method to derive a respiratory signal from ECGs. In this study, an improved ECG-derived respiration (EDR) algorithm based on kernel PCA (kPCA) is presented. KPCA can be seen as a generalization of PCA wher...

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Autores:
Tipo de recurso:
Fecha de publicación:
2012
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/27226
Acceso en línea:
https://doi.org/10.1109/TBME.2012.2186448
https://repository.urosario.edu.co/handle/10336/27226
Palabra clave:
Kerne
Principal component analysis
Electrocardiography
Eigenvalues and eigenfunctions
Coherence
Correlation
Entropy
Rights
License
Restringido (Acceso a grupos específicos)