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

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