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...
- 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)