Ítem
Solo Metadatos
An improved ECG-derived respiration method using kernel principal component analysis
| dc.creator | Caicedo Dorado, Alexander | |
| dc.creator | Varon, Carolina | spa |
| dc.creator | Van Huffel, Sabine | spa |
| dc.creator | Widjaja, Devy | spa |
| dc.date.accessioned | 2020-08-28T15:48:11Z | |
| dc.date.available | 2020-08-28T15:48:11Z | |
| dc.date.created | 2011-09-18 | spa |
| dc.date.issued | 2011 | |
| dc.description.abstract | Recent studies show that principal component analysis (PCA) of heart beats generates well-performing ECG-derived respiratory signals (EDR). This study aims at improving the performance of EDR signals using kernel PCA (kPCA). Kernel PCA is a generalization of PCA where nonlinearities in the data are taken into account for the decomposition. The performance of PCA and kPCA is evaluated by comparing the EDR signals to the reference respiratory signal. Correlation coefficients of 0.630 ± 0.189 and 0.675 ± 0.163, and magnitude squared coherence coefficients at respiratory frequency of 0.819 ± 0.229 and 0.894 ± 0.139 were obtained for PCA and kPCA respectively. The Wilcoxon signed rank test showed statistically significantly higher coefficients for kPCA than for PCA for both the correlation (p = 0.0257) and coherence (p = 0.0030) coefficients. To conclude, kPCA proves to outperform PCA in the extraction of a respiratory signal from single lead ECGs. | eng |
| dc.format.mimetype | application/pdf | |
| dc.identifier.issn | ISSN: 0276-6574 | |
| dc.identifier.issn | EISSN: 2325-8853 | |
| dc.identifier.uri | https://repository.urosario.edu.co/handle/10336/28434 | |
| dc.language.iso | eng | spa |
| dc.publisher | Engineering in Medicine and Biology Society | spa |
| dc.relation.citationTitle | Computing in Cardiology | |
| dc.relation.ispartof | Computing in Cardiology,ISSN: 0276-6574; EISSN: 2325-8853 (2011) | spa |
| dc.relation.uri | https://ieeexplore.ieee.org/abstract/document/6164498 | spa |
| dc.relation.uri | https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edseee&AN=edseee.6164498&lang=es&site=eds-live&scope=site | |
| dc.rights.accesRights | info:eu-repo/semantics/restrictedAccess | |
| dc.rights.acceso | Restringido (Acceso a grupos específicos) | spa |
| dc.source | Computing in Cardiology | spa |
| dc.source.instname | instname:Universidad del Rosario | |
| dc.source.reponame | reponame:Repositorio Institucional EdocUR | |
| dc.subject.keyword | Principal component analysis | spa |
| dc.subject.keyword | Kernel | spa |
| dc.subject.keyword | Electrocardiography | spa |
| dc.subject.keyword | Correlation | spa |
| dc.subject.keyword | Coherence | spa |
| dc.subject.keyword | Sensors | spa |
| dc.subject.keyword | Optimization | spa |
| dc.title | An improved ECG-derived respiration method using kernel principal component analysis | spa |
| dc.title.TranslatedTitle | Un método mejorado de respiración derivado de ECG que utiliza análisis de componentes principales del núcleo | spa |
| dc.type | article | eng |
| dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | |
| dc.type.spa | Artículo | spa |
