Publication
On the Use of KPCA to Extract Artifacts in One-Dimensional Biomedical Signals
dc.contributor.author | Teixeira, Ana | |
dc.contributor.author | Tome, A. | |
dc.contributor.author | Lang, E. | |
dc.contributor.author | Schachtner, R. | |
dc.contributor.author | Stadlthanner, K. | |
dc.date.accessioned | 2023-10-23T10:20:18Z | |
dc.date.available | 2023-10-23T10:20:18Z | |
dc.date.issued | 2006 | |
dc.description.abstract | Kernel principal component analysis(KPCA) is a nonlinear projective technique that can be applied to decompose multi-dimensional signals and extract informative features as well as reduce any noise contributions. In this work we extend KPCA to extract and remove artifact-related contributions as well as noise from one-dimensional signal recordings. We introduce an embedding step which transforms the one-dimensional signal into a multi-dimensional vector. The latter is decomposed in feature space to extract artifact related contaminations. We further address the preimage problem and propose an initialization procedure to the fixed-point algorithm which renders it more efficient. Finally we apply KPCA to extract dominant Electrooculogram (EOG) artifacts contaminating Electroencephalogram (EEG) recordings in a frontal channel. | pt_PT |
dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.doi | 10.1109/MLSP.2006.275580 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10400.26/47391 | |
dc.language.iso | eng | pt_PT |
dc.publisher | [IEEE] | pt_PT |
dc.title | On the Use of KPCA to Extract Artifacts in One-Dimensional Biomedical Signals | pt_PT |
dc.type | conference object | |
dspace.entity.type | Publication | |
oaire.citation.conferencePlace | [Maynooth] | pt_PT |
oaire.citation.endPage | 390 | pt_PT |
oaire.citation.startPage | 385 | pt_PT |
oaire.citation.title | 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing | pt_PT |
person.familyName | Teixeira | |
person.givenName | Ana | |
person.identifier.ciencia-id | D619-A151-8BE2 | |
person.identifier.orcid | 0000-0002-8120-0148 | |
person.identifier.rid | A-3100-2014 | |
person.identifier.scopus-author-id | 7202385348 | |
rcaap.rights | openAccess | pt_PT |
rcaap.type | conferenceObject | pt_PT |
relation.isAuthorOfPublication | c1ff686d-c3d3-4658-96c6-a1f62a52777a | |
relation.isAuthorOfPublication.latestForDiscovery | c1ff686d-c3d3-4658-96c6-a1f62a52777a |
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