Influences of the signal border extension in the discrete wavelet transform in EEG spike detection
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research on Biomedical Engineering (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000300253 |
Resumo: | Abstract Introduction The discrete wavelet transform is used in many studies as signal preprocessor for EEG spike detection. An inherent process of this mathematical tool is the recursive wavelet convolution over the signal that is decomposed into detail and approximation coefficients. To perform these convolutions, firstly it is necessary to extend signal borders. The selection of an unsuitable border extension algorithm may increase the false positive rate of an EEG spike detector. Methods In this study we analyzed nine different border extensions used for convolution and 19 mother wavelets commonly seen in other EEG spike detectors in the literature. Results The border extension may degrade an EEG spike detector up to 44.11%. Furthermore, results behave differently for distinct number of wavelet coefficients. Conclusion There is not a best border extension to be used with any EEG spike detector based on the discrete wavelet transform, but the selection of the most adequate border extension is related to the number of coefficients of a mother wavelet. |
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Research on Biomedical Engineering (Online) |
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Influences of the signal border extension in the discrete wavelet transform in EEG spike detectionEEGSpikeBorder extensionDiscrete wavelet transformLDAAbstract Introduction The discrete wavelet transform is used in many studies as signal preprocessor for EEG spike detection. An inherent process of this mathematical tool is the recursive wavelet convolution over the signal that is decomposed into detail and approximation coefficients. To perform these convolutions, firstly it is necessary to extend signal borders. The selection of an unsuitable border extension algorithm may increase the false positive rate of an EEG spike detector. Methods In this study we analyzed nine different border extensions used for convolution and 19 mother wavelets commonly seen in other EEG spike detectors in the literature. Results The border extension may degrade an EEG spike detector up to 44.11%. Furthermore, results behave differently for distinct number of wavelet coefficients. Conclusion There is not a best border extension to be used with any EEG spike detector based on the discrete wavelet transform, but the selection of the most adequate border extension is related to the number of coefficients of a mother wavelet.Sociedade Brasileira de Engenharia Biomédica2016-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000300253Research on Biomedical Engineering v.32 n.3 2016reponame:Research on Biomedical Engineering (Online)instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)instacron:SBEB10.1590/2446-4740.01815info:eu-repo/semantics/openAccessPacola,Edras ReilyQuandt,Veronica IsabelaLiberalesso,Paulo Breno NoronhaPichorim,Sergio FranciscoGamba,Humberto RemigioSovierzoski,Miguel Antonioeng2016-10-24T00:00:00Zoai:scielo:S2446-47402016000300253Revistahttp://www.rbejournal.org/https://old.scielo.br/oai/scielo-oai.php||rbe@rbejournal.org2446-47402446-4732opendoar:2016-10-24T00:00Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)false |
dc.title.none.fl_str_mv |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
title |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
spellingShingle |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection Pacola,Edras Reily EEG Spike Border extension Discrete wavelet transform LDA |
title_short |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
title_full |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
title_fullStr |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
title_full_unstemmed |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
title_sort |
Influences of the signal border extension in the discrete wavelet transform in EEG spike detection |
author |
Pacola,Edras Reily |
author_facet |
Pacola,Edras Reily Quandt,Veronica Isabela Liberalesso,Paulo Breno Noronha Pichorim,Sergio Francisco Gamba,Humberto Remigio Sovierzoski,Miguel Antonio |
author_role |
author |
author2 |
Quandt,Veronica Isabela Liberalesso,Paulo Breno Noronha Pichorim,Sergio Francisco Gamba,Humberto Remigio Sovierzoski,Miguel Antonio |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Pacola,Edras Reily Quandt,Veronica Isabela Liberalesso,Paulo Breno Noronha Pichorim,Sergio Francisco Gamba,Humberto Remigio Sovierzoski,Miguel Antonio |
dc.subject.por.fl_str_mv |
EEG Spike Border extension Discrete wavelet transform LDA |
topic |
EEG Spike Border extension Discrete wavelet transform LDA |
description |
Abstract Introduction The discrete wavelet transform is used in many studies as signal preprocessor for EEG spike detection. An inherent process of this mathematical tool is the recursive wavelet convolution over the signal that is decomposed into detail and approximation coefficients. To perform these convolutions, firstly it is necessary to extend signal borders. The selection of an unsuitable border extension algorithm may increase the false positive rate of an EEG spike detector. Methods In this study we analyzed nine different border extensions used for convolution and 19 mother wavelets commonly seen in other EEG spike detectors in the literature. Results The border extension may degrade an EEG spike detector up to 44.11%. Furthermore, results behave differently for distinct number of wavelet coefficients. Conclusion There is not a best border extension to be used with any EEG spike detector based on the discrete wavelet transform, but the selection of the most adequate border extension is related to the number of coefficients of a mother wavelet. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-09-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000300253 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000300253 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2446-4740.01815 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Engenharia Biomédica |
publisher.none.fl_str_mv |
Sociedade Brasileira de Engenharia Biomédica |
dc.source.none.fl_str_mv |
Research on Biomedical Engineering v.32 n.3 2016 reponame:Research on Biomedical Engineering (Online) instname:Sociedade Brasileira de Engenharia Biomédica (SBEB) instacron:SBEB |
instname_str |
Sociedade Brasileira de Engenharia Biomédica (SBEB) |
instacron_str |
SBEB |
institution |
SBEB |
reponame_str |
Research on Biomedical Engineering (Online) |
collection |
Research on Biomedical Engineering (Online) |
repository.name.fl_str_mv |
Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB) |
repository.mail.fl_str_mv |
||rbe@rbejournal.org |
_version_ |
1752126288627236864 |