Multivariate evoked response detection based on the spectral F-test
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.1016/j.jneumeth.2016.03.005 http://www.locus.ufv.br/handle/123456789/19371 |
Resumo: | Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed.The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector.The multivariate method showed detection rates consistently higher than those ones when only one signal was used.It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used. |
id |
UFV_c87bef24b80d1a7df712753423c4aa29 |
---|---|
oai_identifier_str |
oai:locus.ufv.br:123456789/19371 |
network_acronym_str |
UFV |
network_name_str |
LOCUS Repositório Institucional da UFV |
repository_id_str |
2145 |
spelling |
Rocha, Paulo Fábio F.Felix, Leonardo B.Sá, Antonio Mauricio F.L. Miranda deMendes, Eduardo M.A.M.2018-05-08T11:13:03Z2018-05-08T11:13:03Z2016-05-0101650270https://doi.org/10.1016/j.jneumeth.2016.03.005http://www.locus.ufv.br/handle/123456789/19371Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed.The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector.The multivariate method showed detection rates consistently higher than those ones when only one signal was used.It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used.engJournal of Neuroscience Methodsv. 264, p. 113-118, may 2016Elsevier B.V.info:eu-repo/semantics/openAccessEEGEvoked responseDetectionSpectral F-testMultivariate detectorMultivariate evoked response detection based on the spectral F-testinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdftexto completoapplication/pdf1184311https://locus.ufv.br//bitstream/123456789/19371/1/artigo.pdf2f01b9a9e9c9599b7fc5f67707ad741eMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/19371/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg4657https://locus.ufv.br//bitstream/123456789/19371/3/artigo.pdf.jpgd7414ae0b06760d955be3a07ad832e53MD53123456789/193712018-05-08 23:00:32.465oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-05-09T02:00:32LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Multivariate evoked response detection based on the spectral F-test |
title |
Multivariate evoked response detection based on the spectral F-test |
spellingShingle |
Multivariate evoked response detection based on the spectral F-test Rocha, Paulo Fábio F. EEG Evoked response Detection Spectral F-test Multivariate detector |
title_short |
Multivariate evoked response detection based on the spectral F-test |
title_full |
Multivariate evoked response detection based on the spectral F-test |
title_fullStr |
Multivariate evoked response detection based on the spectral F-test |
title_full_unstemmed |
Multivariate evoked response detection based on the spectral F-test |
title_sort |
Multivariate evoked response detection based on the spectral F-test |
author |
Rocha, Paulo Fábio F. |
author_facet |
Rocha, Paulo Fábio F. Felix, Leonardo B. Sá, Antonio Mauricio F.L. Miranda de Mendes, Eduardo M.A.M. |
author_role |
author |
author2 |
Felix, Leonardo B. Sá, Antonio Mauricio F.L. Miranda de Mendes, Eduardo M.A.M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Rocha, Paulo Fábio F. Felix, Leonardo B. Sá, Antonio Mauricio F.L. Miranda de Mendes, Eduardo M.A.M. |
dc.subject.pt-BR.fl_str_mv |
EEG Evoked response Detection Spectral F-test Multivariate detector |
topic |
EEG Evoked response Detection Spectral F-test Multivariate detector |
description |
Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed.The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector.The multivariate method showed detection rates consistently higher than those ones when only one signal was used.It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016-05-01 |
dc.date.accessioned.fl_str_mv |
2018-05-08T11:13:03Z |
dc.date.available.fl_str_mv |
2018-05-08T11:13:03Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.1016/j.jneumeth.2016.03.005 http://www.locus.ufv.br/handle/123456789/19371 |
dc.identifier.issn.none.fl_str_mv |
01650270 |
identifier_str_mv |
01650270 |
url |
https://doi.org/10.1016/j.jneumeth.2016.03.005 http://www.locus.ufv.br/handle/123456789/19371 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
v. 264, p. 113-118, may 2016 |
dc.rights.driver.fl_str_mv |
Elsevier B.V. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Elsevier B.V. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Journal of Neuroscience Methods |
publisher.none.fl_str_mv |
Journal of Neuroscience Methods |
dc.source.none.fl_str_mv |
reponame:LOCUS Repositório Institucional da UFV instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
LOCUS Repositório Institucional da UFV |
collection |
LOCUS Repositório Institucional da UFV |
bitstream.url.fl_str_mv |
https://locus.ufv.br//bitstream/123456789/19371/1/artigo.pdf https://locus.ufv.br//bitstream/123456789/19371/2/license.txt https://locus.ufv.br//bitstream/123456789/19371/3/artigo.pdf.jpg |
bitstream.checksum.fl_str_mv |
2f01b9a9e9c9599b7fc5f67707ad741e 8a4605be74aa9ea9d79846c1fba20a33 d7414ae0b06760d955be3a07ad832e53 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV) |
repository.mail.fl_str_mv |
fabiojreis@ufv.br |
_version_ |
1801213103931654144 |