Multivariate evoked response detection based on the spectral F-test

Detalhes bibliográficos
Autor(a) principal: Rocha, Paulo Fábio F.
Data de Publicação: 2016
Outros Autores: Felix, Leonardo B., Sá, Antonio Mauricio F.L. Miranda de, Mendes, Eduardo M.A.M.
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.
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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
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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
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dc.publisher.none.fl_str_mv Journal of Neuroscience Methods
publisher.none.fl_str_mv Journal of Neuroscience Methods
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