Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.1007/s10439-006-9231-4 http://www.locus.ufv.br/handle/123456789/23477 |
Resumo: | The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4). |
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Felix, Leonardo BonatoSá, Antonio Mauricio Ferreira Leite Miranda deInfantosi, Antonio Fernando CatelliYehia, Hani Camille2019-02-11T16:11:10Z2019-02-11T16:11:10Z2007-031573-9686https://doi.org/10.1007/s10439-006-9231-4http://www.locus.ufv.br/handle/123456789/23477The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4).engAnnals of Biomedical EngineeringVolume 35, Issue 3, Pages 443–452, March 2007Biomedical Engineering Societyinfo:eu-repo/semantics/openAccessEEGEvoked responseObjective detectionMultivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf526893https://locus.ufv.br//bitstream/123456789/23477/1/artigo.pdf0e74b8150fc278f0f254ac84673bcd24MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/23477/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/234772019-02-11 13:18:34.37oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-02-11T16:18:34LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
title |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
spellingShingle |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation Felix, Leonardo Bonato EEG Evoked response Objective detection |
title_short |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
title_full |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
title_fullStr |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
title_full_unstemmed |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
title_sort |
Multivariate Objective Response Detectors (MORD): Statistical tools for multichannel eeg analysis during rhythmic stimulation |
author |
Felix, Leonardo Bonato |
author_facet |
Felix, Leonardo Bonato Sá, Antonio Mauricio Ferreira Leite Miranda de Infantosi, Antonio Fernando Catelli Yehia, Hani Camille |
author_role |
author |
author2 |
Sá, Antonio Mauricio Ferreira Leite Miranda de Infantosi, Antonio Fernando Catelli Yehia, Hani Camille |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Felix, Leonardo Bonato Sá, Antonio Mauricio Ferreira Leite Miranda de Infantosi, Antonio Fernando Catelli Yehia, Hani Camille |
dc.subject.pt-BR.fl_str_mv |
EEG Evoked response Objective detection |
topic |
EEG Evoked response Objective detection |
description |
The presence of cerebral evoked responses can be tested by using objective response detectors. They are statistical tests that provide a threshold above which responses can be assumed to have occurred. The detection power depends on the signal-to-noise ratio (SNR) of the response and the amount of data available. However, the correlation within the background noise could also affect the power of such detectors. For a fixed SNR, the detection can only be improved at the expense of using a longer stretch of signal. This can constitute a limitation, for instance, in monitored surgeries. Alternatively, multivariate objective response detection (MORD) could be used. This work applies two MORD techniques (multiple coherence and multiple component synchrony measure) to EEG data collected during intermittent photic stimulation. They were evaluated throughout Monte Carlo simulations, which also allowed verifying that correlation in the background reduces the detection rate. Considering the N EEG derivations as close as possible to the primary visual cortex, if N = 4, 6 or 8, multiple coherence leads to a statistically significant higher detection rate in comparison with multiple component synchrony measure. With the former, the best performance was obtained with six signals (O1, O2, T5, T6, P3 and P4). |
publishDate |
2007 |
dc.date.issued.fl_str_mv |
2007-03 |
dc.date.accessioned.fl_str_mv |
2019-02-11T16:11:10Z |
dc.date.available.fl_str_mv |
2019-02-11T16:11:10Z |
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/10.1007/s10439-006-9231-4 http://www.locus.ufv.br/handle/123456789/23477 |
dc.identifier.issn.none.fl_str_mv |
1573-9686 |
identifier_str_mv |
1573-9686 |
url |
https://doi.org/10.1007/s10439-006-9231-4 http://www.locus.ufv.br/handle/123456789/23477 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 35, Issue 3, Pages 443–452, March 2007 |
dc.rights.driver.fl_str_mv |
Biomedical Engineering Society info:eu-repo/semantics/openAccess |
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Biomedical Engineering Society |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Annals of Biomedical Engineering |
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Annals of Biomedical Engineering |
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LOCUS Repositório Institucional da UFV |
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