Executed movement using EEG signals through a naive bayes classifier
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/267619 |
Resumo: | Recent years have witnessed a rapid development of brain-computer interface (BCI) technology. An independent BCI is a communication system for controlling a device by human intension, e.g., a computer, a wheelchair or a neuroprosthes is, not depending on the brain’s normal output pathways of peripheral nerves and muscles, but on detectable signals that represent responsive or intentional brain activities. This paper presents a comparative study of the usage of the linear discriminant analysis (LDA) and the naive Bayes (NB) classifiers on describing both right- and left-hand movement through electroencephalographic signal (EEG) acquisition. For the analysis, we considered the following input features: the energy of the segments of a band pass-filtered signal with the frequency band in sensorimotor rhythms and the components of the spectral energy obtained through the Welch method. We also used the common spatial pattern (CSP) filter, so as to increase the discriminatory activity among movement classes. By using the database generated by this experiment, we obtained hit rates up to 70%. The results are compatible with previous studies. |
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Machado, Juliano CostaBalbinot, Alexandre2023-11-25T03:26:19Z20142072-666Xhttp://hdl.handle.net/10183/267619000946544Recent years have witnessed a rapid development of brain-computer interface (BCI) technology. An independent BCI is a communication system for controlling a device by human intension, e.g., a computer, a wheelchair or a neuroprosthes is, not depending on the brain’s normal output pathways of peripheral nerves and muscles, but on detectable signals that represent responsive or intentional brain activities. This paper presents a comparative study of the usage of the linear discriminant analysis (LDA) and the naive Bayes (NB) classifiers on describing both right- and left-hand movement through electroencephalographic signal (EEG) acquisition. For the analysis, we considered the following input features: the energy of the segments of a band pass-filtered signal with the frequency band in sensorimotor rhythms and the components of the spectral energy obtained through the Welch method. We also used the common spatial pattern (CSP) filter, so as to increase the discriminatory activity among movement classes. By using the database generated by this experiment, we obtained hit rates up to 70%. The results are compatible with previous studies.application/pdfengMicromachines. Basel, Switzerland. Vol. 5, no. 4 (Dec. 2014), p. 1082-1105Processamento de sinaisInteração homem-computadorEletroencefalografiaNaive BayesLinear discriminant analysisWelch methodBrain computer interfaceExecuted movement using EEG signals through a naive bayes classifierEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT000946544.pdf.txt000946544.pdf.txtExtracted Texttext/plain62656http://www.lume.ufrgs.br/bitstream/10183/267619/2/000946544.pdf.txtddd5b42f439ac3591e7c6c51f94cf87cMD52ORIGINAL000946544.pdfTexto completo (inglês)application/pdf1844807http://www.lume.ufrgs.br/bitstream/10183/267619/1/000946544.pdfb51a622d600eea0c44aff1af467bf4fcMD5110183/2676192023-12-06 04:24:42.648339oai:www.lume.ufrgs.br:10183/267619Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-12-06T06:24:42Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Executed movement using EEG signals through a naive bayes classifier |
title |
Executed movement using EEG signals through a naive bayes classifier |
spellingShingle |
Executed movement using EEG signals through a naive bayes classifier Machado, Juliano Costa Processamento de sinais Interação homem-computador Eletroencefalografia Naive Bayes Linear discriminant analysis Welch method Brain computer interface |
title_short |
Executed movement using EEG signals through a naive bayes classifier |
title_full |
Executed movement using EEG signals through a naive bayes classifier |
title_fullStr |
Executed movement using EEG signals through a naive bayes classifier |
title_full_unstemmed |
Executed movement using EEG signals through a naive bayes classifier |
title_sort |
Executed movement using EEG signals through a naive bayes classifier |
author |
Machado, Juliano Costa |
author_facet |
Machado, Juliano Costa Balbinot, Alexandre |
author_role |
author |
author2 |
Balbinot, Alexandre |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Machado, Juliano Costa Balbinot, Alexandre |
dc.subject.por.fl_str_mv |
Processamento de sinais Interação homem-computador Eletroencefalografia |
topic |
Processamento de sinais Interação homem-computador Eletroencefalografia Naive Bayes Linear discriminant analysis Welch method Brain computer interface |
dc.subject.eng.fl_str_mv |
Naive Bayes Linear discriminant analysis Welch method Brain computer interface |
description |
Recent years have witnessed a rapid development of brain-computer interface (BCI) technology. An independent BCI is a communication system for controlling a device by human intension, e.g., a computer, a wheelchair or a neuroprosthes is, not depending on the brain’s normal output pathways of peripheral nerves and muscles, but on detectable signals that represent responsive or intentional brain activities. This paper presents a comparative study of the usage of the linear discriminant analysis (LDA) and the naive Bayes (NB) classifiers on describing both right- and left-hand movement through electroencephalographic signal (EEG) acquisition. For the analysis, we considered the following input features: the energy of the segments of a band pass-filtered signal with the frequency band in sensorimotor rhythms and the components of the spectral energy obtained through the Welch method. We also used the common spatial pattern (CSP) filter, so as to increase the discriminatory activity among movement classes. By using the database generated by this experiment, we obtained hit rates up to 70%. The results are compatible with previous studies. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2023-11-25T03:26:19Z |
dc.type.driver.fl_str_mv |
Estrangeiro 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://hdl.handle.net/10183/267619 |
dc.identifier.issn.pt_BR.fl_str_mv |
2072-666X |
dc.identifier.nrb.pt_BR.fl_str_mv |
000946544 |
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2072-666X 000946544 |
url |
http://hdl.handle.net/10183/267619 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Micromachines. Basel, Switzerland. Vol. 5, no. 4 (Dec. 2014), p. 1082-1105 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
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