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Use este identificador para citar ou linkar para este item: https://www.repositorio.mar.mil.br/handle/ripcmb/847026
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dc.contributor.authorIssmael Junior, Ali Kamel-
dc.contributor.authorManhães, Aline Gesualdi-
dc.contributor.authorCalvano, José Vicente-
dc.date.accessioned2024-07-08T13:43:50Z-
dc.date.available2024-07-08T13:43:50Z-
dc.date.issued2017-
dc.identifier.urihttps://www.repositorio.mar.mil.br/handle/ripcmb/847026-
dc.descriptionEvent-Related Potentials (ERP) are biological electrical signals synchronized with sensory, cognitive or motor stimuli and measured by electroencephalographs (EEG). ERP technique allows non-invasive analysis of brain functions. Based on the results obtained by Soto [1], this work extracts ERP parameters using EEGLAB® and ERPLAB® tools based on Matlab® software [6], [7], [8], [9]. The result of the research was the obtaining of supervised and unsupervised classification scenarios for the classes proposed in the mentioned experiment and the comparative study and discussion of the classification results found, using the methodology proposed by Webb [2]. This article presents the results obtained with unsupervised classification scenarios only and the supervised classification scenarios will be presented in future. The results achieved accuracies very near from the equiprobability, indicating that the use of unsupervised classifiers approaches considered are not adequate to classify Soto’s data [1]. This study is innovative in the area of Neurolinguistics, since, at least until now, there are no similar previously published works on the subject found in research databases such as: IEEExplorer; Web of Science; Elesevier and Spring. The results open the possibility of analyzing signals from individuals with this ERP methodology associated to Pattern Recognition, with the possible application of this type of analysis in diagnostic tools, assessment of language learning, among others.pt_BR
dc.language.isoen_USpt_BR
dc.publisherXXXV Simpósio Brasileiro de Telecomunicações e Processamento de Sinaispt_BR
dc.rightsopenAccesspt_BR
dc.subjectERPpt_BR
dc.subjectEEGpt_BR
dc.subjectPattern recognitionpt_BR
dc.subjectLinguisticspt_BR
dc.titleApplication of pattern recognition method in a linguistic experiment with unsupervised classificationpt_BR
dc.typeconferenceObjectpt_BR
dc.identifier.doihttp://dx.doi.org/10.14209/sbrt.2017.18-
dc.subject.dgpmEngenharia elétricapt_BR
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