EEG signal classification based on EMD and SVM / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 891-894, 2011.
Artigo
em Chinês
| WPRIM
| ID: wpr-359158
ABSTRACT
The automatic detection and classification of EEG epileptic wave have great clinical significance. This paper proposes an empirical mode decomposition (EMD) and support vector machine (SVM) based classification method for non-stationary EEG. Firstly, EMD was used to decompose EEG into multiple empirical mode components. Secondly, effective features were extracted from the scales. Finally, the EEG was classified with SVM. The experiment indicated that this method could achieve good classification result with accuracy of 99 % for interictal and ictal EEGs.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Processamento de Sinais Assistido por Computador
/
Reconhecimento Automatizado de Padrão
/
Classificação
/
Eletroencefalografia
/
Epilepsia
/
Máquina de Vetores de Suporte
/
Métodos
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2011
Tipo de documento:
Artigo
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