Single trial classification of motor imagery electroencephalogram based on Fisher criterion / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 774-778, 2018.
Artigo
em Chinês
| WPRIM
| ID: wpr-687563
ABSTRACT
In order to realize brain-computer interface (BCI), optimal features of single trail motor imagery electroencephalogram (EEG) were extracted and classified. Mu rhythm of EEG was obtained by preprocessing, and the features were optimized by spatial filtering, which are estimated from a set of data by method of common spatial pattern. Classification decision can be made by Fisher criterion, and classification performance can be evaluated by cross validation and receiver operating characteristic (ROC) curve. Optimal feature dimension determination projected by spatial filter was discussed deeply in cross-validation way. The experimental results show that the high discriminate accuracy can be guaranteed, meanwhile the program running speed is improved. Motor imagery intention classification based on optimized EEG feature provides difference of states and simplifies the recognition processing, which offers a new method for the research of intention recognition.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Tipo de estudo:
Estudo prognóstico
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2018
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS