The feature extraction and recognition of EEG based on wavelet entropy and distance

Author

Yuge, Sun ; Ning, Ye ; Xinhe, Xu

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang

fYear

2008

fDate

2-4 July 2008

Firstpage

4294

Lastpage

4298

Abstract

The paper is based on the technique of brain-computer interface to investigate the EEG of different mental tasks. The wavelet entropy algorithm is applied to realize the feature extraction for the two mental tasks. The Euclidean distance discriminant is proposed to classify the two metal tasks efficiently and the result is perfect. The recognition rate is up to 96.97%. The research is valuable and significant in the realization of control and communication based on the mental tasks in BCI.

Keywords

biology computing; electroencephalography; entropy; feature extraction; pattern classification; wavelet transforms; EEG; Euclidean distance discriminant; brain-computer interface; electroencephalography; feature extraction; mental task; wavelet entropy algorithm; Brain computer interfaces; Educational institutions; Electroencephalography; Electrooculography; Entropy; Euclidean distance; Feature extraction; Independent component analysis; Information science; Sun; Brain-Computer Interface; EEG; Euclidean distance; Feature extraction; Recognition; Wavelet entropy;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2008. CCDC 2008. Chinese

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-1733-9

Electronic_ISBN

978-1-4244-1734-6

Type

conf

DOI

10.1109/CCDC.2008.4598140

Filename

4598140