%0 Journal Article
%A ZHANG Xuejun1
%A 2
%A WANG Longqiang1
%A HUANG Wanlu1
%A HUANG Liya1
%A 2
%A CHENG Xiefeng1
%A 2
%T EEG signals feature extraction based on EMD and CSP combined WOSF
%D 2018
%R 10.3778/j.issn.1002-8331.1709-0021
%J Computer Engineering and Applications
%P 149-155
%V 54
%N 24
%X A feature extraction method based on Empirical Mode Decomposition（EMD）, Common Spatial Pattern（CSP） and Wavelength Optimal Spatial Filter（WOSF） is proposed, Firstly, the EMD is used to decompose the EEG signal, and get a set of stationary time series called Intrinsic Mode Functions（IMFs）. Secondly, selecting the appropriate IMFs for signal reconstruction, then the signal can be transformed into optimal signal through WOSF, the optimal signal is mapped to high-dimensional space through CSP, extracting the corresponding feature vector. Finally, the classification is performed using Support Vector Machine（SVM）. After analyzing the result of the 9 subjects, the average accuracy classification rate obtained is over 95%, confirming the feasibility and availability of this method.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1709-0021