The Comparison of EEG Feature Extraction of Motor Imagery between CSP Algorithm and Wavelet Packet Analysis
WU Linyan
LU Hao
GAO Nuo
WANG Tao
Abstract：The rapid and accurate extraction of motor imagery feature of EEG signals is an important issue in brain computer interface (BCI) research.This paper discussed the theory of common spatial pattern(CSP) and wavelet packet analysis in feature extraction of two classes motion imagery.For the data provided byGRAZ university, the highest classify accuracy with CSP and support vector machines (SVM) was 85.5%;the wavelet packet analysis classify accuracy was 99%.And the accuracy to classify the data by emotiv epoc+ system by wavelet packet analysis and SVM could reach 98%.Experimental results show that, compared to CSP algorithm, wavelet packet analysis is better for feature extraction.
Keywords：Wavelet packet analysisCommon space model (CSP)Support vector machines (SVM)Brain computer interface(BCI)Motor imagery(MI)
Publication Date：2017-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：5( 224-228 )