计算机工程与科学2017，Vol.39Issue(7)：1385-1390,6.DOI:10.3969/j.issn.1007-130X.2017.07.028
基于ERS/ERD的二级共空间模式的运动想象脑电信号特征提取
Feature extraction of motor imagery EEG of two layers common spatial pattern based on ERS/ERD
摘要
Abstract
In order to solve the problem that the classification recognition rate of the multi-class motor imagery EEG signals is low and that there is difference among subjects in the brain-computer interface,we propose a feature extraction method based on the ERS/ERD phenomenon for the two level common spatial pattern.Firstly,we select the EEG of all channels and make wavelet packet de-noising and decomposition (WPD) of specific frequency bands.Secondly,we conduct common spatial pattern (CSP)on the signals of reconstructed decomposition coefficients to obtain spatial filtering devices for the two classes of hands (left,right) and feet (feet,tongue),and use the 2-norm screening criteria to extract N leads of the heavily weighted factor.Thirdly,the projection matrix of the optimized leads are used to filter hands (left,right) and feet (feet,tongue),and the signals which are regard as the original signals are used to conduct two layers common spatial pattern.Finally,feature vectors are categorized by the support vector machine (SVM).The highest classification accuracy rate of the simulation on three subjects from BCI2005Ⅲa reaches 92.55％,and the simulation results show that the proposal has a good effect on the feature extraction of EEG signals.关键词
小波包分解/二级共空间模式/特征提取/支持向量机Key words
wavelet packet decomposition (WPD)/two layers common spatial pattern (CSP)/feature extraction/support vector machine (SVM)分类
信息技术与安全科学引用本文复制引用
尚允坤,段锁林,潘礼正..基于ERS/ERD的二级共空间模式的运动想象脑电信号特征提取[J].计算机工程与科学,2017,39(7):1385-1390,6.基金项目
江苏省科技支撑计划项目(社会发展)(BEK2013671) （社会发展）
