传感技术学报2024，Vol.37Issue(9)：1555-1562,8.DOI:10.3969/j.issn.1004-1699.2024.09.012
基于平均能量差的运动想象EEG通道选择和特征提取
Motor Imagery EEG Channel Selection and Feature Extraction Based on Average Energy Difference
摘要
Abstract
Common spatial pattern(CSP)is widely used in the feature extraction of electroencephalogram(EEG).Appropriate channel se-lection can effectively improve the classification performance of CSP and increase the signal-to-noise ratio.Channel selection and feature extraction are performed according to the average energy difference of motor imagery signals.First,the channel mean energy of the two types of motor imagery signals is taken as the voting threshold,and the number of trials with obvious energy differences on each channel is counted according to the voting difference.The channel is normalized by energy features,and then combined with CSP airspace fea-tures to use SVM for classification.In the classification experiments on the BCI Competition Ⅲ Data Sets Ⅳa and BCI Competition Ⅳ Dataset Sets Ⅰ,compared with the full-channel CSP,the average accuracy of the proposed method is increased by 5.7％and 10.9％,and the number of channels is reduced by 74.3％and 51.7％,respectively,which verifies the effectiveness of the proposed channel selection and feature extraction method.关键词
EEG/运动想象/CSP/SVM/通道选择/能量特征Key words
EEG/motor imagery/CSP/SVM/channel selection/energy features分类
信息技术与安全科学引用本文复制引用
孟明,陈思齐,高云园,佘青山..基于平均能量差的运动想象EEG通道选择和特征提取[J].传感技术学报,2024,37(9):1555-1562,8.基金项目
国家自然科学基金项目(62271181,62371171) （62271181,62371171）
