采用小波熵和频带能量提取脑电信号特征  

Feature extraction from electroencephalography signal using wavelet entropy and band power

作　　者：王宏[1,2] 赵海滨[2] 刘冲[2] 

机构地区：[1]吉林大学汽车动态模拟国家重点实验室,长春130022 [2]东北大学机械工程与自动化学院,沈阳110004

出　　处：《吉林大学学报（工学版）》2011年第3期828-831,共4页Journal of Jilin University:Engineering and Technology Edition

基　　金：汽车动态模拟国家重点实验室开放基金项目(20071105);国家自然科学基金项目(50435040)

摘　　要：对于采用两种不同意识任务(想象左手运动和想象右手运动)的脑-机接口系统,采用脑电信号的小波熵和频带能量作为组合特征,采用Fisher线性判别分析进行分类,最后采用分类准确率和互信息作为评价标准,进行脑电信号的特征提取离线分析结果表明:该算法在分类准确率和互信息上都取得了良好的识别结果,为脑-机接口系统中意识任务的特征提取和分类提供了新方法。The feature extraction was performed from the electroencephalography signals in the braincomputer interface for two different mental tasks（imagine to move the left land or right hand） using the wavelet entropy and the band power as the combining feature. The Fisher linear discrimination analysis was used to classify the features. The classification accuracy and the mutual information were used as evaluation criteria. The results of off-line analysis showed that the proposed algorithm is characterized by good classification accuracy and mutual information, providing a new way for the feature extraction and classification of the mental tasks in the brain-computer interface.

关 键 词：信息处理技术 脑-机接口 小波熵 线性判别分析 互信息 频带能量 

分 类 号：TN911.6[电子电信—通信与信息系统]