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采用小波熵和频带能量提取脑电信号特征
引用本文:王宏,赵海滨,刘冲.采用小波熵和频带能量提取脑电信号特征[J].吉林大学学报(工学版),2011,41(3):828-831.
作者姓名:王宏  赵海滨  刘冲
作者单位:1. 吉林大学汽车动态模拟国家重点实验室,长春130022;东北大学机械工程与自动化学院,沈阳110004
2. 东北大学机械工程与自动化学院,沈阳,110004
基金项目: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。

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

Feature extraction from electroencephalography signal using wavelet entropy and band power
WANG Hong,ZHAO Hai-bin,LIU Chong.Feature extraction from electroencephalography signal using wavelet entropy and band power[J].Journal of Jilin University:Eng and Technol Ed,2011,41(3):828-831.
Authors:WANG Hong  ZHAO Hai-bin  LIU Chong
Affiliation:WANG Hong1,2,ZHAO Hai-bin2,LIU Chong2(1.State Key Laboratory of Automobile Dynamic Simulation,Jilin University,Changchun 130022,China,2.School of Mechanical Engineering and Automation,Northeastern University,Shenyang 110004,China)
Abstract:The feature extraction was performed from the electroencephalography signals in the brain-computer 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 ...
Keywords:information processing  brain-computer interface  wavelet entropy  linear discrimination analysis  mutual information  band power  
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