Decoding Human Right and Left Hand Motor Imagery from EEG Single Trials using Sample Entropy

摘要：

This study aims to researching whether human intentions to move left and right hands can be decoded from Sample Entropy (SampEn) features in noninvasive EEG. Eleven healthy subjects participated in the experiment. We found the a waves SampEn value of imagined left hand movement is larger than imagined right hand movement in most of male electrodes , especially F3, C3 and T3,and the a waves SampEn value of imagined right hand movement is larger than imagined left hand movement in most of female electrodes , especially Fpl and P3. Experiment results show that SampEn can express the EEG dynamic features of imagined left and right hand movement. Besides it has clear physiological significance. Fisher discriminator analysis is utilized to dynamically classify imagined left and right hand movement according to SampEn features. As a result, we gained a male average maximum classification accuracy of 76.97％. Lastly, we discussed the influence of different time length and t value on the classification accuracy.

关键词： Sample Entropy Brain computer interface (BCI) EEG Fisher discriminator

作者: Zhihua Chen Hong Zhou Li Zhao

作者单位: AI & Bioinformatics Technology Laboratory,Software Technology Institute of Dalian Jiaotong University Dalian 116052, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 1269-1272

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）