【作者】 叶坤；

【导师】 骆清铭；

【作者基本信息】 华中科技大学 ， 生物医学工程， 2008， 硕士

【摘要】 脑机接口(BCI)技术给肢体运动残疾人带来了康复的希望,基于脑电的BCI系统更是因为其结构简单,信号采集容易以及方便携带和无损成为研究的热点。本文首先介绍了脑电信号的特征、脑机接口的概念和目前国内外的研究情况,在参考国外BCI实验范式的基础上对左右手运动想象的脑电采集的方法进行了探索,利用Presentation编写了运动想象提示程序“Visual Guide”,训练被试,并成功采集到左右手运动想象的脑电特征信号,成功采集率83%。为了实现运动想象意识信号特征的有效提取,我们对采集到的脑电信号进行了信号的预处理,并对信号进行了频域分析、时域分析、时频联合分析,依据时频信号的分析结果利用小波对特征信号进行了有效的提取。通过频域数据分析我们发现了C3和C4处脑电信号能量在10Hz附近有最大的区分,通过时域分析证明10Hz的C3和C4电极信号确实与左右手运动想象提示相关。时频联合分析进一步证明了此结论。根据这些时频域特征,我们用Morlet小波对原始脑电信号进行分解,成功提取了特征信号。更多还原

【Abstract】 The advancement of Brain-Computer interface (BCI) study brings hopes of rehabilitation to the handicapped. And the BCI based on electroencephalograph has been a hotspot for the BCI study, because of its simple structure, safety and convenience of signal acquisition and portage.In this thesis, the characters of the Electroencephalogram (EEG) signal, the concept of the BCI , the domestic and international research status of BCI were introduced first. Then the paradigm of our own was groped for after the paradigm of the movement imagination studies of the groups oversea being studied, and the program‘Visual Guide’for visual cues of the hands movement imagination was made. Testees were trained with this program and the signal with enough distinction was acquired finally with the successful rate of 83%.For the goal that features of the signal would be extracted effectively, the signal acquired previously was pretreated, and then the signal was analyzed in frequency domain , time domain and time-frequency domain. Through frequency domain analysis, the signal got from C3 and C4 had greatest distinction about the 10Hz, and the signal of 10Hz had correlation with the cues of left hand and right hand movement imagination through time domain analysis. And the time-frequency analysis had further sustained the conclusion. With the features that we got from the time-frequency domain analysis, the original signal was decomposed and the signal with the features was extracted successfully through the Morlet wavelet transformation.更多还原