本實驗室前人之研究致力於應用腦波控制矯型手進行中風病患之動作想像訓練，並藉著多通道訊號的離線分析，觀察訓練前後大腦重塑之現象，然而前人所採用之腦波特徵於想像事件之間的差異並不明顯，並且易受到雜訊干擾，影響特徵識別的結果。因此本研究利用空間濾波(spatial filter)的方法，找出大腦於事件想像過程中事件差異較為顯著的特徵訊號，取代以往研究所使用之特徵，提高動作想像的腦波辨識度，並引入本實驗室前人所發展的腦機介面(brain-computer-interface, BCI)控制矯型手之復健系統，以此系統對3名受測者進行長時間的動作想像訓練。將訓練過程中所擷取之多通道腦波，透過R-value分析腦波能量與動作事件的相關性，另外經由相位斜率指標(phase-slope index, PSI)分析，建立大腦連結，以此兩種指標觀察大腦重塑之現象。
研究結果顯示，藉由共同空間型樣(common spatial pattern, CSP) 法篩選出適當的特徵訊號，受測者可以在訓練過程中逐漸提高想像成功率，並且藉由區域性的大腦重塑現象與想像成功率相互對應的結果，可以更明顯地觀察到人腦於訓練過程中，確實經由學習而產生聯結結構重塑。

In our previous study, we applied EEG signal to control orthotic hands for imagery training of stroke patients, and then explore the reorganization of brain by offline analysis of multi-channel EEG. However, the difference of feature between events we used wasn’t obvious and was easily interfered by noise, both effected the results of identification. Hence, we finding the significant features of event-related imagery by spatial filter to replace the feature we used previously and using a brain-computer-interface (BCI) controlled robot system which has been developed in our previous study to proceed the BCI training.　Three subjects recruited in this study. With multi-channel EEG recorded during the training, R-value which was employed to compute the correlation between EEG power and the motor imagery was computed and an EEG-based brain network was also constructed to explore the plasticity of brain.
The results of this study showed that the accuracy of control has gradually increased during training with suitably selected features by common spatial pattern (CSP) method. And the regional reorganization of brain supported the accuracy of control which indicated that the brain can be plastically modified by BCI training.

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