中風是一種急性腦血管疾病，常造成神經損傷失去運動控制的能力，使病患肢體無法自主運動。針對中風病人的復健治療，藉由機器人對於下肢肌肉神經的誘發，以及利用視覺回饋引導病患作想像的動作，誘發腦部電位產生變化，同時刺激大腦和中樞神經的連結路徑，產生神經復健的療效。
因此本研究的主要目的是整合人腦-電腦介面(Brain Computer Interface, BCI)和下肢復健機器人之新型復健系統。本研究擷取受測者C3、C4的腦波變化，以大腦皮質運動區波為基礎的人機介面系統。經過訊號前處理及辨識器產生復健機器人的控制命令，使用腦波當成機器人作動的觸發訊號。
在實驗中，第一步驟先讓受測者熟悉BCI的使用，作為訓練模式。接著才要求受測者把腳放在機器上，在想像辨識成功後，由機器帶領下肢進行復健動作，做模擬復健的實驗。本研究以單一常人為受測者，由實驗結果發現，經過5週的訓練之後，人腦電腦介面實驗的成功率有進步的趨勢(40%~67.5%)；在訓練之後，常人模擬復健實驗的成功率可達80%。

Stroke is an acute cerebrovascular disease. Stroke patients suffer from movement disabilities as the result of neurological injuries. In the rehabilitation of stroke patients, the connection between brain and the central nervous system is often facilitated by stretch of muscles from robot and potential reorganization in the brain from visual biofeedback.

The aim of this study is to integrate a BCI and a lower limb rehabilitation robot to develop a new rehabilitation system. The brain-computer interface is based on the  wave of motor cortex detected from the C3 and C4 area. Signal preprocessing methods including reducing of spikes generated from robot motors and filtering by an optimal bandpass filter and a classifier are developed to generate a command for robot. In other words, the EEG signal is used as a trigger for controlling movement of the robot.

In the beginning of the study, the subject is familiar with the use of BCI. After training mode, subjects are asked to put his/her lower limb on the robot. And the robot can be driven to guide the patients’ lower extremity to exercise by thoughts of the subjects. The experimental results from one normal subject showed that for the training mode the success rate could be improved after five weeks of usage (40% to 67.5%). While for the test experiments the success rate is about 80%.

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