垂足是中風常見的病症之一，主因為踝關節背屈肌無力或蹠屈肌張力過強，前者造成中風病患步行速度變慢及單腳站立時間不對稱，而蹠屈肌群痙攣則造成步伐不對稱。為改善中風病患垂足及控制能力，本研究目的為應用先前發展之肌電圖控制機器人搭配常人的步態模型，訓練中風病患踝關節背屈肌群及蹠屈肌群的控制能力。
首先分析常人步態之踝關節力矩及角度變化，找出脛骨前肌和比目魚肌於走路時之活化順序，並計算此兩條肌肉對踝關節力矩的共同收縮比例。復健機器人可依據患者脛骨前肌和比目魚肌肌電圖訊號估測之合力矩與常人踝關節力矩的誤差給予阻力或助力。另外當脛骨前肌與比目魚肌須共同活化時如站立期，機器人施加振動力矩於病患踝關節並配合視覺回授以誘發患者此兩條肌肉之共同收縮，使患者能在機器人上模擬常人上述兩條肌肉之協調。為了取得受測者的步態資訊，本研究以自製的電子量角器及足底開關來測量受測者於跑步機上行走時，踝關節的角度變化與步態週期做為訓練前、後的步態評估。
本研究徵召一位中風病患進行4週11次的訓練，結果顯示，中風病患的脛骨前肌和比目魚肌肌電圖訊號經處理其合力矩近似常人踝節力矩，脛骨前肌與比目魚肌出力可達期望力矩值，而且藉由抑制振動及視覺回授，可以誘發中風病患脛骨前肌和比目魚肌產生共同收縮，訓練後於跑步機上所擷取的步態資料也顯示患側步態的穩定性有改善。本研究發現藉由人機之間互動可以提升患者的肌力及肌肉間的協調性，以提高其踝關節的控制力及改善垂足。

Foot drop, a common symptom of the stroke, may due to weaken dorsi-flexors or hypertonic plantar-flexors of the ankle. It often results in reduced controllability and stability of ankle and asymmetric single limb stance time and slow walking speed. In previous work, the EMG of tibialis anterior and soleus were employed to control an ankle rehabilitation robot. To improve the stroke patient’s motor controllability, the robotic system was improved for training the ankle control of stroke patients and for restoring their gait.
At first, tibialis anterior and soleus activation training patterns in level walking were found by analyzing the torque pattern and ankle angle of normal gait. Then, the co-contraction rate was calculated by these two torque pattern in stance phase. The ankle robot provides assisting torque or resisting torque to the affected ankle according to the error between the EMG-estimated resultant torque and the training pattern. Besides, it applies different magnitudes of vibration, combined with visual feedback, to induce desired co-contraction of tibialis anterior and soleus for patients in stance phase. In this thesis, the scaled ankle angle and torque patterns of tibialis anterior and soleus of normal gait are utilized as the training targets for stroke patients. To assess the gait patterns of the subject before and after training, an electric goniometer was made to record the range of motion of ankle, and a pair of foot switches were utilized to determine the temple of gait. A stroke patient with foot drop was recruited to perform eleven sessions of rehabilitation training program in four weeks.
Testing results revealed that resultant torque approximated the desired ankle torque and the estimated torques of tibialis anterior and soleus could reach the desired torques during training process. In addition, by applying vibration combined with visual feedback the robot could really induce co-contraction of tibialis anterior and soleus for subject. After training, the gait pattern acquired from the treadmill revealed that the stability and controllability of affected muscles were improved. In conclusion, the robot could strengthen tibialis anterior and improve the coordination of ankle muscles and the foot drop.

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