自動化神經發展治療步態訓練機之研發

Abstract

本論文針對中風患者的復健，開發一套自動化神經發展治療(Neuro Developmental Treatment; NDT) 步態訓練機。中風後的照護與醫療復健是一筆龐大的負擔，NDT步態訓練整合各種支撐、誘發、引導、與抑制等手法，對於腦中風病患是相當有效的復健方式，然而對於治療師而言，實施這種治療方式相當耗時費力；對於病患而言，則因訓練本身的複雜度及練習時間受限，因此臨床上實際NDT訓練的質與量皆相當不夠，故本論文開發一套自動化NDT步態訓練機，降低治療師的負擔並同時增加中風患者的訓練時間，以提升NDT訓練的效果。 我們首先取得治療師與病人進行訓練時的各種行為量化資訊，將臨床know-how轉譯建立治療師專家系統，而後建立一套自動化系統，設計適當的控制法則遵循此專家系統，學習並且重複治療師的動作。為了能提供良好系統響應，吾人以實驗方式進行系統鑑別，建立數學模型，並針對此模型設計PID控制器與強韌控制器，以準確地複製治療師的動作。 最後，我們徵召中風患者，進行NDT步態訓練，並定義效果指標，驗證所發展的自動化NDT步態訓練機對於中風的復健的效果。

This thesis develops an automated device that can assist Neuro-Developmental Treatment (NDT) training. The rehabilitation expenditure for stroke patients is a heavy load to the society and individuals. NDT training is a way to let patients have the feeling on walking with minimal intervention, and it is shown to be an effective rehabilitation method for stroke patients. During the NDT training, the therapists need to stabilize the patients’ trunk and pelvis, to stimulate the weight shift and pelvic rotation, and to assist the limb control during the stance and swing phases to increase their walking ability. Therefore, NDT training is very labor-intensive for therapists. Consequently, patients normally receive insufficient NDT gait training and delay rehabilitation processes because of the lack of therapist’s assistance. Hence, this thesis develops a machine-aided NDT gait trainer to relief the therapists’ working loads and to improve the rehabilitation effects of stroke patients. First, we measure the position and force data from clinical NDT gait training, and develop an expert system. Second, we develop motor mechanisms to repeat the therapists’ action based on the expert system. In order to improve the system responses, we derive the transfer functions of the motor system by experiments, and we design PID controller and robust controllers. Finally, we invite testing subjects for NDT gait training. We define performance indexes to discuss the rehabilitation results by the designed NDT trainer. The results indicate that the proposed device is deemed effective in improving NDT training.