被動式行動輔助機器人意圖導引系統開發及其醫院臨床試驗

Abstract

醫療的進步促成現今高齡化社會的發展，而年齡的增長造成身體機能減弱並衍生出行動不便的問題，有效的恢復長者行動能力是相當迫切且重要的議題，此外，許多國人因罹患腦中風而導致偏癱，其患者亦需透過積極復健來恢復行動能力以提高生活品質。目前已有許多智慧型行動輔具的相關研究，本研究以實驗室所開發之被動式行動輔助機器人「i-Go」做為系統平台，針對下肢行動能力有限但仍可藉由手部表達輕微行動意圖的使用者，提出意圖導引輔助策略，透過事先學習得到之個別使用者的握力映射模型，將使用者的握力轉為推力與力矩，用以做為意圖判斷指標，並由此指標進行路徑的選擇，再依據所選路徑使用退卻平面被動式輔助策略來輸出輔助煞車力導引使用者至目標點。本研究除了進行相關模擬與實驗來驗證所提出系統的成效，並與義大醫院復健科合作，邀請患者進行直線行走試驗及問卷回答，並以所開發的足壓偵測系統蒐集使用者步態資訊供臨床評估與復健參考，並依據問卷結果了解真實使用者的實際需求，作為所開發之輔具系統之改善參考。

Along with medical progress, the elderly population rapidly increases. The miopragia disease is one of the most common ones for the elders, which may lead to the mobility problem. Meanwhile, walking rehabilitation is widely used for patients suffering from hemiplegia. Many walking assistive devices are thus widely developed in such demand nowadays. In this thesis, we propose a guidance scheme based on user walking intention and implement it on a passive robot walking helper, i-Go, developed in our laboratory. The proposed scheme first detects user walking intention, which serves as the selection index for corresponding guidance path, from their forces applied on the developed force-sensing grips, which can be transformed into the driving force/torque via a learning scheme. Along with the selected path and driving force derived from the measured applied force, the receding horizon passive control strategy will derive the braking torques and then guide the user to the desired target. The effectiveness of the proposed system is verified by simulations and experiments. Moreover, we have invited several target users in the E-DA hospital for clinical trial. They were asked to execute the standard walking trials with foot pressure sensing shoes to analyze their gait states as rehabilitation reference. Questionnaires have also been conducted to obtain their feedbacks for improvement.