用於上肢復健外骨骼機器人之具鬆懈預防機制的主動輔助控制

Active-Assistive Control System with Slacking Behavior Prevention for Upper Limb Rehabilitation Exoskeleton Robot

簡子捷(Tzu-Chieh Chien)

指導教授 ： 傅立成

國立臺灣大學/電機資訊學院/電機工程學研究所/碩士(2020年)

https://doi.org/10.6342/NTU202002885

摘要

中風是一種突發性腦血管疾病，其造成之上肢和下肢的運動障礙為成年人生理殘疾的主要原因之一。據臨床研究結果顯示，中風患者可藉由密集且高質量的物理治療以改善肢體運動能力。將上肢復健外骨骼機器人引入療程，除可提供準確和長期的復健訓練，同時也可降低醫療人力成本。另外，臨床研究報告也指出，復健治療期間患者的主動積極參與將對訓練效果產生積極影響。因此，將監測和維持患者的積極參與的方法納入基於外骨骼的復健控制策略中有其必要性。又因復健療程的動作難度與患者在復健訓練期間的積極參與度具有密切關連，藉由自動且持續調整任務難度為維持患者參與度的一種可行方案。

本研究針對上肢復健外骨骼機器人NTUH-II，提出一種基於使用者參與度的輔助控制方法和復健動作難度調整演算法。首先，使用者的參與度可由提出之表面肌電訊號監測方法獲得。接著，復健動作的輔助策略將應用速度場理論建構。最後，本研究提出一整合方法可藉由衡量使用者在運動過程之參與度及表現，決定機器人之輔助程度，以實現精準輔助與鬆懈行為的預防。此外，任務難度調整算法將依據使用者的運動表現調整動作難度至使用者的適當任務難度。

本研究提出之輔助控制系統經實驗驗證。其結果顯示，與相關文獻相比，此方法在防止使用者的鬆懈行為的同時，仍可輔助使用者準確地完成復健動作。另外，實驗結果也呈現任務難度調整演算法的有效性。於未來展望，本系統需進一步應用於臨床試驗以驗證其應用於中風病患之療效。

關鍵字

復健機械手臂 ； 肌電訊號 ； 輔助式療程 ； 訓練最佳化

並列摘要

Stroke is a sudden cerebrovascular disease, which is one of the leading causes of physiological disability in adults. In order to recover from those motor disabilities, intensive and high-quality physical therapy and rehabilitation training are critical, according to the studies from the clinical research. Introducing the exoskeleton robot to the therapy shows the benefit of providing accurate and long-duration rehabilitation exercise while also having the potential to lower the high labor cost. During the rehabilitation therapy, the sustained engagement of the patients is another essential factor reported from the clinical research, which has a positive effect on training efficiency. Therefore, monitoring and maintaining the patients' active participation should be considered into the control strategy of exoskeleton-based rehabilitation. Since the task difficulty is reported to have a high correlation to patients' active participation during the rehabilitation, the automatic tuning of the task difficulty is another feasible method to maintain the participation level.

A participation-based active-assistive control strategy and a task difficulty adjustment algorithm are proposed for upper-limb rehabilitation exoskeleton robot, NTUH-II. First, we propose a subject's participation monitoring mechanism to translate the surface electromyography into the active participation level in real-time. Next, the participation-based active-assistive control is constructed based on the velocity field based active-assistive control strategy and the proposed participation monitoring mechanism. The proposed participation-based aggregation method has the ability to provide assistance according to the active intention of the patient, assistive motion, and participation level to achieve slacking behavior prevention. Finally, a task difficulty adjustment algorithm is proposed to adjust the task difficulty to converge to the suitable task difficulty for the subject.

We conduct various experiments to verify the feasibility of the proposed control structure. The results show that compared with related work, the proposed method can prevent the subject's slack behavior while assisting the subject in achieving the rehabilitation goal accurately. Additionally, the effectiveness of the task adjustment algorithm is also shown in the experiment results. In future work, clinical studies are required further to validate the proposed system's effectiveness for stroke patients.

並列關鍵字

rehabilitation robotics ； electromyography ； active-assistive rehabilitation ； training optimization ； NTUH-II

參考文獻

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