使用生物訊號回授與彈性機構之復健與支持運動控制

隨著科技的發展，使得機器人領域有了大的進展。不久的將來，機器人將頻繁出現在人類生活環境中，像是學校、醫院、辦公大樓、博物館、以及一般家庭等等區域。為了要使得機器人更容易可以與人類互動，機器人必須理解環境中的人類的意圖並根據所得知之訊息做出相對應的反應。因此本論文目的旨在發展藉由人類肌電與腦波訊號，使機器人能夠偵測人類意圖的方法，並設計具有內在安全性之彈性機構與變剛性機構，使得人類與機器在物理上的互動可以更加的安全，並根據生物訊號之特性來設計相對應之復健與支持運動之控制方法。對於人類意圖的估測，提出了使用幾種根據EMG與EEG特性而設計之架構。EMG上面，主要以肌肉模型、動態模型並以Graphical Model融合不同估測結果。EEG則提出了使用ICA-MKL之架構來分類P300之腦電位訊號。而在機構之設計上則提出了容易組裝與輕便簡易之可反驅動彈簧機構與複雜可變換剛性之耦合連續剛性彈性機構以因應不同任務之需求兩種架構，使得整個系統擁有被動之安全性。在智慧型控制層次上，為了建構能針對各式各樣任務之控制法則，本論文進而發展了容易使用且整合EMG控制與零阻抗控制之混合控制與以人類EMG和順應之特性而發展之虛擬EMG順應性控制等概念。最後本論文展示藉由結合人類意圖偵測、安全機構設計與智慧型控制，將應用拓展至手軸關節復健與支持運動、膝關節支持運動與人類行走與爬樓梯之支持運動上，展示了機器未來輔助人類的可能性。

關鍵字

物理人機互動；智慧型控制；彈性機構設計；輔助與復健機器人；圖形模型；動態與肌電參數估測

並列摘要

The robot technologies have a lot of progress recently. In the near future, robots will appear much more frequently in daily human life, such as in schools, hospitals, offices, museums, and the home. In order to assist and interact with humans, the robots need to understand the humans’ intentions and respond accordingly. Therefore, the aim of this dissertation is to develop human intention estimation methods using electromyography (EMG), electroencephalography (EEG), and dynamic information; and to design an elastic and variable stiffness mechanism with intrinsic safety, and advanced control for assistive and rehabilitation exercises. We use a muscle model to find the relationship between EMG and torque. Moreover, an exoskeleton graphical model is proposed to merge the EMG signal and dynamic information, and enhance the stabilization of the robot-human system. For extremely weak patients, independent component analysis-multiple kernel learning (ICA-MKL) is also proposed to increase the classification accuracy of the EEG human intention estimation. In order to satisfy the demand of the assistive and rehabilitation exercises, two different kinds of mechanism approaches are proposed. Backdrivable torsion spring actuators (BTSA) are recommended because they are light weight, compact, and mainly used in assistive control. Considering their performance and safety, variable stiffness and coupled elastic actuation are designed to adaptively change for different tasks. Finally, intelligent and safety controls are also developed to help humans in assistive exercises, rehabilitation, and walking, and guarantee safety under variable environments.

並列關鍵字

human robot interaction ； elastic actuation ； assistive and rehabilitation robot ； intelligent control ； human intention estimation

參考文獻

[1] M. T. Akhtar, C. J. James, and W. Mitsuhashi, "Modifying the Spatially-Constrained ICA for Efficient Removal of Artifacts from EEG Data," Proc. of International Conference on Bioinformatics and Biomedical Engineering (iCBBE), Chengdu, China, pp. 1-4, 2010.

[2] D. S. Andreasen, S. K. Alien, and D. A. Backus, "Exoskeleton with EMG Based Active Assistance for Rehabilitation," Proc. of International Conference on Rehabilitation Robotics, Chicago, Illinois, pp. 333-336, 2005.

[5] P. Beyl, M. Van Damme, R. Van Ham, B. Vanderborght, and D. Lefeber, "Pleated Pneumatic Artificial Muscle-Based Actuator System as a Torque Source for Compliant Lower Limb Exoskeletons," IEEE/ASME Transactions on Mechatronics, Vol. PP, No. 99, pp. 1-11, 2013.

[6] A. Bicchi and G. Tonietti, "Fast and "Soft-arm" Tactics," IEEE Robotics and Automation Magazine, Vol. 11, No. 2, pp. 22-33, 2004.

[7] B. Bigge and I. R. Harvey, "Programmable Springs: Developing Actuators with Programmable Compliance for Autonomous Robots," Robotics and Autonomous Systems, Vol. 55, No. 9, pp. 728-734, 2007.

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使用生物訊號回授與彈性機構之復健與支持運動控制

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