本論文主要在設計與實現一套肢體同動機械手臂系統來驗證以肌電訊號控制機械手臂的可行性，並作為穿戴式機械骨骼系統之先期研究。這套系統包含肢體同動機械手臂系統的機械結構設計和驅動電路建構，並以數位訊號處理器(TMS320F2812)先實現肢體同動機械手臂系統的運動控制(扭力控制、速度控制和位置控制)，再結合肌電訊號的訊號處理、特徵值處理和肌力估測方法，得到肌電訊號與手臂肌力間之相關模型進行整合。 最後，本論文以數位訊號處理器(TMS320F2812)整合肌電訊號的訊號處理、肌力估測方法與機械手臂運動控制，數位訊號處理器(TMS320F2812)能先以受測者手臂動作時之二頭肌與三頭肌的肌電訊號估測出其肌力變化，並作為機械手臂的扭力命令操控機械手臂，讓機械手臂可以實現受測者想要完成的動作和指令，達成機械手臂能跟隨受測者手臂動作的目的，也意味著未來應用於穿戴式機械骨骼系統時，機械手臂能幫助病人作其想要的動作，使生活更為便利，並提升其生活品質。 This thesis aims to develop an EMG-based upper limb motion synchronization robotic arm system which enables an upper limb robotic arm to move synchronously with the tester. This system contains four sections: (a) the design of mechanism; (b) the design of electronic driver circuits; (c) the motion control of robotic arm; (d) the analyses of EMG signals and the estimation of muscle strength which used EMG signals In this thesis, we combine four sections and realize algorithms with a digital signal processor (TMS320F2812). We use a digital signal processor (TMS320F2812) to measure the EMG signals of biceps and triceps, which imply the human subject’s intention. We utilize a band-pass filter to process the EMG signals and feature extraction methods convert EMG signals to variances (VAR).Then we employ an estimator to estimate the muscle strength of the tester’s forearm. Therefore, the estimated muscle strength can be used as a torque command for robotic arm system. We also use a digital signal processor (TMS320F2812) to realize the torque control of robotic arm system. So the robotic arm can achieve the desired motion of the tester. In the future, this system can be transferred into an exoskeletal robot for human motion support, especially for those physically weak ones.
