A Study on Intelligent Trajectrory Control for Prosthetic Arm using EMG Signals

근전도신호를 이용한 의수의 지능적 궤적제어에 관한 연구

An intelligent trajectory control method that controls a direction and a average velocity for a prosthetic arm by force and direction estimations using EMG signals is proposed. 3 stage linear filters are used as a real time joint trajectory planner to minimize the impact to human body induced by arm motions and to reduce muscle fatigues. We use combination of MLP and fuzzy filter for a limb direction estimation and a time model of force for determining a cartesian trajectory control parameter. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. Simulation results of the proposed method show that the arm is effectively followed the desired trajectory by estimated foreces and directions. This method reduces the number of electrodes and attatched sites compared with the method using Hogan's impedance control.