EMG analysis and control of artificial arm

Abstract

Robotic hand for prosthetic applications is a unique structure intended to be driven by electro myographic (EMG) signals captured from human body. The main characteristic of this robotic hand is its actuation system, which is based on the behaviour of EMG signals. The direct relation between signal and actuation system lends itself well to interpreting the EMG signals from the muscles into effective task execution, with the goal of helping the user to achieve a good approximation of the full capabilities associated with the human hand, without compromising strength, dexterity, appearance, or weight; which are common issues associated with prosthetic hands. EMG signal capturing capability was added to control the DC motors. The emg signal was then filtered and scaled using MAT lab to a value representing the amplitude of the EMG signal, which was then used to control the direction of the motors. The controller is a simple feed forward system in the project but provides the appropriate framework to integrate more elaborate control schemes and EMG signal conditioning. The goal is to create a direct relation between the EMG signals.