GUI Simulation for Movement of Human Arm Driven by EMG Signal

Abstract

This work presents a simulation methodology applied to a human arm. It isaimed to allow the human-assisting manipulators to perform complex movementbased on electromyography (EMG) signal for patient person in Virtual Reality(VR). This work achieves better classification with multiple parameters based KNearestNeighbor for different movements of a prosthetic arm. A K- NearestNeighbor (K-NN) rule is one of the simplest and the most important methods inpattern recognition. The method implements in the 3D space and uses theMATLAB Ver.2009a approach. This methodology can be used with differentrobots to test the behavior of system and the different motion