GUI simulation for movement of human arm driven by EMG signal

Abstract EN

This work presents a simulation methodology applied to a human arm.

It is aimed to allow the human-assisting manipulators to perform complex movement based on electromyography (EMG) signal for patient person in Virtual Reality (VR).

This work achieves better classification with multiple parameters based Nearest Neighbor for different movements of a prosthetic arm.

A K- Nearest Neighbor (K-NN) rule is one of the simplest and the most important methods in pattern recognition.

The method implements in the 3D space and uses the MATLAB Ver.2009a approach.

This methodology can be used with different robots to test the behavior of system and the different motion.