Authors
Abstract
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 KNearest
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
Keywords
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