Methods of Acquisition and Signal Processing for Myoelectric Control of Artificial Arms

摘要

Myoelectric control of intelligent artificial arms, serving to replace amputated arms with prostheses, involves a lot of issues that have to be solved for achieving good results. It starts from the detection of electrical activity of muscles on the stump, which though does not develop a useful muscular exertion it can be used to control at will some predefined motions of artificial hand. An essential problem to be solved in this approach is the acquisition of the most useful controlling biosignals for the prosthesis, but the more important issue is to extract the control information from the raw myosignals. This approach is even more difficult as the amputation is older and those muscles are greatly atrophied, leading to weaker signals acquisition and more difficult signal processing. In this paper we present a simple method to separate the useful signal from noise and it's processing in order to get clear myoelectrical signals. This method is first presented using the software tools of the electromyograph used and then it is applied distinctly for separate processing of the signal generated by an amputated arm and extracting useful information.