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Journal of Intelligent Information Systems

, Volume 21, Issue 2, pp 127–141 | Cite as

The Development of a Virtual Myoelectric Prosthesis Controlled by an EMG Pattern Recognition System Based on Neural Networks

  • Alcimar Soares
  • Adriano Andrade
  • Edgard Lamounier
  • Renato Carrijo
Article

Abstract

One of the major difficulties faced by those who are fitted with prosthetic devices is the great mental effort needed during the first stages of training. When working with myoelectric prosthesis, that effort increases dramatically. In this sense, the authors decided to devise a mechanism to help patients during the learning stages, without actually having to wear the prosthesis. The system is based on a real hardware and software for detecting and processing electromyografic (EMG) signals. The association of autoregressive (AR) models and a neural network is used for EMG pattern discrimination. The outputs of the neural network are then used to control the movements of a virtual prosthesis that mimics what the real limb should be doing. This strategy resulted in rates of success of 100% when discriminating EMG signals collected from the upper arm muscle groups. The results show a very easy-to-use system that can greatly reduce the duration of the training stages.

EMG neural networks prosthesis AR signal processing virtual reality 

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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Alcimar Soares
    • 1
  • Adriano Andrade
    • 1
  • Edgard Lamounier
    • 1
  • Renato Carrijo
    • 1
  1. 1.Biomedical and Computer Graphics LaboratoriesFederal University of Uberlândia/Faculty of Electrical EngineeringUberlândia/MGBrazil

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