Design and Implementation of an Intelligent Interface for Myoelectric Controlled Prosthesis

Abstract

In this paper, a discrimination system, using a neural network for electromyographic (EMG) externally controlled upper extremity prostheses is proposed. In this system, the Artificial Neural Network (ANN) is used to learn the relation between the power spectrum of EMG signal analyzed by Fast Fourier Transform (FFT) and the performance desired by handicapped people. The Neural Network can discriminate 7 performances of the EMG signals simultaneously. In order to prove the effectiveness of this system, experiments for discriminating the 7 arm performances of a healthy 23 year-old man, were carried out For real-time operation, a Digital Signal Processor (ADSP-21061) operates over the resulting set of weights and maps the incoming signal to the stimuli control domain. Results show a highly accurate discrimination of the control signal over interference patterns.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411621

Entities

People

  • Carlos Sanchez
  • Fernando Rosas
  • Juan Leon
  • Victor Grisales
  • Vladimir Barrero

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Computing System Architectures
  • Databases
  • Discrimination
  • Electrodes
  • Fourier Analysis
  • Frequency
  • Frequency Domain
  • Host Computers
  • Network Architecture
  • Network Topology
  • Neural Networks
  • Power Spectra
  • Prostheses And Implants
  • South America
  • Spectra
  • Upper Limb Prostheses

Fields of Study

  • Engineering

Readers

  • Neural Network Machine Learning.
  • Radar Systems Engineering.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks