Swarm Based Fuzzy Discriminant Analysis for Multifunction Prosthesis Control

  • Rami N. Khushaba
  • Ahmed Al-Ani
  • Adel Al-Jumaily
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5998)

Abstract

In order to interface the amputee’s with the real world, the myoelectric signal (MES) from human muscles is usually utilized within a pattern recognition scheme as an input to the controller of a prosthetic device. Since the MES is recorded using multi channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher’s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for the weights calculation. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

Keywords

Discriminant Analysis Myoelectric Control Particle Swarm Optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rami N. Khushaba
    • 1
  • Ahmed Al-Ani
    • 1
  • Adel Al-Jumaily
    • 1
  1. 1.Faculty of EngineeringUniversity of TechnologySydneyAustralia

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