Discrimination between Two Mental States (Rest and Motor Image) Using Wavelet Transform and Neural Networks

  • Authors:

  • Jose L. Martin;Luciano Boquete;Carmen Diaz;Manuel Garcia de Leon;Manuel Mazo

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
  • Year:
  • 2001

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Abstract

This paper presents a method for the processing and classification of electroencephalographic (EEG) signals linked to mental states (rest and motor image) using the wavelet transform of these signals as input information of an LVQ neural network. This system obtained a 70% correct qualification rate in the first recording session, a 50% rate in the second and an 80% rate in the third, with a 75% classification success rate for the whole set of data. These results fall within the average range obtained by other systems which require more information.