Fuzzy Algorithm for SEEG Classification

  • A. Kinié
  • M. Ndiaye
Part of the IFMBE Proceedings book series (IFMBE, volume 37)

Abstract

This work is focused on the study of the organization of the SEEG signals during epileptic seizures. We propose a fuzzy algorithm approach for the classification of the interesting signals. This new classification method use a non linear regression coefficient and is able to provide a relevant brain area structures organisation and to bring out epileptogenic networks pertinent elements. The method gives good results when applied to SEEG signals.

Keywords

Classification Method Epileptic Seizure Temporal Lobe Epilepsy Linear Regression Coefficient Cerebral Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • A. Kinié
    • 1
  • M. Ndiaye
    • 2
  1. 1.Collaborateur Laboratoire Traitement du Signal et Image INSERMU642 Université Rennes1- IUTSaint-Malo
  2. 2.Ecole Polytechnique de DakarSénégal

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