A new multi criteria classification approach in a multi agent system applied to SEEG analysis.
This work is focused on the study of the organization of the SEEG signals during epileptic seizures with multi-agent system approach. This approach is based on cooperative mechanisms of auto-organization at the micro level and of emergence of a global function at the macro level. In order to evaluate this approach we propose a distributed collaborative approach for the classification of the interesting signals. This new multi-criteria classification method is able to provide a relevant brain area structures organisation and to bring out epileptogenic networks elements. The method is compared to another classification approach a fuzzy classification and gives better results when applied to SEEG signals.
Kinié
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A
LTSI, Laboratoire Traitement du Signal et de l'Image INSERM, U642, Université Rennes I, Campus de Beaulieu, Rennes Cedex, France. abel.kinie@univ-rennes1.fr
Ndiaye
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M
Montois
J J
JJ
Jacquelet
Y
Y
D000465:Algorithms; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D001330:Electronic Data Processing; D004827:Epilepsy / Q000175:diagnosis* / Q000473:pathology*; D004867:Equipment Design; D017143:Fuzzy Logic; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net; D017711:Nonlinear Dynamics; D012984:Software