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              <p>Dans cet article, nous proposons un nouvel algorithme d'extraction de caractéristiques pour les interfaces cerveau-ordinateur. Cet algorithme utilise les modèles inverses ainsi que le nouveau concept de Région d'Intérêt (RI) floue. Il peut automatiquement identifier les RIs pertinentes pour la discrimination ainsi que leurs bandes de fréquences réactives. L'activité dans ces RIs peut être utilisée comme caractéristiques pour n'importe quel classifieur. Une première évaluation de l'algorithme, utilisant une Machine à Vecteurs Supports comme classifeur, est présentée sur le jeu de données IV de la BCI competition 2003. Les résultats sont prometteurs car nous avons obtenu une précision allant de 85% à 86% tandis que le gagnant de la compétition sur ces données a obtenu 84%.</p>
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