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Studying the Use of Fuzzy Inference Systems for Motor Imagery Classification

Fabien Lotte 1, * Anatole Lécuyer 1 Fabrice Lamarche 1 Bruno Arnaldi 1
* Corresponding author
1 BUNRAKU - Perception, decision and action of real and virtual humans in virtual environments and impact on real environments
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, ENS Cachan - École normale supérieure - Cachan, Inria Rennes – Bretagne Atlantique
Abstract : This paper studies the use of Fuzzy Inference Systems (FISs) for motor imagery classification in EEG-based Brain-Computer Interfaces (BCIs). The results of the four studies achieved are promising as, on the analysed data, the used FIS was efficient, interpretable, showed good capabilities of rejecting outliers and offered the possibility of using a priori knowledge.
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Contributor : Fabien Lotte <>
Submitted on : Tuesday, March 6, 2007 - 9:48:34 AM
Last modification on : Thursday, May 9, 2019 - 4:16:10 PM
Long-term archiving on: : Wednesday, April 7, 2010 - 2:55:32 AM


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  • HAL Id : inria-00134958, version 1



Fabien Lotte, Anatole Lécuyer, Fabrice Lamarche, Bruno Arnaldi. Studying the Use of Fuzzy Inference Systems for Motor Imagery Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering, Institute of Electrical and Electronics Engineers, 2007. ⟨inria-00134958v1⟩



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