FuRIA: An inverse Solution based Feature Extraction Algorithm using Fuzzy Set Theory for Brain-Computer Interfaces

Fabien Lotte 1, * Anatole Lécuyer 1 Bruno Arnaldi 1
* Auteur correspondant
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 presents FuRIA, a trainable feature extraction algorithm for non-invasive Brain-Computer Interfaces (BCI). FuRIA is based on inverse solutions and on the new concepts of fuzzy Region Of Interest (ROI) and fuzzy frequency band. FuRIA can automatically identify the relevant ROI and frequency bands for the discrimination of mental states, even for multiclass BCI. Once identified, the activity in these ROI and frequency bands can be used as features for any classifier. The evaluations of FuRIA showed that the extracted features were interpretable and can lead to high classification accuracies.
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IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2009, 57 (8), pp.3253-3263
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Fabien Lotte, Anatole Lécuyer, Bruno Arnaldi. FuRIA: An inverse Solution based Feature Extraction Algorithm using Fuzzy Set Theory for Brain-Computer Interfaces. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2009, 57 (8), pp.3253-3263. 〈inria-00368282〉

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