Brain & Mind Computational Seminar

Marco Congedo – CNRS (French National Centre for Scientific Research), Grenoble Alpes University

In this talk we will review recent advances in the use of Riemannian Geometry for BCI classification. The Riemannian manifold of positive definite matrices will be briefly reviewed from an applicative point of view. Then, the general functioning of Riemannian classification algorithms for electroencephalography (EEG) will be explained. The talk is concluded with a demonstration of one such algorithm in action to allow control of a brain-computer interface based on event-related potentials.

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