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Clinical BCI Challenge-WCCI2020: RIGOLETTO – RIemannian GeOmetry LEarning, applicaTion To cOnnectivity

02/09/2021
by   Marie-Constance Corsi, et al.
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This short technical report describes the approach submitted to the Clinical BCI Challenge-WCCI2020. This submission aims to classify motor imagery task from EEG signals and relies on Riemannian Geometry, with a twist. Instead of using the classical covariance matrices, we also rely on measures of functional connectivity. Our approach ranked 1st on the task 1 of the competition.

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