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