Riemannian Geometry on Connectivity for Clinical BCI
Corsi, Marie-Constance; Yger, Florian; Chevallier, Sylvain; Noûs, Camille (2021), Riemannian Geometry on Connectivity for Clinical BCI, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021-06, Toronto, Canada
TypeCommunication / Conférence
External document linkhttps://hal.archives-ouvertes.fr/hal-03202349
Conference titleICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
MetadataShow full item record
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)Riemannian BCI based on EEG covariance have won many data competitions and achieved very high classification results on BCI datasets. To increase the accuracy of BCI systems, we propose an approach grounded on Riemannian geometry that extends this framework to functional connectivity measures. This paper describes the approach submitted to the Clinical BCI Challenge-WCCI2020 and that ranked 1 st on the task 1 of the competition.
Subjects / KeywordsRiemannian geometry; functional connectivity; ensemble learning; BCI
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Ensemble learning based on functional connectivity and Riemannian geometry for robust workload estimation Corsi, Marie-Constance; Chevallier, Sylvain; Barthélemy, Quentin; Hoxha, Isabelle; Yger, Florian Communication / Conférence