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 …
This Student Award is based on my accepted 2020 abstract submission. I will give a presentation during the next Virtual BCI meeting, scheduled next June ! For more information regarding this work, our study is available [here](https://hal.archives-ouvertes.fr/hal-02438794/).
Pleased to announce with [Sylvain Chevallier](https://sylvchev.github.io) and [Florian Yger](http://www.yger.fr) that our manuscript on our participation to the Clinical BCI Challenge WCCI2020 has been accepted for the next [ICASSP](https://2021.ieeeicassp.org) conference ! The technical report and code about the competition are available [here](https://arxiv.org/abs/2102.06015)
In the last decade, functional connectivity (FC) has been increasingly adopted based on its ability to capture statistical dependencies between multivariate brain signals. However, the role of FC in the context of brain-computer interface …
Very pleased to announce with [Sylvain Chevallier](https://sylvchev.github.io) from Univ. Paris-Saclay and [Florian Yger](http://www.yger.fr) from Univ. Paris-Dauphine that our method combining functional connectivity with Riemannian geometry made it 1st to the [Clinical BCI Challenge IEEE WCCI2020](CBCIC2020sites.google.com) (within-subject category) ! More info to come, stay tuned !