Classification

HappyFeat—An interactive and efficient BCI framework for clinical applications

Brain–Computer Interface (BCI) systems allow to perform actions by translating brain activity into commands. Such systems require training a classification algorithm to discriminate between mental states, using specific features from the brain …

RIGOLETTO paper accepted in ICASSP !

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)

Our RIGOLETTO approach ranked 1st to the IEEE WCCI2020 Challenge !

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 !