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 …
EEG signals acquired at different electrodes can be modelled as Signals on Graph, where the graph structure reflects the underlying brain Functional Connectivity (FC), representing brain region interactions. FC gives crucial information to detect …
Objective: Relying on the idea that functional connectivity provides important insights on the underlying dynamic of neuronal interactions, we propose a novel framework that combines functional connectivity estimators and covariance-based pipelines …
Thrilled to present our last piece of work in which we combined functional connectivity estimators with Riemannian geometry via an ensemble methods to improve the classification accuracy on a large number of publicly available datasets! OA version available [here](http://arxiv.org/abs/2111.03122), code paper available [here](https://www.softwareimpacts.com/article/S2665-9638(22)00019-7/fulltext) and code used available [here](https://github.com/mccorsi/FUCONE).
Thrilled to present our last piece of work in which we combined functional connectivity estimators with Riemannian geometry via an ensemble methods to improve the classification accuracy on a large number of publicly available datasets! Preprint available [here](http://arxiv.org/abs/2111.03122) and code used available [here](https://github.com/mccorsi/FUCONE).
Truly honoured to have received the #vBCI2021 best oral presentation award ! Thank you very much to the BCI Society for this award and for having put together this incredible conference ! Slides are available in the Talks section.
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/).