Riemannian geometry

Functional connectivity ensemble method to enhance BCI performance (FUCONE)

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 …

Paper on functional connectivity ensemble method to enhance BCI performance accepted in IEEE Transactions on Biomedical Engineering!

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).

Riemannian geometry for combining functional connectivity metrics and covariance in BCI

Just up on ArXiv, our latest work on functional connectivity ensemble method to enhance BCI performance!

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).

Riemannian Geometry on Connectivity for Clinical BCI

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 …

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 !