Functional Connectivity Ensemble Method to Enhance BCI Performance (FUCONE)

@article{Corsi2022FunctionalCE,
  title={Functional Connectivity Ensemble Method to Enhance BCI Performance (FUCONE)},
  author={Marie-Constance Corsi and Sylvain Chevallier and Fabrizio de Vico Fallani and Florian Yger},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2022},
  volume={69},
  pages={2826-2838}
}
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 to improve the classification of mental states, such as motor imagery. Methods: A Riemannian classifier is trained for each estimator and an ensemble classifier combines the decisions in each feature space. A thorough assessment of the functional… 

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