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 bio-medical engineering},
  year={2022},
  volume={PP}
}
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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