Riemannian Approaches in Brain-Computer Interfaces: A Review

@article{Yger2017RiemannianAI,
  title={Riemannian Approaches in Brain-Computer Interfaces: A Review},
  author={Florian Yger and Maxime Berar and Fabien Lotte},
  journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  year={2017},
  volume={25},
  pages={1753-1762}
}
Although promising from numerous applications, current brain–computer interfaces (BCIs) still suffer from a number of limitations. In particular, they are sensitive to noise, outliers and the non-stationarity of electroencephalographic (EEG) signals, they require long calibration times and are not reliable. Thus, new approaches and tools, notably at the EEG signal processing and classification level, are necessary to address these limitations. Riemannian approaches, spearheaded by the use of… CONTINUE READING
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