A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

Short summary

Modern EEG-based BCIs increasingly use adaptive classifiers, matrix/tensor methods, transfer learning, and deep learning, with adaptive classifiers generally outperforming static ones and Riemannian geometry methods achieving state-of-the-art results.

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