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

20182,041 citationsReview

Authors

Fabien Lotte · Centre National de la Recherche Scientifique

Laurent Bougrain · RIKEN Center for Brain Science

Andrzej Cichocki · Skolkovo Institute of Science and Technology

Maureen Clerc · Institut national de recherche en sciences et technologies du numérique

Marco Congedo · Institut polytechnique de Grenoble

Alain Rakotomamonjy · Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes

Abstract

This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

Topics & Keywords

EEG and Brain-Computer Interfaces Neural dynamics and brain function Advanced Memory and Neural Computing

UN Sustainable Development Goals

Reduced inequalities

Publication Details

Published in: Journal of Neural Engineering

Volume 15, Issue 3, pp. 031005-031005

DOI: 10.1088/1741-2552/aab2f2

Field-Weighted Citation Impact: 106.96