Papers to understand the BCI field.

  • [1]F. Lotte et al., “A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update,” Journal of Neural Engineering, vol. 15, no. 3, p. 031005, Jun. 2018.
  • [2]F. Lotte, L. Bougrain, and M. Clerc, “Electroencephalography (EEG)-Based Brain-Computer Interfaces,” in Wiley Encyclopedia of Electrical and Electronics Engineering, Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015, pp. 1–20.
  • [3]F. Lotte, “A Tutorial on EEG Signal-processing Techniques for Mental-state Recognition in Brain–Computer Interfaces,” in Guide to Brain-Computer Music Interfacing, E. R. Miranda and J. Castet, Eds. London: Springer London, 2014, pp. 133–161.
  • [4]F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, and B. Arnaldi, “A review of classification algorithms for EEG-based brain–computer interfaces,” Journal of Neural Engineering, vol. 4, no. 2, pp. R1–R13, Jun. 2007.
  • [5]F. Lotte and C. Jeunet, “ONLINE CLASSIFICATION ACCURACY IS A POOR METRIC TO STUDY MENTAL IMAGERY-BASED BCI USER LEARNING: AN EXPERIMENTAL DEMONSTRATION AND NEW METRICS,” p. 6.