N. Birbaumer and L. G. Cohen, Brain-computer interfaces: communication and restoration of movement in paralysis, The Journal of Physiology, vol.101, issue.3, pp.621-636, 2007.
DOI : 10.1113/jphysiol.2006.125633

B. Blankertz, G. Curio, and K. Müller, « Classifying single trial EEG : Towards brain computer interfacing, Advances in Neural Inf. Proc. Systems (NIPS 01), pp.157-164, 2002.

B. Blankertz, G. Dornhege, S. Lemm, M. Krauledat, G. Curio et al., The Berlin Brain???Computer Interface: EEG-Based Communication Without Subject Training, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.14, issue.2, pp.147-152, 2006.
DOI : 10.1109/TNSRE.2006.875557

C. Brunner, M. Naeem, R. Leeb, B. Graimann, and G. Pfurtscheller, Spatial filtering and selection of optimized components in four class motor imagery EEG data using independent components analysis, Pattern Recognition Letters, vol.28, issue.8, pp.957-964, 2007.
DOI : 10.1016/j.patrec.2007.01.002

H. Cecotti and A. Gräser, « Neural network pruning for feature selection -Application to a P300 Brain-Computer Interface, European Symposium on Artificial Neural Networksp, pp.473-478, 2009.

H. Cecotti, I. Volosyak, and A. Gräser, Evaluation of an SSVEP based Brain-Computer Interface on the command and application levels, 2009 4th International IEEE/EMBS Conference on Neural Engineering, 2009.
DOI : 10.1109/NER.2009.5109336

G. E. Chatrian, E. Lettich, and P. L. Nelson, « Ten percent electrode system for topographic studies of spontaneous and evoked EEG activity », Am J EEG Technol, vol.25, pp.83-92, 1985.

E. Donchin, K. M. Spencer, and R. Wijesinghe, The mental prosthesis: assessing the speed of a P300-based brain-computer interface, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.2, pp.174-179, 2000.
DOI : 10.1109/86.847808

L. Farwell and E. Donchin, Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials, Electroencephalography and Clinical Neurophysiology, vol.70, issue.6, pp.510-523, 1988.
DOI : 10.1016/0013-4694(88)90149-6

T. Felzer and B. Freisieben, Analyzing EEG signals using the probability estimating guarded neural classifier, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.11, issue.4, 2003.
DOI : 10.1109/TNSRE.2003.819785

O. Friman, I. Volosyak, and A. Gräser, Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces, IEEE Transactions on Biomedical Engineering, vol.54, issue.4, pp.742-750, 2007.
DOI : 10.1109/TBME.2006.889160

M. Hansenne, Le potentiel ??voqu?? cognitif P300 (I)??: aspects th??orique et psychobiologique, Neurophysiologie Clinique/Clinical Neurophysiology, vol.30, issue.4, pp.191-210, 2000.
DOI : 10.1016/S0987-7053(00)00223-9

M. Hansenne, Le potentiel ??voqu?? cognitif P300 (II)??: variabilit?? interindividuelle et application clinique en psychopathologie, Neurophysiologie Clinique/Clinical Neurophysiology, vol.30, issue.4, pp.211-231, 2000.
DOI : 10.1016/S0987-7053(00)00224-0

E. Haselsteiner and G. Pfurtscheller, Using time-dependent neural networks for EEG classification, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.4, pp.457-463, 2000.
DOI : 10.1109/86.895948

U. Hoffmann, J. M. Vesin, K. Diserens, and T. Ebrahimi, An efficient P300-based brain???computer interface for disabled subjects, Journal of Neuroscience Methods, vol.167, issue.1, pp.115-125, 2008.
DOI : 10.1016/j.jneumeth.2007.03.005

D. J. Krusienski, E. W. Sellers, D. Mcfarland, T. M. Vaughan, J. R. Wolpaw et al., Toward enhanced P300 speller performance, Journal of Neuroscience Methods, vol.167, issue.1, pp.15-21, 2008.
DOI : 10.1016/j.jneumeth.2007.07.017

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2349091

T. N. Lal, M. Schroder, T. Hinterberger, J. Weston, M. Bogdan et al., Support Vector Channel Selection in BCI, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.1003-1010, 2004.
DOI : 10.1109/TBME.2004.827827

E. Maby, G. Gibert, P. Aguera, M. Perrin, O. Bertrand et al., « The Open- ViBE P300-Speller scenario : a thorough online evaluation, Human Brain Mapping Conference, 2010.

D. J. Mackay and . Bayesian-interpolation, Bayesian Interpolation, Neural Computation, vol.49, issue.3, pp.415-447, 1992.
DOI : 10.1093/comjnl/11.2.185

N. Masic and G. Pfurtscheller, Neural network based classification of single-trial EEG data, Artificial Intelligence in Medicine, vol.5, issue.6, pp.503-513, 1993.
DOI : 10.1016/0933-3657(93)90040-A

N. Masic, G. Pfurtscheller, and D. Flotzinger, Neural network-based predictions of hand movements using simulated and real EEG data, Neurocomputing, vol.7, issue.3, pp.259-274, 1995.
DOI : 10.1016/0925-2312(95)00025-2

K. Müller, M. Tangermann, G. Dornhege, M. Krauledat, G. Curio et al., Machine learning for real-time single-trial EEG-analysis: From brain???computer interfacing to mental state monitoring, Journal of Neuroscience Methods, vol.167, issue.1, pp.82-90, 2008.
DOI : 10.1016/j.jneumeth.2007.09.022

G. R. Müller-putz, R. Scherer, C. Brauneis, and G. Pfurtscheller, Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components, Journal of Neural Engineering, vol.2, issue.4, pp.123-130, 2005.
DOI : 10.1088/1741-2560/2/4/008

J. Polich and P. Updating, Updating P300: An integrative theory of P3a and P3b, Clinical Neurophysiology, vol.118, issue.10, pp.2128-2148, 2007.
DOI : 10.1016/j.clinph.2007.04.019

A. Rakotomamonjy, V. Guigue, and «. Bci, BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller, IEEE Transactions on Biomedical Engineering, vol.55, issue.3, pp.1147-1154, 2008.
DOI : 10.1109/TBME.2008.915728

URL : https://hal.archives-ouvertes.fr/hal-00439462

B. Rivet, A. Souloumiac, V. Attina, and G. Gibert, xDAWN Algorithm to Enhance Evoked Potentials: Application to Brain–Computer Interface, IEEE Transactions on Biomedical Engineering, vol.56, issue.8, 2009.
DOI : 10.1109/TBME.2009.2012869

B. Rivet, A. Souloumiac, G. Gibert, and V. Attina, « P300 speller Brain-Computer Interface : Enhancement of P300 evoked potential by spatial filters, Proc. EU- SIPCO, 2008.

E. I. Shih, A. H. Shoeb, and J. V. Guttag, Sensor selection for energy-efficient ambulatory medical monitoring, Proceedings of the 7th international conference on Mobile systems, applications, and services, Mobisys '09, pp.347-358, 2009.
DOI : 10.1145/1555816.1555851

R. Tomioka, N. J. Hill, B. Blankertz, and K. Aihara, Adapting Spatial Filter Methods for Nonstationary BCIs, Based Induction Sciences (IBIS), vol.6, 2006.

I. Volosyak, H. Cecotti, D. Valbuena, and A. Gräser, Evaluation of the Bremen SSVEP based BCI in real world conditions, 2009 IEEE International Conference on Rehabilitation Robotics, pp.322-331, 2009.
DOI : 10.1109/ICORR.2009.5209543

N. Xu, X. Gao, B. Hong, X. Miao, S. Gao et al., BCI Competition 2003???Data Set IIb: Enhancing P300 Wave Detection Using ICA-Based Subspace Projections for BCI Applications, IEEE Transactions on Biomedical Engineering, vol.51, issue.6, pp.1067-1072, 2003.
DOI : 10.1109/TBME.2004.826699

F. *. Hères, U. Inserm, and . Lyon, GIPSA-lab CNRS UMR 5216 Universités de Grenoble 38402 Saint Martin d, Coordonnées des auteurs : ? adresse postale, p.0

. Formulaire-de-copyright, Retourner le formulaire de copyright signé par les auteurs, téléchargé sur : http://www.revuesonline.com Service éditorial ? Hermes-Lavoisier 14 rue de Provigny