B. Asfari, Riemannian L p center of mass: existence, uniqueness and convexity, Proc. Amer. Math. Soc, vol.139, issue.2, pp.655-673, 2011.

A. Barachant, S. Bonnet, M. Congedo, and C. Jutten, Multiclass Brain-Computer Interface Classification by Riemannian Geometry, IEEE Transactions on Biomedical Engineering, vol.59, issue.4, pp.920-928, 2012.
DOI : 10.1109/tbme.2011.2172210
URL : https://hal.archives-ouvertes.fr/hal-00681328

A. Barachant, S. Bonnet, M. Congedo, and C. Jutten, Classification of covariance matrices using a Riemannian-based kernel for BCI applications, Neurocomputing, vol.112, pp.172-178, 2013.
DOI : 10.1016/j.neucom.2012.12.039
URL : https://hal.archives-ouvertes.fr/hal-00820475

A. Barachant and M. Congedo, A Plug&Play P300 BCI Using Information Geometry, 2014.

R. Bhatia, Positive definite matrices, 2007.
URL : https://hal.archives-ouvertes.fr/hal-01500514

D. A. Bini and B. Iannazzo, Computing the Karcher mean of symmetric positive definite matrices, Linear Algebra and its Applications, vol.438, issue.4, pp.1700-1710, 2013.
DOI : 10.1016/j.laa.2011.08.052
URL : https://doi.org/10.1016/j.laa.2011.08.052

B. Blankertz, G. Dornhege, M. Krauledat, K. R. Muller, V. Kunzmann et al., The Berlin brain-computer interface: EEGbased communication without subject training, IEEE Trans. Neural Syst. Rehabil. Eng, vol.14, issue.2, pp.147-152, 2006.
DOI : 10.1109/tnsre.2006.875557
URL : http://ml.cs.tu-berlin.de/publications/BlaDorKraMueKunLosCur06.pdf

B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K. Muller, Optimizing spatial filters for robust EEG Single-Trial analysis, IEEE Signal Processing Magazine, vol.25, issue.1, pp.41-56, 2008.
DOI : 10.1109/msp.2008.4408441
URL : http://ida.first.fhg.de/publications/BlaTomLemKawMue08.pdf

B. Blankertz, S. Lemm, M. Treder, S. Haufe, and K. Muller, , 2011.

, Single-trial analysis and classification of ERP components-A tutorial, NeuroImage, vol.56, issue.2, pp.814-825

S. Bonnabel, Stochastic gradient descent on Riemannian manifolds, IEEE Transactions on Automatic Control, vol.122, issue.4, pp.2217-2229, 2013.

M. Congedo, M. Goyat, N. Tarrin, G. Ionescu, L. Varnet et al., Brain Invaders": a prototype of an open-source P300-based video game working with the OpenViBE platform, 5th International Brain-Computer Interface Conference, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00641412

M. Congedo, EEG Source Analysis, 2013.
URL : https://hal.archives-ouvertes.fr/tel-00880483

M. Congedo, B. Afsari, A. Barachant, and M. Moakher, Approximate Joint Diagonalization and Geometric Mean of Symmetric Positive Definite Matrices, PLoS ONE, issue.4, p.10, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01149652

M. Congedo, A. Barachant, and E. Kharati-koopaei, Fixed Point Algorithms for Estimating Power Means of Positive Definite Matrices, IEEE Transactions on Signal Processing, vol.65, issue.9, pp.2211-2220, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01500514

M. Congedo, A. Barachant, and R. Bhatia, Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review, Brain Computer Interfaces, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01570120

J. Farquhar, A linear feature space for simultaneous learning of spatio-spectral filters in BCI, Neural Networks, vol.22, issue.9, pp.1278-1285, 2009.

R. Ferreira, J. Xavier, J. P. Costeira, and V. Barroso, Newton algorithms for Riemannian distance related to problems on connected locally symmetric manifolds, IEEE J. Sel. Topics Signal Process, vol.7, issue.4, pp.634-645, 2013.

C. Gouy-pailler, M. Congedo, C. Brunner, C. Jutten, and G. Pfurtscheller, Nonstationary brain source separation for multiclass motor imagery, IEEE Transactions on Biomedical Engineering, vol.57, issue.2, pp.469-478, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00460494

M. Grosse-wentrup and M. Buss, Multiclass common spatial patterns and information theoretic feature extractions, IEEE Transactions on Biomedical Engineering, vol.55, issue.8, pp.1991-2000, 2008.

S. Haufe, M. S. Treder, M. F. Gugler, M. Sagebaum, G. Curio et al., EEG potentials predict upcoming emergency brakings during simulated driving, Journal of Neural Engineering, vol.8, 2011.

V. Jayaram, M. Alamgir, Y. Altun, B. Scholkopf, and M. Grosse-wentrup, Transfer Learning in Brain-Computer Interfaces Computational Intelligence Magazine, IEEE, vol.11, issue.1, pp.20-31, 2016.

B. Jeuris, R. Vandebril, and B. Vandereycken, A survey and comparison of contemporary algortihms for computing the matrix geometric mean, Electronic Transactions on Numerical Analysis, vol.39, pp.379-402, 2012.

L. Korczowski, M. Congedo, and C. Jutten, Single-Trial Classification of Multi-User P300-based Brain-Computer Interface Using Riemannian Geometry, 37th Annual International Conference, pp.1769-1772, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01191913

C. A. Kothe and S. Mekeig, BCILAB: a platform for braincomputer interface development, Journal of Neural Engineering, issue.5, p.10, 2013.

R. Leeb, C. Brunner, G. R. Muller-putz, A. Schlogl, and G. Pfurtscheller, BCI competition 2008-Graz data set A, 2008.

C. Lenglet, M. Rousson, R. Deriche, and O. Faugeras, Statistics on the manifold of multivariate normal distributions, J. Math. Imaging Vis, vol.25, issue.1, pp.127-154, 2006.

F. Lotte and C. Guan, Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms, IEEE Transactions on Biomedical Engineering, vol.58, issue.2, pp.355-362, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00476820

M. Moakher, A differential geometric approach to the geometric mean of symmetric posiitve-definite matrices, SIAM J. Matrix Anal. and Appl, vol.26, issue.3, pp.735-747, 2005.

K. Mohanchandra, Criminal forensic: An application to EEG. Recent and Emerging trends in Computer and Computational Sciences (RETCOMP), pp.18-21, 2015.

S. J. Pan and Q. Yang, A Survey on Transfer Learning, IEEE Transactions on Knowledge and Data Engineering, vol.22, issue.10, pp.1345-1359, 2010.

X. Pennec, P. Fillard, and N. Ayache, A Riemannian Framework for Tensor Computing, International Journal of Computer Vision, vol.66, issue.1, pp.41-66, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00070743

R. P. Rao, Brain-Computer Interfacing-An Introduction, 2013.

B. Reuderink, J. Farquhar, M. Poel, and A. Nijholt, A subjectindependent brain-computer interface based on smoothed, second-order baselining, Proceedings of the 33st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011.

S. Said, L. Bombrun, Y. Berthoumieu, and J. H. Manton, Riemannian gaussian distributions on the space of covariance matrices, 2015.

L. Van-der-maaten and G. Hinton, Visualizing Data using t-SNE, Journal of Machine Learning Research, vol.9, pp.2579-2605, 2008.

D. Wu, B. J. Lance, and T. D. Parsons, Collaborative Filtering for Brain-Computer Interaction Using Transfer Learning and Active Class Selection, PLoS ONE, vol.8, issue.2, 2013.

P. Zanini, M. Congedo, C. Jutten, S. Said, and Y. Berthomieu, Parameters estimate of Riemannian Gaussian distribution in the manifold of covariance matrices, Proc. of the Ninth IEEE Sensor Array and Multichannel Signal Processing Workshop (IEEE SAM 2016), 2016.
URL : https://hal.archives-ouvertes.fr/hal-01325055