E. K. Kalunga, S. Chevallier, O. Rabreau, and E. Monacelli, Hybrid interface: Integrating BCI in multimodal humanmachine interfaces, Proc. AIM, pp.530-535, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01352056

R. Rupp, S. C. Kleih, R. Leeb, J. Millan, A. Kübler et al., Brain-Computer-Interfaces in their ethical, social and cultural contexts, vol.12, pp.7-38, 2014.

J. R. Wolpaw, N. Birbaumer, D. J. Mcfarland, G. Pfurtscheller, and T. M. Vaughan, Brain-computer interfaces for communication and control, Clin. Neurophysiol, vol.113, issue.6, pp.767-791, 2002.

G. Pfurtscheller, D. Flotzinger, and J. Kalcher, Brain-Computer Interface-a new communication device for handicapped persons, J. Microcomput. Appl, vol.16, issue.3, pp.293-299, 1993.

T. Castermans, M. Duvinage, G. Cheron, and T. Dutoit, Towards Effective Non-Invasive Brain-Computer Interfaces Dedicated to Gait Rehabilitation Systems, Brain Sci, vol.4, issue.1, pp.1-48, 2013.

B. Rebsamen, E. Burdet, C. Guan, C. L. Teo, Q. Zeng et al., Controlling a wheelchair using a BCI with low information transfer rate, Proc. ICORR, pp.1003-1008, 2007.

L. A. Farwell and E. Donchin, Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials, Electroencephalogr. Clin. Neurophysiol, vol.70, issue.6, pp.510-523, 1988.

L. Tonin, T. Carlson, R. Leeb, and J. Del-r-millan, Braincontrolled telepresence robot by motor-disabled people, Proc. EMBC, pp.4227-4230, 2011.

C. J. Bell, P. Shenoy, R. Chalodhorn, and R. P. Rao, Control of a humanoid robot by a noninvasive brain-computer interface in humans, J. Neural Eng, vol.5, issue.2, pp.214-220, 2008.

R. Tomari, R. R. Hassan, W. N. Zakaria, and R. Ngadengon, Analysis of Optimal Brainwave Concentration Model for Wheelchair Input Interface, Procedia Comput. Sci, vol.76, pp.336-341, 2015.

G. Cisotto, S. Pupolin, M. Cavinato, and F. Piccione, An EEG-Based BCI Platform to Improve Arm Reaching Ability of Chronic Stroke Patients by Means of an Operant Learning Training with a Contingent Force Feedback, Int. J. E-Health Med. Commun, vol.5, issue.1, pp.114-134, 2014.

N. R. Pal, C. Chuang, L. Ko, C. Chao, T. Jung et al., EEG-Based Subject-and Sessionindependent Drowsiness Detection: An Unsupervised Approach, EURASIP J. Adv. Signal Process, issue.1, pp.519-480, 2008.

A. Picot, S. Charbonnier, and A. Caplier, On-line automatic detection of driver drowsiness using a single electroencephalographic channel, Proc. EMBC, pp.3864-3867, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00359392

W. Zhou and J. Gotman, Automatic removal of eye movement artifacts from the EEG using ICA and the dipole model, Prog. Nat. Sci, vol.19, issue.9, pp.1165-1170, 2009.

O. G. Lins, D. T. Picton, P. Berg, and M. Scherg, Ocular artifacts in recording EEGs and event-related potentials II: Source dipoles and source components, Brain Topogr, vol.6, issue.1, pp.65-78, 1993.

A. Schlögl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb et al., A fully automated correction method of EOG artifacts in EEG recordings, Clin. Neurophysiol, vol.118, issue.1, pp.98-104, 2007.

H. Martin, S. Chevallier, and E. Monacelli, Fast calibration of hand movement-based interface for arm exoskeleton control, Proc. ESANN, pp.573-578, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00757886

P. Duhamel and M. Vetterli, Fast fourier transforms: A tutorial review and a state of the art, vol.19, pp.259-299, 1990.

M. Baklouti, P. Guyot, E. Monacelli, and S. Couvet, Force controlled upper-limb powered exoskeleton for rehabilitation, Proc. IROS, pp.4202-4202, 2008.