J. B. Sanderson, The Electrical Response to Stimulation of Muscle, and its Relation to the Mechanical Response, J. Physiol, vol.1895, pp.117-160

A. Kralj, T. Bajd, and R. Turk, Electrical stimulation providing functional use of paraplegic patient muscles, Med. Prog. Technol, vol.7, pp.3-9, 1980.

D. Popovi? and T. Sinkjaer, Control of Movement for the Physically Disabled: Control for Rehabilitation Technology

. Springer, , 2000.

D. J. Mcfarland and J. R. Wolpaw, Brain-Computer Interface Operation of Robotic and Prosthetic Devices, Computer, vol.41, pp.52-56, 2008.

N. Rashid, J. Iqbal, A. Javed, M. Tiwana, and U. Khan, Design of Embedded System for Multivariate Classification of Finger and Thumb Movements Using EEG Signals for Control of Upper Limb Prosthesis, Biomed Res. Int, 2018.

M. G. Antonelli, P. Beomonte-zobel, and J. Giacomin, Use of MMG Signals for the Control of Powered Orthotic Devices: Development of a Rectus Femoris Measurement Protocol, Assist. Technol, vol.21, 2009.

A. Posatskiy and T. Chau, The effects of motion artifact on mechanomyography: A comparative study of microphones and accelerometers, J. Electromyogr. Kinesiol, vol.22, 2012.

Y. Chen and W. Newman, A human-robot interface based on electrooculography, Proceedings of the IEEE International Conference on Robotics and Automation, 2004.

, , pp.243-248

C. H. Morimoto and M. R. Mimica, Eye gaze tracking techniques for interactive applications, Comput. Vis. Image Underst, vol.98, 2005.

B. H. Fan and K. Y. Li, The Speech Control System of Intelligent Robot Prosthesis, Proceedings of the IEEE Second WRI Global Congress on Intelligent Systems, pp.407-409, 2010.

X. Lv, M. Zhang, and H. Li, Robot control based on voice command, Proceedings of the, 2008.

, IEEE International Conference on Automation and Logistics, pp.1-3, 2008.

A. E. Schultz and T. A. Kuiken, Neural Interfaces for Control of Upper Limb Prostheses: The State of the Art and Future Possibilities, PM R, vol.3, 2011.

T. Keller, A. Curt, M. R. Popovic, A. Signer, and V. Dietz, Grasping in high lesioned tetraplegic subjects using the EMG controlled neuroprosthesis, NeuroRehabilitation, vol.10, pp.251-255, 1998.

R. Kirsch, P. Parikh, and A. Acosta, Van Der Helm, F. Feasibility of EMG-based control of shoulder muscle FNS via artificial neural network, Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol.2, pp.25-28, 2001.

M. Dicicco, L. Lucas, and Y. Matsuoka, Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand, Proceedings of the IEEE International Conference on Robotics and Automation, vol.2, pp.1622-1627, 2004.

H. Jiang, J. P. Wachs, and B. S. Duerstock, Integrated vision-based robotic arm interface for operators with upper limb mobility impairments, Proceedings of the 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), pp.24-26, 2013.

J. C. Moreno, E. R. De-lima, A. F. Ruíz, F. J. Brunetti, and J. L. Pons, Design and implementation of an inertial measurement unit for control of artificial limbs: Application on leg orthoses, Sens. Actuators B Chem, vol.118, pp.333-337, 2006.

M. W. Keith, P. H. Peckham, G. B. Thrope, K. C. Stroh, B. Smith et al., Implantable functional neuromuscular stimulation in the tetraplegic hand, J. Hand Surg, vol.14, pp.524-530, 1989.

W. D. Memberg, K. H. Polasek, R. L. Hart, A. M. Bryden, K. L. Kilgore et al., Implanted neuroprosthesis for restoring arm and hand function in people with high level tetraplegia, Arch. Phys. Med. Rehabil, vol.95, pp.1201-1211, 2014.

A. Ajiboye, F. Willett, D. Young, W. Memberg, B. Murphy et al., Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: A proof-of-concept demonstration, Lancet, vol.389, 2017.

C. E. Bouton, A. Shaikhouni, N. V. Annetta, M. A. Bockbrader, D. A. Friedenberg et al., Restoring cortical control of functional movement in a human with quadriplegia, Nature, vol.533, p.247, 2016.

J. Lobo-prat, P. N. Kooren, A. H. Stienen, J. L. Herder, B. F. Koopman et al., Non-invasive control interfaces for intention detection in active movement-assistive devices, J. Neuroeng. Rehabil, vol.11, 2014.

W. Tigra, B. Navarro, A. Cherubini, X. Gorron, A. Gelis et al., A novel EMG interface for individuals with tetraplegia to pilot robot hand grasping, IEEE Trans. Neural Syst. Rehabil. Eng, vol.26, pp.291-298, 2016.
URL : https://hal.archives-ouvertes.fr/lirmm-01373668

P. Sarcevic, Z. Kincses, and S. Pletl, Wireless Sensor Network based movement classification using wrist-mounted 9DOF sensor boards, Proceedings of the IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), 2014.

A. Phinyomark, R. Khushaba, and E. Scheme, Feature Extraction and Selection for Myoelectric Control Based on, Wearable EMG Sensors. Sensors, vol.18, 1615.

C. L. Fall, F. Quevillon, M. Blouin, S. Latour, A. Campeau-lecours et al., A Multimodal Adaptive Wireless Control Interface for People With Upper-Body Disabilities, IEEE Trans. Biomed. Circuits Syst, vol.12, 2018.

S. Micera, T. Keller, M. Lawrence, M. Morari, and D. B. Popovic, Wearable Neural Prostheses, IEEE Eng. Med. Biol. Mag, vol.29, pp.64-69, 2010.

A. L. Benabid, T. Costecalde, A. Eliseyev, G. Charvet, A. Verney et al., An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: A proof-of-concept demonstration, Lancet Neurol, issue.19, pp.30321-30328, 2019.

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