@proceedings {1882,
	title = {Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke},
	year = {2014},
	month = {08/2014},
	keywords = {Accuracy, Adult, bioelectric potentials, brain-computer interfaces, closed loop systems, closed-loop brain-machine interfaces, Computer-Assisted, diseases, electroencephalography, Electromyography, Exoskeletons, hemiparesis, Humans, Male, medical robotics, medical signal detection, medical signal processing, Middle Aged, Movement, movement intent detection, neurophysiology, Paresis, Patient rehabilitation, Robotics, Robots, scalp electroencephalography, Signal Processing, stroke, stroke rehabilitation, Support Vector Machine, Support vector machines, training, Upper Extremity, upper extremity dysfunction, upper limb robotic rehabilitation system, Young Adult},
	doi = {10.1109/EMBC.2014.6944532},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/bhagat2014ieee.pdf},
	author = {N. A. Bhagat and J. French and A. Venkatakrishnan and N. Yozbatiran and G. E. Francisco and M. K. O{\textquoteright}Malley and J. L. Contreras-Vidal}
}
