@proceedings {1885,
	title = {A Cable-based Series Elastic Actuator with Conduit Sensor for Wearable Exoskeletons},
	year = {2017},
	month = {05/2017},
	publisher = {IEEE},
	address = {Singapore},
	keywords = {actuation system design, Actuators, cable tension control, cable tension measurement, cable-based series elastic actuator, cable-conduit transmission, cables (mechanical), compliance control, compliant force sensor, conduit sensor, DC motor, DC motors, deflection measurement, dynamic effect, Exoskeletons, Feedback, flexible cable conduit transmission, Force, Force control, force sensors, full wearable exosuit, gearbox, Hall effect sensors, Hall effect transducers, human arm, human-robot interaction, Impedance, Magnetic flux, physical assistance, robot dynamics, Robots, series elastic force sensor, soft exosuit, soft wearable exoskeleton, springs (mechanical), translational steel compression spring, transmission conduit, user interface, virtual impedance, wearable robotic device},
	doi = {10.1109/ICRA.2017.7989790},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/blumenschein2017ieee.pdf},
	author = {L. H. Blumenschein and C. G. McDonald and M. K. O{\textquoteright}Malley}
}
@proceedings {1923,
	title = {Combining functional electrical stimulation and a powered exoskeleton to control elbow flexion},
	year = {2017},
	month = {11/2017},
	pages = {87-88},
	keywords = {Elbow, elbow flexion, Exoskeletons, extension trajectory, functional electrical stimulation, hybrid FES, hybrid system, Iron, medical robotics, Muscles, neuromuscular stimulation, Patient rehabilitation, robotic exoskeleton system, Robots, Torque, Trajectory, upper-limb paralysis},
	doi = {10.1109/WEROB.2017.8383860},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/Wolf2017werob.pdf},
	author = {D. Wolf and N. Dunkelberger and C. G. McDonald and K. Rudy and C. Beck and M. K. O{\textquoteright}Malley and E. Schearer}
}
@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}
}
@proceedings {1880,
	title = {Robotic training and clinical assessment of forearm and wrist movements after incomplete spinal cord injury: A case study},
	year = {2011},
	month = {June},
	pages = {619-622},
	abstract = {<p>The effectiveness of a robotic training device was evaluated in a 24-year-old male, cervical level four, ASIA Impairment Scale D injury. Robotic training of both upper extremities was provided for three hr/day for ten consecutive sessions using the RiceWrist, an electrically-actuated forearm and wrist haptic exoskeleton device that has been designed for rehabilitation applications. Training involved wrist flexion/extension, radial/ulnar deviation and forearm supination/pronation. Therapy sessions were tailored, based on the patient{\textquoteright}s movement capabilities for the wrist and forearm, progressed gradually by increasing number of repetitions and resistance. Outcome measures included the ASIA upper-extremity motor score, grip and pinch strength, the Jebsen-Taylor Hand Function test and the Functional Independence Measure. After the training, improvements were observed in pinch strength, and functional tasks. The data from one subject provides valuable information on the feasibility and effectiveness of robotic-assisted training of forearm and hand functions after incomplete spinal cord injury.</p>},
	keywords = {age 24 yr, arm motor function recovery, ASIA upper-extremity motor score, biomechanics, clinical assessment, electrically-actuated forearm, Forearm, forearm movement, forearm pronation, forearm supination, functional independence measure, functional tasks, grip, Haptic interfaces, Humans, injuries, Jebsen-Taylor hand function test, Joints, Male, medical robotics, Medical treatment, Muscles, neurophysiology, patient movement capabilities, Patient rehabilitation, Patient treatment, pinch strength, radial-ulnar deviation, rehabilitation applications, robotic training, Robots, Spinal Cord Injuries, spinal cord injury, training, Wrist, wrist extension, wrist flexion, wrist haptic exoskeleton device, wrist movement, Young Adult},
	doi = {10.1109/ICORR.2011.5975425},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/yozbatiran2011ieee.pdf},
	author = {N. Yozbatiran and J. Berliner and C. Boake and M. K. O{\textquoteright}Malley and Z. Kadivar and G. E. Francisco}
}
