@article {8304762, title = {The hBracelet: a wearable haptic device for the distributed mechanotactile stimulation of the upper limb}, journal = {IEEE Robotics and Automation Letters}, volume = {3}, number = {3}, year = {2018}, month = {2018}, pages = {2198-2205}, abstract = {

Haptic interfaces are mechatronic devices designed to render tactile sensations; although they are typically based on robotic manipulators external to the human body, recently, interesting wearable solutions have been presented. Towards a more realistic feeling of virtual and remote environment interactions, we propose a novel wearable skin stretch device for the upper limb called "hBracelet." It consists of two main parts coupled with a linear actuator. Each part contains two servo actuators that move a belt. The device is capable of providing distributed mechanotactile stimulation on the arm by controlling the tension and the distance of the two belts in contact with the skin. When the motors spin in opposite directions, the belt presses into the user{\textquoteright}s arm, while when they spin in the same direction, the belt applies a shear force to the skin. Moreover, the linear actuator exerts longitudinal cues on the arm by moving the two parts of the device. In this work we illustrate the mechanical structure, working principle, and control strategies of the proposed wearable haptic display. We also present a qualitative experiment in a teleoperation scenario as a case study to demonstrate the effectiveness of the proposed haptic interface and to show how a human can take advantage of multiple haptic stimuli provided at the same time and on the same body area. The results show that the device is capable of successfully providing information about forces acting at the remote site, thus improving telepresence.

}, keywords = {Actuators, Belts, Force, Haptic interfaces, Haptics and haptic interfaces, Human-Centered Robotics, Pulleys, Robots, Skin, Telerobotics and Teleoperation, Wearable Robots}, doi = {10.1109/LRA.2018.2810958}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/meli2018ieee.pdf}, author = {L. Meli and I. Hussain and M. Aurilio and M. Malvezzi and M. O{\textquoteright}Malley and D. Prattichizzo} } @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} } @article {6878466, title = {A Subject-Adaptive Controller for Wrist Robotic Rehabilitation}, journal = {Mechatronics, IEEE/ASME Transactions on}, volume = {20}, number = {3}, year = {2015}, pages = {1338 - 1350}, keywords = {adaptive control, Exoskeletons, Force, Iron, Medical treatment, nonlinear systems, parallel mechanisms, robot dynamics, robotic rehabilitation, Robots, Trajectory, Vectors, Wrist}, issn = {1083-4435}, doi = {10.1109/TMECH.2014.2340697}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/tmech-pehlivan-press.pdf}, author = {Pehlivan, A.U. and Sergi, F. and OMalley, M.K.} } @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 {1706, title = {System characterization of RiceWrist-S: A forearm-wrist exoskeleton for upper extremity rehabilitation}, year = {2013}, month = {June}, keywords = {Actuators, closed loop position performance, closed loop systems, distal joints, Exoskeletons, forearm rehabilitation, forearm-wrist exoskeleton, Friction, haptic interface design, Joints, medical robotics, neurological lesions, neurophysiology, Patient rehabilitation, position control, prosthetics, RiceWrist-S, robotic rehabilitation, Robots, serial mechanisms, spatial resolution, spinal cord injury, spinal cord injury rehabilitation, stroke, stroke rehabilitation, system characterization, Torque, torque output, upper extremity rehabilitation, Wrist, wrist rehabilitation}, doi = {10.1109/ICORR.2013.6650462}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Pehlivan_RW-S_ICORR2013.pdf}, author = {Pehlivan, Ali Utku and Rose, Chad G. and O{\textquoteright}Malley, Marcia K.} } @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 = {

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.

}, 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} } @article {06199869875, title = {Shared control in haptic systems for performance enhancement and training}, journal = {Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME}, volume = {128}, number = {1}, year = {2006}, note = {

Virtual environments;Mass-spring-damper;System dynamics;Shared control;

}, pages = {75 - 85}, chapter = {75}, abstract = {

This paper presents a shared-control interaction paradigm for haptic interface systems, with experimental data from two user studies. Shared control, evolved from its initial telerobotics applications, is adapted as a form of haptic assistance in that the haptic device contributes to execution of a dynamic manual target-hitting task via force commands from an automatic controller. Compared to haptic virtual environments, which merely display the physics of the virtual system, or to passive methods of haptic assistance for performance enhancement based on virtual fixtures, the shared-control approach offers a method for actively demonstrating desired motions during virtual environment interactions. The paper presents a thorough review of the literature related to haptic assistance. In addition, two experiments were conducted to independently verify the efficacy of the shared-control approach for performance enhancement and improved training effectiveness of the task. In the first experiment, shared control is found to be as effective as virtual fixtures for performance enhancement, with both methods resulting in significantly better performance in terms of time between target hits for the manual target-hitting task than sessions where subjects feel only the forces arising from the mass-spring-damper system dynamics. Since shared control is more general than virtual fixtures, this approach may be extremely beneficial for performance enhancement in virtual environments. In terms of training enhancement, shared control and virtual fixtures were no better than practice in an unassisted mode. For manual control tasks, such as the one described in this paper, shared control is beneficial for performance enhancement, but may not be viable for enhancing training effectiveness. Copyright \© 2006 by ASME.

}, keywords = {Control equipment, Damping, Data reduction, Haptic interfaces, Robotics, Robots}, issn = {0022-0434}, doi = {10.1115/1.2168160 }, url = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=JDSMAA000128000001000075000001\&idtype=cvips\&gifs=yes}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/52-00\%20-\%20JDSMC\%20Shared\%20control.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta and Gen, Matthew and Yanfang Li} } @proceedings {04278244642, title = {Cooperative manipulation between humans and teleoperated agents}, year = {2004}, note = {

Robonauts;Haptic feedback;Cooperative manipulation;

}, pages = {114 - 120}, address = {Chicago, IL, United States}, abstract = {

Robonaut is a humanoid robot designed by the Robotic Systems Technology Branch at NASA{\textquoteright}s Johnson Space Center in a collaborative effort with DARPA. This paper describes the implementation of haptic feedback into Robonaut. We conducted a cooperative manipulation task, inserting a flexible beam into an instrumented receptacle. This task was performed while both a human at the worksite and the teleoperated robot grasped the flexible beam simultaneously. Peak forces in the receptacle were consistently lower when the human operator was provided with kinesthetic force feedback in addition to other modalities of feedback such as gestures and voice commands. These findings are encouraging as the Dexterous Robotics Lab continues to implement force feedback into its teleoperator hardware architecture.

}, keywords = {Computer simulation, Feedback, Haptic interfaces, Human computer interaction, Robots, Statistical methods}, url = {http://dx.doi.org/10.1109/HAPTIC.2004.1287185}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/glassmire2004haptics.pdf}, author = {John Glassmire and O{\textquoteright}Malley, M.K. and William Bluethmann and Robert O. Ambrose} } @proceedings {05239144488, title = {Design of a haptic arm exoskeleton for training and rehabilitation}, volume = {73}, number = {2 PART B}, year = {2004}, note = {

Haptic arm exoskeleton;Inertia;Structural stiffness;Kinesthetic feedback;

}, pages = {1011 - 1018}, address = {Anaheim, CA, United States}, abstract = {

A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of additional parameters and constraints including space and weight limitations, workspace requirements and the kinematic constraints placed on the device by the human arm. In this context, we present the design of a five degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments. The design of the device, including actuator and sensor selection, is discussed. Limitations of the device that result from the above selections are also presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Copyright {\textcopyright} 2004 by ASME.

}, keywords = {Actuators, Bandwidth, Damping, Degrees of freedom (mechanics), Friction, Human computer interaction, Kinematics, Robotic arms, Robots, Sensors, Stiffness}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/gupta2004asme.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} }