MR-SoftWrist
We are interested in observing the neural processes responsible for learning a motor skill and for recovery after neurological injury through functional MRI, and we want to be able to do that while subject are actively involved in a motor learning or motor adaptation session. To this aim, we have recently developed an MR-compatible wrist exoskeleton capable of accurate haptic feedback during wrist pointing movements. The robotic device, the MR-SoftWrist, is shown below in its design and in a 3D rendering showing its location during operation in the scanner.
Publications on this topic
A. J. Farrens, S. Vahdat, F. Sergi, “Changes in Resting State Functional Connectivity Associated with Dynamic Adaptation of Wrist Movements“, accepted, Journal of Neuroscience, vol. 43, no. 19, pp. 3520-3537, May 2023, doi: 10.1109/TNSRE.2023.3242601, available online, pre-print.
A. J. Farrens, K. Schmidt, H. N. Cohen, F. Sergi, “Concurrent Contribution of Co-Contraction to Error Reduction During Dynamic Adaptation of the Wrist”, accepted, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 1287-1296, Feb. 2023, doi: 10.1109/TNSRE.2023.3242601, available online, pre-print.
A. J. Farrens, F. Sergi, ”Characterizing adaptive behavior of the wrist during lateral force perturbations”, IEEE/RAS-EMBS International Conference on Biomedical Robotics, New York City, November 2020, pre-print, available online. Nominated for Best Student Paper Award.
A. J. Farrens, F. Sergi, ”Neural correlates of dynamic adaptation and motor memory formation in two-degree of freedom wrist pointing”, IEEE/RAS-EMBS International Conference on Biomedical Robotics, New York City, November 2020, pre-print.
A. J. Farrens, A. Zonnino, F. Sergi,“Effects of force-field adaptation on neural activation and resting-state functional connectivity”, International Conference on Neurorehabilitation, available online, pre-print.
A. J. Farrens, A. Zonnino, A. Erwin, M. K. O’Malley, C. L. Johnson, D. Ress, F. Sergi, “Quantitative testing of fMRI-compatibility of an electrically active mechatronic device for robot-assisted sensorimotor protocols”, IEEE Transactions on Biomedical Engineering, vol. 65, no. 7, pp. 1595 – 1606, 2018 – doi: 10.1109/TBME.2017.2741346 – available online. pre-print
MR-StretchWrist
Long Latency Responses (LLRs) can be elicited in the forearm muscles with background wrist torque and perturbation velocities that range from 0 to 0.5 Nm and from 100 to 250 deg/s, respectively. To apply such perturbations, we have developed a novel robotic device, the MR-StretchWrist (MR-SW). The MR-SW is a 1-Degree of Freedom (DOF) robot capable of applying controlled movement to the wrist Flexion/Extension (FE) axis in a range of θFE = [−45; 45] deg. It is actuated by an ultrasonic piezoelectric motor (EN60 motor, Shinsei Motor Inc., Japan) which provides 1 Nm peak torque and 900 deg/s peak velocity. To fulfill the design specifications, we have employed a capstan transmission with 3:1 gear ratio to transfer motion from the motor to the end effector. The capstan drive consists of two pulleys with different diameters connected together with a smooth cable that, to ensure no-slippage high-friction contact, is wrapped around the pulleys multiple times to ensure no-slippage, high-friction contact. The MR-SW is instrumented with a six-axis MR-compatible Force/Torque sensor (Mini27Ti, ATI Industrial Automation, Apex, NC) to measure wrist joint torque. Please see Zonnino, 2019 for our assessment of the MR-SW’s MR-compatibility.
Exploded view (top) and prototype (bottom) of the MR-StretchWrist. (1) Ultrasonic motor, (2) output capstan arc, (3) input pulley, (4) tensioning mechanisms, (5) structural bearings, (6) force/torque sensor, (7) hand support
Publications on this topic
A. Zonnino, A. J. Farrens, D. Ress, F. Sergi, “Measurement of stretch-evoked brainstem function using fMRI”, Scientific reports, vol. 11, no. 12544, 2021, available online, pre-print.
J. Weinman, P. Arfa-Fatollahkhani, A. Zonnino, R. C. Nikonowicz, F. Sergi, “Effects of Perturbation Velocity, Direction, Background Muscle Activation, and Task Instruction on Long-Latency Responses Measured From Forearm Muscles”, Frontiers in Human Neuroscience, vol. 15, April 2021, https://doi.org/10.3389/fnhum.2021.639773, available online.
A. Zonnino, A. J. Farrens, F. Sergi, “StretchfMRI: a new technique to quantify the contribution of the reticular formation to long-latency responses via fMRI”, 16th International Conference on Rehabilitation Robotics, pre-print, available online.
MRE-bot
We are interested in studying how the central nervous system coordinates the action of multiple muscles in the forearm to control movements of the wrist while maintaining efficiency and stability. In this project, in collaboration with the Mechanical Neuroimaging Lab at the University of Delaware, we aim to establish if shear-wave elastography can indeed measure the force applied by multiple muscles during isometric tasks. With shear-wave elastography, we can measure the speed of propagation of shear waves in all muscles of the forearm, which we know is load-dependent, and quantify the changes in muscle mechanical properties under different conditions of neural activation. To obtain muscle shear wave velocities during isometric wrist tasks, we have developed an MR-compatible forearm device which allows us to measure wrist joint torques and postures during magnetic resonance imaging. The robotic device, the MRE-bot, is shown below in its design and incorporation within the MRI scanner.
Publications on this topic
D. R. Smith*, C. A. Helm*, A. Zonnino, M. D. J. McGarry, C. L. Johnson*, F. Sergi*, “Individual Muscle Force Estimation in the Human Forearm Using Multi-Muscle MR Elastography (MM-MRE)”, accepted, IEEE Transactions on Biomedical Engineering vol. 70, no. 11, pp. 3206-3215, Nov. 2023, doi: 10.1109/TNSRE.2023.3242601, available online, pre-print.
A. Zonnino, D. R. Smith, P. L. Delgorio, C. L. Johnson, F. Sergi, “MM-MRE: a new technique to quantify individual muscle forces during wrist isometric contractions using MR Elastography”,16th International Conference on Rehabilitation Robotics, pre-print, available online.
