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 subjects 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

 K. Schmidt, B. Berret, F. Sergi, “Development of an Experimental Protocol to Study the Neural Control of Force and Impedance in Wrist Movements with Robotics and fMRI”, 2024, doi: 10.1101/2024.02.19.581013, pre-print.

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, 2018, 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

Feedback reflex control is an important mechanism of motor control and multiple motor pathways are involved in feedback loops. Specifically, long-latency responses (LLRs) are semi-reflexive muscle responses that are composed of spinal, subcortical, and cortical components. 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 MR-compatible 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 θ_FE = [−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. 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, 2019, pre-print, available online.

Dual Motor StretchWrist (DMSW)

Secondary motor pathways have been suggested to contribute to the increase in the long-latency response observed when individuals are asked to “resist” a perturbation. However, a lack of methods to measure in-vivo function of cortical and subcortical brain regions when instructed to resist a stretch reflex has limited the knowledge of the direct role of secondary motor pathways on the long-latency response associated with task instruction. Functional MRI during robot-evoked LLRs under different task instructions may be a method to probe and measure motor-related function in the brainstem. To this end, we have developed the Dual Motor StretchWrist(DMSW), a new MR-compatible robotic perturbation system capable of eliciting stretch reflexes when individuals are instructed to resist a perturbation in the MRI scanner. The DMSW is a 1-degree-of-freedom wrist robot capable of imposing controlled perturbations to the hand about the wrist flexion/extension axis in the range of θ_FE = [-45, 45]° with up to 6 Nm of peak torque. It is actuated by two ultrasonic piezoelectric motors connected in parallel (EN60 motor, Shinsei Motor Inc., Japan) via a capstan transmission with a 3:1 gear ratio to transfer motion from the motors to the end effector. The capstan drive consists of 3 pulleys with different diameters connected with a smooth cable wrapped multiple times to ensure no slippage, high friction contact.

(A) Dual Motor StretchWrist top view with a participant’s hand. (B)
Exploded view of the Dual Motor StretchWrist. (1) Output capstan arc, (2)
structural ceramic bearings, (3) tensioning mechanisms, (4) MR-compatible
force/torque sensor, (5) ultrasonic motors, and (6) hand support.

Publications on this topic

R. C. Nikonowicz, F. Sergi, “Development of an MRI-compatible robotic perturbation system for studying the task-dependent contribution of the brainstem to long-latency responses”, 2024, doi: 10.1101/2024.03.01.583025, pre-print.

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 magnetic resonance elastography can measure the force applied by multiple muscles during isometric tasks. With magnetic resonance elastography, we can measure the speed that shear waves propagate in all forearm muscles, which we know is load-dependent, and quantify the changes in muscle mechanical properties under different conditions of neural activation and joint angle. To obtain muscle shear wave velocities during isometric wrist tasks, we have developed an MR-compatible forearm device which allows us to measure flexion/extension and radio/ulnar deviation wrist joint torques and wrist angle during magnetic resonance imaging. The robotic device, the MRE-bot, is shown below in its design and incorporation within the MRI scanner.

(1) Force/Torque sensor, (2) hand support, (3) optical encoder, (4) forearm support, (5) locking mechanism, (6) mechanical vibrator, (7) MR flex coil.

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, 2019, pre-print, available online.

Simultaneous TMS and Functional MRI

We are interested in studying the causal role of various motor pathways on stretch reflexes. Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that involves targeting cortical brain regions to investigate their role in motor control or connectivity with other brain regions. When applied to the motor cortex, TMS induces changes to the excitability of the corticospinal pathway which can be quantified using surface electromyography (EMG) on the targeted muscle. In our work, we are interested in studying the effects of inhibitory TMS on cortical and subcortical brain function during wrist perturbations. To do this, we combine single TMS pulses with functional MRI and surface EMG to quantify the effect of TMS on whole brain function and its association with muscle activity. We use an MR-compatible TMS coil (MR-B91 coil, MagVenture Inc., Alpharetta, GA), held in place using a TMS coil holder (MagVenture Inc., Alpharetta, GA), to apply stimulation pulses during MRI scanning. An 8 channel head array (RAPID Biomedical, Germany) is used to collect functional images allowing to fit the TMS coil inside the imaging coil. The MR-compatible TMS coil is shown below in its design and its incorporation with the participant within the MRI scanner.

Publications on this topic

C. A. Helm, F. Sergi, “Inhibitory Effect of Subthreshold TMS on the Long-latency Response in the Flexor Carpi Radialis”, in review, doi: 10.1101/2024.03.18.585555, pre-print.