MR-compatible Robotics

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.

Untitledmrsw_physNOLOGO

The robot is actuated by traveling-wave ultrasonic piezoelectric motors with high intrinsic impedance. To enable interaction control, an inner force control loop is closed on the force estimate provided by Series Elastic elements ((phosphor bronze extension springs – for more details, please ref to this paper). Leveraging this actuation technology, the MR-SoftWrist can be controlled to display force fields in its task space (wrist flexion-extension and radial-ulnar deviation), through a simple impedance control loop with gravity compensation.

MR-SW control

 

Publications on this topic

A. J. Farrens, A. Zonnino, F. Sergi, “Determining the fMRI compatibility of an electrically active robot”, 43rd Annual Northeast Bioengineering Conference, Newark NJ, Mar 2017. [podium presentation], pdf.

A. Erwin, M. K. O’Malley, D. Ress, F. Sergi, “Kinesthetic Feedback During 2DOF Wrist Movements via a Novel MR-Compatible Robot”, in press, IEEE Transactions on Neural Systems and Rehabilitation Engineering. –  available onlinepdf (pre-print).

F. Sergi, A. Erwin, M. K. O’Malley, “Interaction control capabilities of an MR-compatible compliant actuator for wrist sensorimotor protocols during fMRI”, IEEE/ASME Transactions on Mechatronics, doi:10.1109/TMECH.2015.2389222 – available online , pdf

F. Sergi, M. K. O’Malley, “On the stability and accuracy of high stiffness rendering in non-backdrivable actuators through series elasticity”, Mechatronics , vol. 26, pp. 64-75 – doi: 10.1016/j.mechatronics.2015.01.007 – available online pdf

A. Erwin, M. K. O’Malley, D. Ress, F. Sergi, “Development, control, and MRI compatibility of the MR-SoftWrist”, Proceedings of the IEEE/RAS-EMBS International Conference on Rehabilitation Robotics, Singapore, August 2015, pdf

F. Sergi, H. I. Krebs, B. Groisser, A. Rykman, B. T. Volpe, E. Guglielmelli, J. D. Schaechter, “Predicting Efficacy of Robot-Aided Rehabilitation in Chronic Stroke Patients using an MRI-Compatible Robotic Device”, 33rd International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, September 2011, doi: 10.1109/IEMBS.2011.6091843.

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