Erwin, AndrewO’Malley, Marcia K.Ress, DavidSergi, Fabrizio2017-08-042017-08-042016Erwin, Andrew, O’Malley, Marcia K., Ress, David, et al.. "Kinesthetic Feedback during 2DOF Wrist Movements via a Novel MR-Compatible Robot." <i>IEEE Transactions on Neural Systems and Rehabilitation Engineering,</i> PP, no. 99 (2016) IEEE: https://doi.org/10.1109/TNSRE.2016.2634585.https://hdl.handle.net/1911/96583We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N·m of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius. Via dynamic characterization, we demonstrate capability for transparent operation with low (10% of maximum torque output) backdrivability torques at nominal speeds. Moreover, we demonstrate a 5.5 Hz stiffness control bandwidth for a 14 dB range of virtual stiffness values, corresponding to 25-125% of the device’s physical reflected stiffness in the nominal configuration. We finally validate the possibility of operation during fMRI via a case study involving one healthy subject. Our validation experiment demonstrates the capability of the device to apply kinesthetic feedback to elicit distinguishable kinetic and neural responses without significant degradation of image quality or task-induced head movements. With this study, we demonstrate the feasibility of MR-compatible devices like the MR-SoftWrist to be used in support of motor control experiments investigating wrist pointing under robot-applied force fields. Such future studies may elucidate fundamental neural mechanisms enabling robot-assisted motor skill learning, which is crucial for robot-aided neurorehabilitation.engThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE.Journal articleErwin2017_MR_SoftWristhttps://doi.org/10.1109/TNSRE.2016.2634585