Browsing by Author "Erwin, Andrew"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Kinesthetic Feedback during 2DOF Wrist Movements via a Novel MR-Compatible Robot
    (IEEE, 2016) Erwin, Andrew; O’Malley, Marcia K.; Ress, David; Sergi, Fabrizio
    We 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.
  • Thumbnail Image
    Item
    Quantitative Testing of fMRI-Compatibility of an Electrically Active Mechatronic Device for Robot-Assisted Sensorimotor Protocols
    (IEEE, 2018) Farrens, Andria J.; Zonnino, Andrea; Erwin, Andrew; O'Malley, Marcia K.; Johnson, Curtis L.; Ress, David; Sergi, Fabrizio; Mechatronics and Haptic Interfaces Laboratory
    OBJECTIVE: To develop a quantitative set of methods for testing the functional magnetic resonance imaging (fMRI) compatibility of an electrically-active mechatronic device developed to support sensorimotor protocols during fMRI. METHODS: The set of methods includes phantom and in vivo experiments to measure the effect of a progressively broader set of noise sources potentially introduced by the device. Phantom experiments measure the radio-frequency (RF) noise and temporal noise-to-signal ratio (tNSR) introduced by the device. The in vivo experiment assesses the effect of the device on measured brain activation for a human subject performing a representative sensorimotor task. The proposed protocol was validated via experiments using a 3T MRI scanner operated under nominal conditions and with the inclusion of an electrically-active mechatronic device - the MR-SoftWrist - as the equipment under test (EUT). RESULTS: Quantitative analysis of RF noise data allows detection of active RF noise sources both in controlled RF noise conditions, and in conditions resembling improper filtering of the EUT's electrical signals. In conditions where no RF noise was detectable, the presence and operation of the EUT did not introduce any significant increase in tNSR. A quantitative analysis conducted on in vivo measurements of the number of active voxels in visual and motor areas further showed no significant difference between EUT and baseline conditions. CONCLUSION AND SIGNIFICANCE: The proposed set of quantitative methods supports the development and troubleshooting of electrically-active mechatronic devices for use in sensorimotor protocols with fMRI, and may be used for future testing of such devices.
  • Thumbnail Image
    Item
    Series Elastic Actuation: Facilitating Robotic Assessment of Human Neurological and Biomechanical Properties
    (2018-04-20) Erwin, Andrew; O'Malley, Marcia K
    This thesis proposes integrating series elastic actuators into the design of robots that facilitate assessment of human neurological function and biomechanical properties. Such assessments can provide objective measures of the physiological adaptations which promote recovery after neurological injury, such as stroke or spinal cord injury. These adaptations are currently not well-understood, leading to variable recovery despite intensive rehabilitation. The robot-aided assessments reported in this thesis can be used to identify the neurological catalysts for brain plasticity and the biomechanical factors for everyday function essential for motor recovery. Robots currently used for these assessments do not measure torque and so use backdrivable (i.e., low friction) actuators since nonbackdrivable (i.e., high friction) actuators cannot be used for accurate torque control. However, accurate torque control with nonbackdrivable actuators can be achieved through series elastic actuation, a design in which an elastic element is purposefully incorporated in series between the actuator and user. To overcome limitations found in existing backdrivable robots, this thesis develops two novel series elastic actuated assessment robots with nonbackdrivable actuators for applications in robot-aided assessment. In the first application, brain activity is acquired through functional magnetic resonance imaging during physical human-robot interaction with the Magnetic Resonance Soft Wrist (MR-SoftWrist) robot. The MR- SoftWrist features series elastic actuation to overcome limitations in using non-ferrous and nonbackdrivable ultrasonic motors. As demonstrated in this thesis, the MR-SoftWrist can interact with the wrist safely and accurately during functional magnetic resonance imaging, while not degrading acquired images of brain activity. In the second application, passive stiffness and active range of motion wrist envelopes are assessed with the novel Series Elastic Assessment Wrist (SE-AssessWrist) exoskeleton. The SE-AssessWrist employs rotary series elastic actuators to provide accurate torque estimation and zero force control, despite using nonbackdrivable actuators consisting of geared motors and a flexible Bowden cable transmission. The SE-AssessWrist can facilitate measurement of wrist biomechanics, in particular determination of the axis of least stiffness and greatest range of motion, which does not coincide with anatomical axes. As an important first step towards improved robotic rehabilitation, the proposed robot-aided assessments in this thesis are validated in able-bodied human experiments.
  • Thumbnail Image
    Item
    The effect of robot dynamics on smoothness during wrist pointing
    (IEEE, 2017) Erwin, Andrew; Pezent, Evan; Bradley, Joshua; O’Malley, Marcia K.
    The improvement of movement smoothness over the course of therapy is one of the positive outcomes observed during robotic rehabilitation. Although movements are generally robust to disturbances, certain perturbations might disrupt an individual's ability to produce these smooth movements. In this paper, we explore how a rehabilitation robot's inherent dynamics impact movement smoothness during pointing tasks. Able-bodied participants made wrist pointing movements under four different operating conditions. Despite the relative transparency of the device, inherent dynamic characteristics negatively impacted movement smoothness. Active compensation for Coulomb friction effects failed to mitigate the degradation in smoothness. Assessment of movements that involved coupled motions of the robot's joints reduced the bias seen in single degree of freedom movements. When using robotic devices for assessment of movement quality, the impact of the inherent dynamics must be considered.
  • Thumbnail Image
    Item
    Using Custom Integrated Force Sensing Mechanisms for Interaction Control in Rehabilitation Robots
    (2014-04-25) Erwin, Andrew; O'Malley, Marcia K.; Ghorbel, Fathi H.; McLurkin, James; Sergi, Fabrizio
    This thesis presents the implementation of interaction controllers on two custom integrated force sensing mechanisms and demonstrates their suitability for applications to the field of rehabilitation robotics. One condition in which interaction control is beneficial occurs when the robot's dynamics are significant and need to be compensated through force-feedback. To address this need, a grip force sensor that measures forces in three planes by using force sensing resistors was developed. The device readily integrates with most rehabilitation robots at the end effector. Additionally, if a robot is non-backdrivable, force measurement is required to render transparent environments during evaluation mode as well as for interaction control. Here, interaction controllers are implemented in a 1DOF MR-compatible actuation module. The MR-compatible device uses a non-backdrivable actuator with series elasticity for force sensing. Experimental implementation of interaction controllers on both devices demonstrates the advantages of closed-loop force control.