Browsing by Author "Sergi, Fabrizio"

Now showing 1 - 6 of 6
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    Characterization of a hand-wrist exoskeleton, READAPT, via kinematic analysis of redundant pointing tasks
    (IEEE, 2015) Rose, Chad G.; Sergi, Fabrizio; Yun, Youngmok; Madden, Kaci; Deshpande, Ashish D.; O'Malley, Marcia K.; Mechatronics and Haptic Interfaces Laboratory
    Training coordinated hand and wrist movement is invaluable during post-neurological injury due to the anatomical, biomechanical, and functional couplings of these joints. This paper presents a novel rehabilitation device for coordinated hand and wrist movement. As a first step towards validating the new device as a measurement tool, the device transparency was assessed through kinematic analysis of a redundant finger pointing task requiring synergistic movement of the wrist and finger joints. The preliminary results of this new methodology showed that wearing the robot affects the kinematic coupling of the wrist and finger for unconstrained pointing tasks. However, further experiments specifying a subset of the solution manifold did not exhibit the same difference between robot and no robot trials. The experiments and analysis form a promising method for the characterization of multi-articular wearable robots as measurement tools in robotic rehabilitation.
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    Design of a parallel-group balanced controlled trial to test the effects of assist-as-needed robotic therapy
    (IEEE, 2015) Sergi, Fabrizio; Pehlivan, Ali Utku; Fitle, Kyle; Nedley, Kathryn; Yozbatiran, Nuray; Francisco, Gerard E.; O’Malley, Marcia K.; Mechatronics and Haptic Interfaces Laboratory
    In this methods paper, we report on the design of a clinical study testing the efficacy of a newly developed control scheme for robot-aided rehabilitation. To measure the value added by a new control scheme, we pursued a parallel-group controlled clinical study design. This approach enables comparing the effects of the novel scheme, based on the Assist-As-Needed (AAN) paradigm, with those of a less sophisticated, fixed gain, Subject-Triggered (ST) controller. We describe the steps followed in the design of this clinical study, including details on the implementation of the two control modes, and a power analysis to determine the required number of subjects to test a clinically significant difference hypothesis. Finally, we present a method for sequential group assignment with co-variates minimization, capable of guaranteeing a desired level of balance of prognostic factors in the two study groups, a crucial requisite for small-scale clinical studies in rehabilitation. To the best of our knowledge, the study presented is the first one testing, in a controlled fashion, the differential effects of a specific control mode in upper extremity rehabilitation after incomplete spinal cord injury.
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    Effects of Assist-As-Needed Upper Extremity Robotic Therapy after Incomplete Spinal Cord Injury: A Parallel-Group Controlled Trial
    (Frontiers Media S.A., 2017) Frullo, John Michael; Elinger, Jared; Pehlivan, Ali Utku; Fitle, Kyle; Nedley, Kathryn; Francisco, Gerard E.; Sergi, Fabrizio; O’Malley, Marcia K.
    Background: Robotic rehabilitation of the upper limb following neurological injury has been supported through several large clinical studies for individuals with chronic stroke. The application of robotic rehabilitation to the treatment of other neurological injuries is less developed, despite indications that strategies successful for restoration of motor capability following stroke may benefit individuals with incomplete spinal cord injury (SCI) as well. Although recent studies suggest that robot-aided rehabilitation might be beneficial after incomplete SCI, it is still unclear what type of robot-aided intervention contributes to motor recovery. Methods: We developed a novel assist-as-needed (AAN) robotic controller to adjust challenge and robotic assistance continuously during rehabilitation therapy delivered via an upper extremity exoskeleton, the MAHI Exo-II, to train independent elbow and wrist joint movements. We further enrolled seventeen patients with incomplete spinal cord injury (AIS C and D levels) in a parallel-group balanced controlled trial to test the efficacy of the AAN controller, compared to a subject-triggered (ST) controller that does not adjust assistance or challenge levels continuously during therapy. The conducted study is a stage two, development-of-concept pilot study. Results: We validated the AAN controller in its capability of modulating assistance and challenge during therapy via analysis of longitudinal robotic metrics. For the selected primary outcome measure, the pre–post difference in ARAT score, no statistically significant change was measured in either group of subjects. Ancillary analysis of secondary outcome measures obtained via robotic testing indicates gradual improvement in movement quality during the therapy program in both groups, with the AAN controller affording greater increases in movement quality over the ST controller. Conclusion: The present study demonstrates feasibility of subject-adaptive robotic therapy after incomplete spinal cord injury, but does not demonstrate gains in arm function occurring as a result of the robot-assisted rehabilitation program, nor differential gains obtained as a result of the developed AAN controller. Further research is warranted to better quantify the recovery potential provided by AAN control strategies for robotic rehabilitation of the upper limb following incomplete SCI.
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    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.
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    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.
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    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.