Browsing by Author "Kann, Claudia K."

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    Assessing Wrist Movement With Robotic Devices
    (IEEE, 2018) Rose, Chad G.; Pezent, Evan; Kann, Claudia K.; Deshpande, Ashish D.; O'Malley, Marcia K.
    Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional clinical assessments through precise, repeatable measurements of joint angles and movement quality. These measures assume that exoskeletons are making accurate joint measurements with a negligible effect on movement. For the coupled and coordinated joints of the wrist and hand, the validity of these two assumptions cannot be established by characterizing the device in isolation. To examine these assumptions, we conducted three user-in-the-loop experiments with able-bodied participants. First, we compared robotic measurements to an accepted modality to determine the validity of joint- and trajectory-level measurements. Then, we compared those movements to movements without the device to investigate the effects of device dynamic properties on wrist movement characteristics. Last, we investigated the effect of the device on coordination with a redundant, coordinated pointing task with the wrist and hand. For all experiments, smoothness characteristics were preserved in the robotic kinematic measurement and only marginally impacted by robot dynamics, validating the exoskeletons for use as assessment devices. Stemming from these results, we propose design guidelines for exoskeletal assessment devices.
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    Estimating anatomical wrist joint motion with a robotic exoskeleton
    (IEEE, 2017) Rose, Chad G.; Kann, Claudia K.; Deshpande, Ashish D.; O’Malley, Marcia K.
    Robotic exoskeletons can provide the high intensity, long duration targeted therapeutic interventions required for regaining motor function lost as a result of neurological injury. Quantitative measurements by exoskeletons have been proposed as measures of rehabilitative outcomes. Exoskeletons, in contrast to end effector designs, have the potential to provide a direct mapping between human and robot joints. This mapping rests on the assumption that anatomical axes and robot axes are aligned well, and that movement within the exoskeleton is negligible. These assumptions hold well for simple one degree-of-freedom joints, but may not be valid for multi-articular joints with unique musculoskeletal properties such as the wrist. This paper presents an experiment comparing robot joint kinematic measurements from an exoskeleton to anatomical joint angles measured with a motion capture system. Joint-space position measurements and task-space smoothness metrics were compared between the two measurement modalities. The experimental results quantify the error between joint-level position measurements, and show that exoskeleton kinematic measurements preserve smoothness characteristics found in anatomical measures of wrist movements.