Browsing by Subject "Rehabilitation robotics"
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Item Delineating abnormal coordination patterns in post-stroke gait : a multidisciplinary approach(2019-01-23) Akbas, Tunc; Sulzer, James S.; Neptune, Richard R.; Deshpande, Ashish; Jones, Theresa; Djurdjanovic, DraganStroke is the largest cause of long-term disability in U.S. where majority of the survivors experience impairments such as muscle weakness, spasticity and abnormal coordination. Stiff-Knee gait (SKG) is an incessant disability defined by the reduced knee flexion during swing. The abnormal neuromuscular mechanisms governing the interactions between impairments during SKG is still not clear. This work attempts to reveal the causal relationship between the specific influences of different impairments on post-stroke gait. Specifically, it delineates the underlying neuromuscular mechanisms behind observed increased hip abduction in SKG. The results indicate that hip abduction is part of an abnormal coordination pattern, instead of a presumed compensation for reduced knee flexion. This result is supported by previous work observing coupled knee flexion and hip abduction motions during SKG following pre-swing knee flexion torque perturbations. I hypothesized the underlying mechanism behind excessive hip abduction is due to an involuntary mechanism between quadriceps and abductor muscles which is initiated by quadriceps hyperreflexia. The results obtained from neuromusculoskeletal modeling and simulation suggest an involuntary coupled response between estimated rectus femoris (RF) and gluteus medius (GMed) activations following simulated peak RF fiber stretch velocity, suggesting an abnormal cross-planar reflex coupling initiated by excessive RF stretch reflex response. We have elicited RF reflex responses in SKG to identify the association between RF hyperreflexia and severity of the SKG excluding the influence of increased voluntary RF activity. Our results indicate a strong negative correlation between RF H-reflex response and reduced peak knee flexion angle in SKG, revealing the distinctive influence of spasticity in SKG. This novel framework delineates the abnormal neuromuscular mechanisms behind the excessive hip abduction in post-stroke gait using biomechanics, neuromusculoskeletal simulations and neurophysiological perturbations. The results obtained from this dissertation could improve lower-limb interventions for gait rehabilitation following stroke by introducing quantified measures of abnormal coordination in SKG and improve the development of subject-specific assistive technology targeting impairments to restore healthy gait.Item Development of a paradigm for systematic evaluation of robot dynamic transparency(2022-08-12) Lazar, Michael Lawrence; Deshpande, Ashish D.; Longoria, Raul GRobots designed for physically interacting with humans must be compliant and reactive to ensure safety and effective performance. In the field of rehabilitation robotics, dynamic transparency, which is the measure of the parasitic interaction force a robot imparts on its end user, is a key metric for the quality of assessment and therapy that can be accomplished with the robot. The improvement of dynamic transparency is an area of ongoing research. In this work, a novel paradigm for the systematic evaluation of dynamic transparency is developed, implemented, and tested. This new paradigm builds upon previous works by using a robot with multiple degrees of freedom to reliably and fully assess a rehabilitation robot's transparency. Optimized B-splines are used to evenly excite the full range of the rehabilitation robot's dynamics, and interaction measurements are used to calculate a transparency metric. A case study is presented that employs the paradigm to automate the control gain-tuning process and minimize the interaction forces imparted on an end-user without increasing vibrations. The method was able to discern differences in average interaction forces over a trajectory as low as 0.2 N caused by changes in controller gains and use those differences reduce the average interaction force by 35% from hand-tuned starting gains. Through the use of this method, the dynamic transparency for a robot can be systematically evaluated and tuned to improve the quality of physical human-robot interaction.