The Effects of Real-Time Biofeedback on Gait Propulsive Forces and Gait Biomechanics Restricted; Files & ToC

Liu, Justin (Spring 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/cz30ps676?locale=en
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Abstract

Hemiparesis following stroke results in debilitating motor impairments including decreased walking ability. Reduced paretic leg propulsion, measured as the anterior component of the ground reaction force (AGRF), is a common gait deficit that negatively impacts walking ability in post-stroke individuals. Gait interventions that target AGRF often result in improvements to walking speed and function. Real-time biofeedback is a promising post-stroke gait rehabilitation strategy that can provide real-time physiological information to users during training. Our previous study in a post-stroke population show that real-time AGRF biofeedback training results in significant improvements in paretic leg propulsion without inducing compensatory changes in the non-paretic leg. 

However, several questions regarding the use of real-time biofeedback remain. To date, no studies have compared AGRF biofeedback training with other gait interventions that target propulsion. Moreover, other biomechanical variables that may contribute to improved walking function have yet to be delivered via real-time biofeedback. The experiments presented in this thesis explore these gaps in research in an able-bodied population. In our first experiment, we compare the walking outcomes of able-bodied individuals following exposure to verbal feedback and real-time biofeedback. Our results demonstrate the efficacy and engagement of real-time biofeedback in improving gait propulsive forces, strengthening its promise as a viable post-stroke gait intervention. In our second experiment, we investigate, for the first time, the effects of trailing limb angle (TLA) biofeedback on modulating gait propulsive forces and biomechanical variables. Our results provide a rationale for further investigation into the use of real-time TLA biofeedback in a post-stroke population.

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