Design and Modelling of a Magnetic Fluid Based Artificial Muscle for Gait Rehabilitation

Scone, Thomas H (2023). Design and Modelling of a Magnetic Fluid Based Artificial Muscle for Gait Rehabilitation. University of Birmingham. Ph.D.

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Robotic gait rehabilitation systems have seen a plateau in functional gait rehabilitation outcomes for hemiparetic stroke survivors over the past 5 years, particularly when using improvements in walking speed as a key metric. Research continues into various types of robotic systems, and many have been seen to increase rates of independent walking. Why then have improvements in users’ walking speed remained sluggish? It is suggested that the issue may lie either in the design of the robotic systems themselves or in approach these systems take to providing training. A such a ground up approach is taken for this research into improving robotic gait rehabilitation techniques. This first required a closer look at how
hemiparetic gait patterns vary with walking speed though this in turn necessitated consideration of the targeting effect. Caused by the presence of a distinctly marked shape along their path, this effect was found to have no significant impact on the kinematic parameters of hemiparetic stroke survivors. This allowed gait analysis into the kinematic gait patterns of stroke survivors to be carried out and relationships between said pattern and the participants walking speed to be obtained. It was found that there existed compensatory gait techniques that related to walking speed and it was suggested that these could be encouraged as beneficial traits to improve functional rehabilitation outcomes. This still left the consideration of the robotic system itself though. Soft robotics and smart materials had been suggested as a potential avenue for designing improved robotic systems that would allow for high user engagement and autonomy while removing the tethering common in current designs. A magnetic fluid muscle design and FEA model was proposed and validated. The design was iterated on using the FEA model to improve its functionality and gather details about its potential for use in gait rehabilitation.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Licence: Creative Commons: Attribution-Noncommercial 4.0
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Engineering, Department of Mechanical Engineering
Funders: Engineering and Physical Sciences Research Council
Subjects: Q Science > QM Human anatomy
T Technology > TJ Mechanical engineering and machinery


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