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Robotic rehabilitation for upper limb post-stroke recovery is a developing technology. However, there are major issues in the implementation of this type of rehabilitation, issues which decrease efficacy. Two of the major solutions currently being explored to the upper limb post-stroke rehabilitation problem are the use of socially assistive rehabilitative

Robotic rehabilitation for upper limb post-stroke recovery is a developing technology. However, there are major issues in the implementation of this type of rehabilitation, issues which decrease efficacy. Two of the major solutions currently being explored to the upper limb post-stroke rehabilitation problem are the use of socially assistive rehabilitative robots, robots which directly interact with patients, and the use of exoskeleton-based systems of rehabilitation. While there is great promise in both of these techniques, they currently lack sufficient efficacy to objectively justify their costs. The overall efficacy to both of these techniques is about the same as conventional therapy, yet each has higher overhead costs that conventional therapy does. However there are associated long-term cost savings in each case, meaning that the actual current viability of either of these techniques is somewhat nebulous. In both cases, the problems which decrease technique viability are largely related to joint action, the interaction between robot and human in completing specific tasks, and issues in robot adaptability that make joint action difficult. As such, the largest part of current research into rehabilitative robotics aims to make robots behave in more "human-like" manners or to bypass the joint action problem entirely.
ContributorsRamakrishna, Vijay Kambhampati (Author) / Helms Tillery, Stephen (Thesis director) / Buneo, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / W. P. Carey School of Business (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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Description
Microwave tomography (MWT) differs from the current forms of biomedical imaging modalities by measuring the dielectric properties in different tissues in order to create an image of the object under evaluation. This technology could be harnessed for the evaluation of a stroke because the areas of the brain that are

Microwave tomography (MWT) differs from the current forms of biomedical imaging modalities by measuring the dielectric properties in different tissues in order to create an image of the object under evaluation. This technology could be harnessed for the evaluation of a stroke because the areas of the brain that are not being provided oxygen will have a reduced concentration of blood, leading to a reduced relative permittivity (also referred to as dielectric constant). Strokes themselves require accurate diagnosis for proper treatment to be administered. Microwave tomography offers advantages of stroke diagnosis over imaging methods such as magnetic resonance imaging (MRI) and computerized tomography (CT). Like MRIs, microwave tomography passes only non-ionizing radiation through the patient, allowing for multiple safe scans. Because MWT requires only an array of antennas sending a non-ionizing electromagnetic field, which is on the level of the fields sent in cell phones, a patient undergoing a stroke could be diagnosed inside an ambulance with multiple MWT scans, greatly reducing the time before treatment. The challenge for this thesis is to correctly solve an ill-posed problem presented in a microwave tomography system and output an image of the object's electrical properties. The system itself is an inverse problem because the object to be imaged and its properties are unknown. Rather, the incident field and resulting scattered field due to interaction with the object of interest are known. To achieve a unique solution for this problem, a software implementation of a common microwave inversion method known as Born's Iterative Method is realized through MATLAB.
ContributorsNam, Suhyun (Author) / Chae, Junseok (Thesis director) / Liu, Shiyi (Committee member) / W. P. Carey School of Business (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12