Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Electrical Engineering Program
Description
This paper introduces a wireless reconfigurable “button-type” pressure sensor system, via machine learning, for gait analysis application. The pressure sensor system consists of an array of independent button-type pressure sensing units interfaced with a remote computer. The pressure sensing unit contains pressure-sensitive resistors, readout electronics, and a wireless Bluetooth module, which are assembled within footprint of 40 × 25 × 6mm3. The small-footprint, low-profile sensors are populated onto a shoe insole, like buttons, to collect temporal pressure data. The pressure sensing unit measures pressures up to 2,000 kPa while maintaining an error under 10%. The reconfigurable pressure sensor array reduces the total power consumption of the system by 50%, allowing extended period of operation, up to 82.5 hrs. A robust machine learning program identifies the optimal pressure sensing units in any given configuration at an accuracy of up to 98%.
ContributorsBooth, Jayden Charles (Author) / Chae, Junseok (Thesis director) / Chen, Ang (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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 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
Description
The team has designed and built a golf swing analyzer that informs the user of his mistakes while putting with a golf club. The team also interfaced a Linux program with the analyzer that allows the user to review the flaws in his golf swing. In addition, the application is more personalized than existing devices and tailored to the individual based on his level of experience. The analyzer consists of an accelerometer, gyroscope, magnetometer, vibration motor, and microcontroller that are connected on a board that attaches to the top of the shaft of a golf club, fitting inside a 3D printed case. The team has assembled all of the necessary hardware, and is able to successfully display critical parameters of a golf putt, as well as send instant feedback to the user. The final budget for this project was $378.24
ContributorsKaur, Hansneet (Co-author) / Cox, Jeremy (Co-author) / Farnsworth, Chad (Co-author) / Zorob, Nabil (Co-author) / Chae, Junseok (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12