Document Type
Honors Thesis
Abstract
Bacterial infections are one of the biggest issues facing hospitals today; they prolong hospital stays, worsen patient outcomes, and decrease the quality of life for these patients. In the food and water industry, bacteria are causes for food recalls and non-potable water. The objects of this research were to develop a biosensor that could detect E. coli and S. aureus bacteria simultaneously using the lateral flow assay platform and to generate a software program that could accurately read results of the LFA. The biosensor was not built due to antibody shortages from the COVID-19 pandemic. The software program was developed using MATLAB. Twenty images of LFA test results were subjected to three conditions: the standard condition, the decreased image intensity condition, and the decreased image contrast condition. The program successfully identified the results of the LFA test for all twenty images under all three conditions. The minimal pixel depth required for accurate results was also investigated, and as a result, it was determined to be 8-bits.
Publication Date
5-1-2022
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Conley II, Reginald, "Dual Automated Colorimetric Detection of Bacteria Using A Lateral Flow Assay" (2022). 2022 Spring Honors Capstone Projects. 55.
https://mavmatrix.uta.edu/honors_spring2022/55