FPGA-based urinalysis for urinary tract infection detection using principal component analysis
Date of Publication
2016
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics and Communications Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Cesar A. Llorente
Defense Panel Chair
Maria Antonette C. Roque
Defense Panel Member
Roderick Yao Yap
Argel A. Bandala
Abstract/Summary
Urinalysis is considered to be a common test performed in laboratory in order to diagnose Urinary Tract Infection (UTI). It undergoes three stages, which include macroscopic, dipstick, and microscopic analysis. This paper discusses about a new way of performing urinalysis for UTI detection through a Field Programmable Gate Array (FPGA) and with the use of five different sensors that measure five different components specifically sodium, nitrate, potassium, and pH level of a urine sample. The designed system has an accuracy of 94.13% for the urinalysis. To be able to detect the presence of UTI in urines, an outlier detection method, Principal Component Analysis (PCA), was used. PCA is a tool used in reducing multidimensional data to lesser dimensions while keeping all the information. The selection of the parameters to be measured is important in order to increase the accuracy of detection. Because of this, the group compared the accuracy of UTI detection when the pH sensor was used and if it was removed. The accuracy of the designed system for UTI detection increased to 83.33% when pH sensor is removed. This paper also discusses about the implementation of PCA on an FPGA. The computed principal component by the FPGA was compared to be computed principal components by MATLAB and has an accuracy of 99.917%.
Abstract Format
html
Language
English
Format
Accession Number
TU21504
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
366 leaves : colored illustrations ; 28 cm.
Keywords
Urine--Analysis; Urinary tract infections; Field programmable gate arrays; Principal components analysis
Recommended Citation
Cualquiera, J. P., Loriaga, K. A., Roxas, P. N., & Ybanez, K. (2016). FPGA-based urinalysis for urinary tract infection detection using principal component analysis. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/8595