FPGA-based urinalysis for urinary tract infection detection using principal component analysis

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...

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Main Authors: Cualquiera, James Kenneth P., Loriaga, Karl Joszep A., Roxas, Paulo Gabriel N., Ybanez, Kristine D. V.
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Language:English
Published: Animo Repository 2016
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/8595
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-92402021-08-24T06:50:48Z FPGA-based urinalysis for urinary tract infection detection using principal component analysis Cualquiera, James Kenneth P. Loriaga, Karl Joszep A. Roxas, Paulo Gabriel N. Ybanez, Kristine D. V. 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%. 2016-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/8595 Bachelor's Theses English Animo Repository Urine--Analysis Urinary tract infections Field programmable gate arrays Principal components analysis
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Urine--Analysis
Urinary tract infections
Field programmable gate arrays
Principal components analysis
spellingShingle Urine--Analysis
Urinary tract infections
Field programmable gate arrays
Principal components analysis
Cualquiera, James Kenneth P.
Loriaga, Karl Joszep A.
Roxas, Paulo Gabriel N.
Ybanez, Kristine D. V.
FPGA-based urinalysis for urinary tract infection detection using principal component analysis
description 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%.
format text
author Cualquiera, James Kenneth P.
Loriaga, Karl Joszep A.
Roxas, Paulo Gabriel N.
Ybanez, Kristine D. V.
author_facet Cualquiera, James Kenneth P.
Loriaga, Karl Joszep A.
Roxas, Paulo Gabriel N.
Ybanez, Kristine D. V.
author_sort Cualquiera, James Kenneth P.
title FPGA-based urinalysis for urinary tract infection detection using principal component analysis
title_short FPGA-based urinalysis for urinary tract infection detection using principal component analysis
title_full FPGA-based urinalysis for urinary tract infection detection using principal component analysis
title_fullStr FPGA-based urinalysis for urinary tract infection detection using principal component analysis
title_full_unstemmed FPGA-based urinalysis for urinary tract infection detection using principal component analysis
title_sort fpga-based urinalysis for urinary tract infection detection using principal component analysis
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/etd_bachelors/8595
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