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Measurement of Specific Gravity, Urobilinogen, Blood, Protein and pH Level of Urine Samples Using Raspberry Pi based Portable Urine Test Strip Analyzer

Published: 15 September 2020 Publication History

Abstract

Urinalysis has been a helpful tool in detecting some common diseases. It has been used to diagnose conditions such as urinary tract infections, kidney disorders, liver problems, and other metabolic conditions. Regular urinalysis may be done to detect early signs of diseases and prevent it, but it is also time consuming and costly. Urine has several components and some of the parameters can be examined through the use of a urine test strip analysis. This paper presents a portable raspberry-pi based system that is designed to analyze the key parameters of urine namely, specific gravity, urobilinogen, blood, protein, and pH level. This study is focused in determining the key parameters of urine samples aforementioned which are essential in diagnosing early signs of disorders. Image processing was used in order to properly identify the positioning of each pad in the strip and to obtain the color change evaluated in terms of HSV color space analysis. Statistical analysis was performed in order to compare the values measured by the urine test strip analyzer to the actual laboratory urinalysis test. Using T-test, the results show that there is no significant difference between the values measured by the urine test strip analyzer and the actual laboratory urinalysis.

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Susan King Strasinger, DA, Marjorie Schaub Di Lorenzo, BS. "Urinalysis and Body Fluids", 6th edition
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Bilirubin in Urine. National Institute of Health. U.S. National Library of Medicine. Retrieved October 26, 2016 from http://www.nlm.nih.gov/medlineplus/ency/article/003595.htm
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J.A. Simerville, W.C. Maxted, and J.J. Pahira (2005) "Urinalysis: a Comprehensive Review," American Family Physician, vol. 71(6), pp. 1153--1158
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Compendium of Urinalysis: Urine Test Strips and Microscopy. Roche. Retrieved June 3, 2015 from http://www.roche-diagnostics.ch/content/dam/corporate/roche-dia_ch/documents/broschueren/professional_diagnostics/urindiagnostik/12254620001_EN_EA_Compendium-of-urinanalysis_Brosch%C3%BCre_EN.pdf
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Cited By

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  • (2023)Chemiluminescence Immunoassay Method of Urinary Liver Fatty-acid-binding Protein as a Promising Candidate for Kidney DiseaseJournal of Fluorescence10.1007/s10895-022-03120-z33:3(1191-1200)Online publication date: 11-Jan-2023
  • (2022)Predictive System Implementation to Improve the Accuracy of Urine Self-Diagnosis with Smartphones: Application of a Confusion Matrix-Based Learning Model through RGB Semiquantitative AnalysisSensors10.3390/s2214544522:14(5445)Online publication date: 21-Jul-2022

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  1. Measurement of Specific Gravity, Urobilinogen, Blood, Protein and pH Level of Urine Samples Using Raspberry Pi based Portable Urine Test Strip Analyzer

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    ICBET '20: Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology
    September 2020
    350 pages
    ISBN:9781450377249
    DOI:10.1145/3397391
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 15 September 2020

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    Author Tags

    1. Image processing
    2. Raspberry-pi
    3. T-test
    4. Urinalysis

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    Cited By

    View all
    • (2023)Chemiluminescence Immunoassay Method of Urinary Liver Fatty-acid-binding Protein as a Promising Candidate for Kidney DiseaseJournal of Fluorescence10.1007/s10895-022-03120-z33:3(1191-1200)Online publication date: 11-Jan-2023
    • (2022)Predictive System Implementation to Improve the Accuracy of Urine Self-Diagnosis with Smartphones: Application of a Confusion Matrix-Based Learning Model through RGB Semiquantitative AnalysisSensors10.3390/s2214544522:14(5445)Online publication date: 21-Jul-2022

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