Biochemical semi-automated acoustics by Dipstick image processing based on arduino

Keywords: Automation, Arduino, Urinalysis

Abstract

Although many devices are available to read urinalysis reactive strips, potential failure, based on human interpretation, persists in routine tasks. Current study develops and evaluates the performance of an Arduino-based device for the semi-automated reading of reactive strip parameters. The glucose parameter of a commercial reactive strip model was analyzed by the system, which predicts analyte concentration by submitting the color observed in the strip to a regression model, adjusted to a database of color patterns. The system was assessed by reading of 80 strips with 16 samples of random glucose concentrations. The lowest coefficient of variation after five replicated readings was 4.5% and the highest was 16.6% (MSE=68.7 mg/dL; r=0.979). The device featured satisfactory results plus low costs. To make it useful in the laboratory routine, further experiments with other parameters and other classes of urinalysis reactive strips would be necessary.

Author Biographies

Ronneery Moura Teles, Universidade Paulista
Biomedical graduate from Universidade Paulista, Campus Goiânia-Flamboyant, Goiânia (GO), Brazil.
Ronneesley Moura Teles , Instituto Federal Goiano
Permanent professor at the Federal Institute of Goiás, Campus Ceres, Ceres (GO), Brazil.
Antonio Márcio Teodoro Cordeiro Silva , Pontifícia Universidade Católica de Goiás
Permanent professor at the School of Medical, Biomedical and Pharmaceutical Sciences at the Pontifical Catholic University of Goiás, Goiânia (GO), Brazil.
Denise da Silva Pinheiro, Universidade Federal de Goiás
Biomedical in the Institute of Biological Sciences at the Federal University of Goiás, Goiânia (GO), Brazil.
Lee Chen-Chen, Universidade Federal de Goiás
Permanent professor at the Institute of Biological Sciences, Federal University of Goiás, Goiânia (GO), Brazil
Xisto Sena Passos , Universidade Paulista
Professor at the Institute of Health Sciences at Universidade Paulista, Campus Goiânia-Flamboyant, Goiânia (GO), Brazil.
Cristiene Costa Carneiro, Universidade Paulista
Professor at the Institute of Health Sciences at Universidade Paulista, Campus Goiânia-Flamboyant, Goiânia (GO), Brazil.

References

Ercan M, Oǧuz EF, Kaya O, Yilmaz FM. Evaluation of H-800/FUS-100 automatic urine analyzer performance. Turkish J Biochem. 2018;43(1):89–92.

Khan LB, Read HM, Ritchie SR, Proft T. Artificial Urine for Teaching Urinalysis Concepts and Diagnosis of Urinary Tract Infection in the Medical Microbiology Laboratory †. J Microbiol Biol Educ. 2017;18(2):1–6.

Ince FD, Ellidağ HY, Koseoğlu M, Şimşek N, Yalçin H, Zengin MO. The comparison of automated urine analyzers with manual microscopic examination for urinalysis automated urine analyzers and manual urinalysis. Pract Lab Med. 2016;5:14–20.

Lee W, Kim Y, Chang S, Lee AJ, Jeon CH. The influence of vitamin C on the urine dipstick tests in the clinical specimens: a multicenter study. J Clin Lab Anal. 2017;31(5):1–6.

Dolscheid-Pommerich RC, Kiarmann-Schuiz U, Conrad R, Stoffel-Wagner B, Zur B. Evaluation of the appropriate time period between sampling and analyzing for automated urinalysis. Biochem Medica. 2016;26(1):82–9.

Eriksen SV, Sykepleier A Geriatrisk, Østfold S. Can we trust urine dipsticks? Forskning. 2016;2–15.

Ko K, Kwon MJ, Ryu S, Woo HY, Park H. Performance Evaluation of Three URISCAN Devices for Routine Urinalysis. J Clin Lab Anal. 2016;30(5):424–30.

Khejonnit V, Pratumvinit B, Reesukumal K, Meepanya S, Pattanavin C, Wongkrajang P. Optimal criteria for microscopic review of urinalysis following use of automated urine analyzer. Clin Chim Acta. 2015;439:1–4.

Walta AM, Keltanen T, Lindroos K, Sajantila A. The usefulness of point-of-care (POC) tests in screening elevated glucose and ketone body levels postmortem. Forensic Sci Int. 2016;266:299–303.

Van Delft S, Goedhart A, Spigt M, Van Pinxteren B, De Wit N, Hopstaken R. Prospective, observational study comparing automated and visual point-of-care urinalysis in general practice. BMJ Open. 2016;6(8):1–8.

Delanghe JR, Speeckaert MM. Preanalytics in urinalysis. Clin Biochem. 2016;49(18):1346–50.

Lim S, Yu HJ, Lee S, Park H, Kwon MJ, Woo HY. Evaluation of the URISCAN 2 ACR Strip to estimate the urine albumin/creatinine ratios. J Clin Lab Anal. 2018;32(3):6–11.

Asano Y, Fairchild MD, Blondé L. Individual colorimetric observer model. PLoS One. 2016;11(2):1–19.

Mittal S. A survey of techniques for improving energy efficiency in embedded computing systems. Int J Comput Aided Eng Technol. 2014;6(4):440–59.

Konnaiyan KR, Cheemalapati S, Gubanov M, Pyayt A. MHealth Dipstick Analyzer for Monitoring of Pregnancy Complications. IEEE Sens J. 2017;17(22):7311–6.

Jalal Uddin M, Jin GJ, Shim JS. Paper-Plastic Hybrid Microfluidic Device for Smartphone-Based Colorimetric Analysis of Urine. Anal Chem. 2017;89:13160–6.

Valenzuela I, Amado T, Orillo JW. Urine test strip analysis using image processing for mobile application. J Teknol. 2016;78(5–7):93–9.

Martínez-Santos JC, Acevedo-Patino O, Contreras-Ortiz SH. Influence of Arduino on the Development of Advanced Microcontrollers Courses. Rev Iberoam Tecnol del Aprendiz. 2017;12(4):208–17.

Luo MR, Cui G, Georgoula M. Colour difference evaluation for white light sources. Light Res Technol. 2015;47(3):360–9.

Mukaka MM. Statistics Corner: A guide to appropriate use of Correlation coefficient in medical research. Malawi Med J. 2012;24(3):69–71.

Bekhof J, Kollen BJ, Van De Leur S, Kok JH, Van Straaten IHLM. Reliability of reagent strips for semi-quantitative measurement of glucosuria in a neonatal intensive care setting. Pediatr Neonatol. 2014;55(6):444–8.

Chien TI, Lu JY, Kao JT, Lee TF, Ho SY, Chang CY, et al. Comparison of three automated urinalysis systems-Bayer Clinitek Atlas, Roche Urisys 2400 and Arkray Aution Max for testing urine chemistry and detection of bacteriuria. Clin Chim Acta. 2007;377(1–2):98–102.

Published
2021-04-30
Section
Artigos Originais