Optical Characterization of Calcium Oxalate Hydrate in Urine

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Kidney stones is a common ailment worldwide, affecting adults, children and even animals. Calcium oxalate is the main component of the urinary tract stones in individuals, mostly due to the intake of high-oxalate foods. This paper is an approach towards the optical characterization of calcium oxalate hydrate in urine. This study demonstrates a label-free, accurate and sensitive method for detecting the presence of oxalate levels in urine. This can be done by measuring the changes in the optical properties of urine with increasing concentrations of calcium oxalate hydrate (CaC2O4.xH2O) powder. The current method could detect CaC2O4.xH2O at a concentration as low as 10 μg/mL of urine, making this method suitable for detecting changes that cannot be recognized by conventional methods. The ability to detect very small amount of stones makes it an attractive tool for detecting oxalate concentration. It can be used as cautionary measure for the individuals who take high amounts of oxalates and are prone to the kidney stones.

Original languageEnglish
Title of host publication2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679661
DOIs
Publication statusPublished - Jul 2 2018
Event5th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018 - Bangkok, Thailand
Duration: Nov 22 2018Nov 23 2018

Publication series

Name2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018

Conference

Conference5th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018
Country/TerritoryThailand
CityBangkok
Period11/22/1811/23/18

Keywords

  • Kidney stones
  • NIR Spectrophotometry
  • Urinalysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Education

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