Color Space Transformation-Based Smartphone Algorithm for Colorimetric Urinalysis

Abstract

Urine strips are widely applied for rapid analysis of various indexes of urine for clinical examinations. The tests mainly rely on the application of a urine analyzer, which suffers several drawbacks and cannot meet the requirements of point-of-care testing (POCT). The integration of a smartphone with a biosensor has recently attracted great attention. We herein propose a human vision-based smartphone algorithm for colorimetric analysis of various urine indexes. A CIEDE2000 formula in CIELab color space is applied for the evaluation of color difference, which may greatly improve the analytical performances of urine strips. The proposed algorithm also possesses merits such as good accuracy, quantitative analysis, and limited calculation task, which is suitable for the application with smartphone platform. Experimental results demonstrate that the proposed method shows excellent reliability compared with the urine analyzer and some other algorithms. In addition, human real samples are successfully analyzed with excellent accuracy. Therefore, this work provides a convenient colorimetric tool for POCT urine analysis.