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. 2017 Dec 15:6:2800111.
doi: 10.1109/JTEHM.2017.2765631. eCollection 2018.

Smartphone-Based Point-of-Care Urinalysis Under Variable Illumination

Moonsoo Ra  1 , Mannan Saeed Muhammad  2 , Chiawei Lim  1   3 , Sehui Han  1   4 , Chansung Jung  5 , Whoi-Yul Kim  6
Affiliations

Smartphone-Based Point-of-Care Urinalysis Under Variable Illumination

Moonsoo Ra et al. IEEE J Transl Eng Health Med. .

Abstract

Urine tests are performed by using an off-the-shelf reference sheet to compare the color of test strips. However, the tabular representation is difficult to use and more prone to visual errors, especially when the reference color-swatches to be compared are spatially apart. Thus, making it is difficult to distinguish between the subtle differences of shades on the reagent pads. This manuscript represents a new arrangement of reference arrays for urine test strips (urinalysis). Reference color swatches are grouped in a doughnut chart, surrounding each reagent pad on the strip. The urine test can be evaluated using naked eye by referring to the strip with no additional sheet necessary. Along with this new strip, an algorithm for smartphone based application is also proposed as an alternative to deliver diagnostic results. The proposed colorimetric detection method evaluates the captured image of the strip, under various color spaces and evaluates ten different tests for urine. Thus, the proposed system can deliver results on the spot using both naked eye and smartphone. The proposed scheme delivered accurate results under various environmental illumination conditions without any calibration requirements, exhibiting performances suitable for real-life applications and an ease for a common user.

Keywords: Smartphone; color-matching; colorimetric; diagnostics; optical sensor; point-of-care; urinalysis.

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Figures

FIGURE 1.
FIGURE 1.
Off-the-shelf diagnostic tools for strip-based urinalysis. (a) Urine test strips with multi-analyte sensors. (b) Reference colorimetric sheet where color swatches are arrayed in tabular form, (c) Conventional way of matching the color of reagent pads on the urine test strip.
FIGURE 2.
FIGURE 2.
Newly proposed urine test strip, Donut-shaped Nearness Urine Tester (DONUT).
FIGURE 3.
FIGURE 3.
Developed smart-phone application for Android software using the proposed method. (a) Loading new data. (b) Detecting the strip for urinalysis. (c) Displaying results.
FIGURE 4.
FIGURE 4.
Captured images under natural light conditions. (a) Conventional test strip. (b) Proposed test strip.
FIGURE 5.
FIGURE 5.
(a) Circular Hough Transform. (b) Results of segmentation.
FIGURE 6.
FIGURE 6.
Segmentation procedure in DONUT arrays. (a) Partitioning. (b) ROIs of each region.
FIGURE 7.
FIGURE 7.
Glucose Test 1 image (a) scanned image (b) smartphone image.
FIGURE 8.
FIGURE 8.
Matching factor for Glucose Test 1 for both conventional and the proposed method in RGB color space (a) for scanned image (b) for smartphone image.
FIGURE 9.
FIGURE 9.
Color flow for all colors of Glucose Test for both conventional and proposed strips in RGB color space (a) for scanned image (b) for smartphone image. (The color pattern in both the figures is different due to the illumination change.)
FIGURE 10.
FIGURE 10.
Results obtained with the conventional and new reference system. (a) Normal urine test sample. (b) Abnormal urine test sample. Standard deviations are plotted on top of each bar.
See this image and copyright information in PMC

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