Lab-in-a-Cup (LiC): An autonomous fluidic device for daily urinalysis using smartphone

Since urine can be collected noninvasively, a wide range of biomarkers found in urine makes urinalysis well suited for continuous routine health screening. Although there has been amazing progress in automated urine analyzers, they are laboratory-centered and still suffer from labor-involved sample processing and analysis being infeasible for routine healthcare. To facilitate routine healthcare, this work presents a cost-effectively implemented lab-in-a-Cup (LiC) hybrid urinalyzer developed using a disposable plastic cup in association with conventional paper-based urine sensors. Since the sensor pad is precisely fixed with the bottom of the cup, the small gap between the sensor pad and cup surface leads to the limited diffusion of urine which results in the stable, reproducible, repeatable data and sample volume-irrelevant measurement. To characterize the urine sample in the cup, a smartphone application with an image recognition algorithm has been developed and applied that automatizes the entire analysis procedures enabling it for routine healthcare without relying on the manual color scheme. The device was successfully applied for investigating a number of urinary biomarkers such as glucose, pH, protein, and red blood cell (RBC) to a wider concentration covering their clinical ranges. While quantified, the proposed analyzer was found to significantly improve the reaction time and sample volume-dependent irregularities enhancing the colorimetric assessment of urine sensors as a major concern for biological samples. As a result, the user-friendly LiC device may suitably be applied as a near-patient urinalyzer.

Automated summary

Urine analysis is a noninvasive method suitable for routine health screening due to the wide range of biomarkers found in urine. A lab-in-a-Cup (LiC) hybrid urinalyzer has been developed using a disposable plastic cup and conventional paper-based urine sensors, enabling stable and reproducible measurements. A smartphone application with image recognition algorithm automates the analysis procedures, eliminating the reliance on manual color scheme. The LiC device can be applied as a near-patient urinalyzer, significantly improving reaction time and sample volume-dependent irregularities for colorimetric assessment of urine sensors.