Point-of-Care Pathogen Testing Using Photonic Crystals and Machine Vision for Diagnosis of Urinary Tract Infections

Abstract

Urinary tract infections (UTIs) caused by bacterial invasion can lead to life-threatening complications, posing a significant health threat to more than 150 million people worldwide. As a result, there is need for accurate and rapid diagnosis of UTIs to enable more effective treatment. Described here is an intelligent diagnostic system constructed for bacterial detection using an immunobiosensor, signal-amplification biochip, and image processing algorithm based on machine vision. This prototype can quickly detect bacteria by collection of enhanced luminescence enabled by the photonic crystals integrated into the biochip. By use of a machine vision algorithm, the very small luminescence signals are analyzed to provide a low detection limit and wide dynamic range. This sensor system can offer an affordable, accessible, and user-friendly digital diagnostic solution, possibly suitable for wearable technology, that could improve treatment of this challenging disease.