Cell phone based colorimetric analysis for point-of-care settings
Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue–saturation–value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results.