🤖 AI Summary
This work addresses the lack of low-cost, portable biochemical concentration detection devices in resource-constrained settings by proposing a smartphone camera–based imaging system. By integrating custom optical attachments with tailored image processing algorithms, the system establishes a quantitative mapping model between sample colorimetric features and target analyte concentrations, effectively transforming a standard smartphone into a portable analytical platform. The method achieves detection accuracy comparable to that of commercial instruments across diverse samples—including fluorescein, RNA Mango aptamer complexes, homogenized milk, and yeast—while substantially reducing costs and enhancing the feasibility of on-site diagnostics.
📝 Abstract
This paper presents a smartphone-based imaging system capable of quantifying the concentration of an assortment of biological/chemical assay samples. The main objective is to construct an image database which characterizes the relationship between color information and concentrations of the biological/chemical assay sample. For this aim, a designated optical setup combined with image processing and data analyzing techniques was implemented. A series of experiments conducted on selected assays, including fluorescein, RNA Mango, homogenized milk and yeast have demonstrated that the proposed system estimates the concentration of fluorescent materials and colloidal mixtures comparable to currently used commercial and laboratory instruments. Furthermore, by utilizing the camera and computational power of smartphones, eventual development can be directed toward extremely compact, inexpensive and portable analysis and diagnostic systems which will allow experiments and tests to be conducted in remote or impoverished areas.