IoT enabled microfluidics-based biochemistry analyzer based on colorimetric detection techniques

Microfluidics is an ideal technique to simplify whole blood processing including classical biochemical analysis. In this work, a microfluidics-based biochemistry analyzer has been developed. It is based on the colorimetric imaging acquisition and analyzing system, utilizing a machine-learning algorithm to estimate the concentration of targeted biochemistry blood parameters. A microfluidics-based device was fabricated using Polydimethylsiloxane to hold the sample at the time of analysis using the soft lithography technique. The integration of microfluidics and machine learning algorithms helped in minimizing the incubation time by around 80%, which leads to reducing the per-test reaction time and speedup the complete analysis process. The Internet of things has been incorporated so that the test result can be accessed online in real-time for remote counseling. The developed platform is tested to estimate the concentration of Triglyceride, Calcium, and Glucose in the blood serum has been estimated with a limit of detection of 0.79, 0.24, 1.71 mg/dL and linear detection range 1–1000, 1–400 and 2–20 mg/dL respectively. The developed platform offers the advantages of portability, lower cost per test, less reagent and sample consumption, shorter time-to-result, reduced hardware complexity due to programming flexibility, and less analytical footprint.