Instrument-free single-step direct estimation of the plasma glucose level from one drop of blood using smartphone-interfaced analytics on a paper strip
Sujay Kumar Biswas, Subhamoy Chatterjee, Sampad Laha, Victor Pakira, Nirmal K. Som, Satadal Saha, Suman Chakraborty
Abstract
a completely-automated mobile-app-based image analytics interface developed using dynamic machine learning, obviating manual interpretation. The tests were demonstrated to be of high efficacy, even when executed by minimally trained frontline personnel having no special skill of drawing precise volume of blood, on deployment at under-resourced community centres having no in-built or accessible healthcare infrastructure. Clinical validation using 220 numbers of human blood samples in a double-blinded manner evidenced sensitivity and specificity of 98.11% and 96.7%, respectively, as compared to the results obtained from a laboratory-benchmarked biochemistry analyser, establishing its efficacy for public health and community disease management in resource-limited settings without any quality compromise of the test outcome.