A portable and low cost system to blood glucose, cholesterol and urea identification

Abstract

Over the last century there has been a considerable increase in human longevity and this made a large number of people to reach a critical age for development of several diseases. As a result of this increase in life expectancy health issues related, some examples are hypercholesterolemia, hyperglycemia and increased levels of blood urea. This paper presents a portable and low cost system using Artificial Neural Networks to blood metabolites identification. The system developed is based in amperometric biosensors and is able to perform the identification of glucose, cholesterol and urea concentrations in the blood. The main goals of this system is: the identification of three types of blood metabolites with their concentrations, the low cost of the entire system and the reuse capability of the biosensor.