Designing a Diabetes Mellitus Detection Tool Using the Backpropagation Method

Abstract

Technological advances in the field of medical electronics are developing very rapidly; one of the positive effects of advances in electronic technology in the world of health is the detection of Diabetes Mellitus (DM) with urine odor which based on microcontrollers with Backpropagation artificial neural network methods. Diabetes Mellitus is a chronic disease characterized by high levels of sugar (Glucose), and is caused by the inability of pancreas to produce insulin. The detection of diabetes mellitus in this study used gas sensors of TGS 2602, TGS 2610 and TGS 813. Results of the study showed several sensor values; 120-290 for TGS 2610, 120-290 for TGS 813, and 100-170 for TGS 2610. The undertaken artificial neural network method was able to identify two urine samples, of which each sample was tested and conducted a training test with success rate results of 75%.