Mathematical modelling and simulation analysis of a modified Butterworth van Dyke circuit model for non-invasive diabetes detection

In recent times, there is an intense need for a reliable non-invasive diabetes prediction system. Some of the researches in this field suggest that acetone gas in breath has a good correlation to blood glucose levels. Hence, acetone is emerging as a promising bio-marker in diabetes prediction. In this study, acetone levels are measured using quartz crystal microbalance sensor that has wide-scale application as a bio-sensor. It is a piezoelectric sensor which is used to detect and quantify mass variations. The resonant frequency of the sensor changes when there is a deposition of mass on the surface of the crystal. The shift in resonant frequency is directly proportional to the change in the mass concentration. To estimate the performance of this sensor, it is required to understand the sensor's electrical characteristics such as its conductance gain and admittance. This study studies these characteristics and evaluates the behaviour of the sensor in the presence of various acetone concentrations in breath sample for healthy, type 1 and type 2 diabetic subjects.