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

• Published in: IET circuits, devices & systems Vol. 11; no. 6; pp. 682 - 687
• Main Authors: Lekha, Srinivasan, Manikandan, Suchetha
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.11.2017; John Wiley & Sons, Inc; Wiley
• Subjects: Acetone; acetone gas; acetone level measurement; admittance; bio-marker; biomedical electronics; bioMEMS; biosensor; biosensors; blood glucose levels; Breath tests; Chromatography; conductance gain; crystal surface; Diabetes; diseases; Gases; Glucose; level measurement; mass concentration; mass deposition; mass variations; mathematical modelling; microsensors; modified Butterworth van Dyke circuit model; noninvasive diabetes detection; piezoelectric sensor; piezoelectric transducers; Piezoelectricity; quartz crystal microbalance sensor; quartz crystal microbalances; Quartz crystals; reliable noninvasive diabetes prediction system; Research Article; Resonant frequencies; resonant frequency; sensor electrical characteristics; Sensors; simulation analysis; Spectrum analysis; sugar; VOCs; Volatile organic compounds; piezoelectric sensor; microsensors; blood glucose levels; bioMEMS; reliable noninvasive diabetes prediction system; bio-marker; resonant frequency; acetone gas; mass concentration; quartz crystal microbalance sensor; sensor electrical characteristics; biomedical electronics; conductance gain; acetone level measurement; crystal surface; modified Butterworth van Dyke circuit model; mass deposition; piezoelectric transducers; biosensor; quartz crystal microbalances; level measurement; mass variations; diseases; biosensors; admittance; mathematical modelling; noninvasive diabetes detection; simulation analysis; sugar
• ISSN: 1751-858X; 1751-8598; 1751-8598
• DOI: 10.1049/iet-cds.2017.0002

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.