期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2015
卷号：8
期号：2
页码：1244-1260
出版社：Massey University
摘要：There has been a constant demand for the development of non-invasive, sensitive glucosesensor system that offers fast and real-time electronic readout of blood glucose levels. In this article, wepropose a new system for detecting blood glucose levels by estimating the concentration of acetone inthe exhaled breath. A TGS822 tin oxide (SnO2) sensor has been used to detect the concentration ofacetone in the exhaled air. Acetone in exhaled breath showed a correlation with the blood glucoselevels. Effects of pressure, temperature and humidity have been considered. Artificial Neural Network(ANN) has been used to extract features from the output waveform of the sensors. The system has beentrained and tested with patient data in the blood glucose ranges from 80 mg/dl to 180 mg/dl. Using theproposed system, the blood glucose concentration has been estimated within an error limit of ±7.5mg/dl.
