Development of a non-invasive blood glucose monitor: application of artificial neural networks for signal processing

Abstract

We have developed a noninvasive blood glucose measuring instrument, based on application of the Optical Bridge/sup TM/ in the near-infrared region. This exploratory research is an endeavor to evaluate the possibility of increasing the performance of the noninvasive glucose monitor by employing Artificial Neural Networks (ANN). The objective of this research is to design an ANN to interpret the instrument's outputs as well as the system parameters, and correlate them with blood glucose levels. The main hypothesis of this project is that such an ANN can be designed to improve the performance of this instrument.