Abstract
Fourier transformation infrared (FT-IR) spectroscopy has been used to measure glucose concentrations in different matrices. The accuracy of the FT-IR technique does not meet the requirements of medical applications, so we have developed a new, efficient and precise method based on attenuated total reflectance coupled with wavelet transformation (ATR-WT-IR). One thousand interferograms, divided into training- and testing-sets, have been recorded from four glucose concentrations using an ATR-IR unit. Signals were subjected to (WT) and neural network (NN) study in order to design correlation algorithm. The Pearson's Correlation Coefficient (PCC) obtained by judging the predicted- against the real-concentrations was 0.9954, with a mean square error of 8.4e-005. The proposed ATR-WT-IR method shows efficiency in glucose prediction and could possibly to be integrated into a non-invasive monitoring technique.