Near-Infrared Spectroscopic Method for Noninvasive Blood Glucose Prediction without Using Multivariate Analyses

Abstract

A near-infrared spectroscopy method for noninvasive blood glucose prediction without using multivariate analyses is proposed and examined. Near-infrared diffuse reflection spectra with a wavelength range from 1400 to 1850 nm were measured at the skin tissue using an optical fiber probe. The difference spectra obtained by subtracting the initially measured spectrum from the other measured spectra were reconstructed from the spectra of four major components in the human skin (water, protein, glucose, and fat) and the spectrum of a scattering equivalent component called baseline, based on the modified Beer’s law. Then the blood glucose contents were predicted from the content index of the glucose component appearing in calculation of the reconstructed spectrum. We assumed that one of the origins of the errors in the blood glucose prediction using near-infrared spectroscopy was the similarity of the shapes of the absorption spectrum between glucose and baseline. To distinguish the glucose contribution from those of baseline and fat in the difference spectra, an imaginary component combining baseline and fat was introduced by considering that both the change in the fat contribution and the generation of baseline originated from the change in scattering in the skin. The imaginary component enabled us to reduce the errors in the blood glucose prediction. In contrast to the conventional methods using multivariate analyses, the calculation process of the proposed method is not so called "a black box." Thus, it is easy to estimate the origins of the changes and contributions of the components in the difference spectra. The proposed method may become a useful tool for realization of noninvasive blood glucose prediction. Disclosure K. Maruo: None. Y. Yamada: None.