Near-infrared noninvasive blood glucose prediction without using multivariate analyses: introduction of imaginary spectra due to scattering change in the skin.

A noninvasive measurement method is proposed and examined to continuously predict blood glucose contents using near-infrared diffuse reflection difference spectra measured at the skin tissue without using multivariate analyses. Using the modified Beer’s law, the difference spectra are assumed to be synthesized from four major components in the human skin (water, protein, glucose, and fat) and a scattering equivalent component called baseline. As a result, one of the origins of the errors in blood glucose prediction using near-infrared is found to be the similarity of the shapes of the absorption spectrum between glucose and baseline. After separating the glucose contributions from the difference spectra at the characteristic wavelengths of baseline and fat, an imaginary component combining baseline and fat is introduced by considering that both the change in the fat contribution and the generation of baseline originate from the change in scattering in the skin. The imaginary component enables us to reduce the errors in blood glucose prediction. In contrast to the methods using multivariate analyses, the calculation process of the blood glucose contents from the measured reflection spectra is clear in this method, thus, it is easy to estimate the origins of the changes and contributions of the components in the measured difference spectra. The proposed method may become a useful tool for realization of noninvasive blood glucose prediction using near-infrared spectroscopy.