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.
Bacterial contamination of blood products is one of the most frequent infectious complications of transfusion. Since glucose levels in blood supplies decrease as bacteria proliferate, it should be possible to detect the presence of bacterial contamination by measuring the glucose concentrations in the blood components. Hence this study is aimed to serve as a preliminary study for the nondestructive measurement of glucose level in transfusion blood. The glucose concentrations in red blood cell (RBC) samples were predicted using near-infrared diffuse-reflectance spectroscopy in the 1350 to 1850 nm wavelength region. Furthermore, the effects of donor, hematocrit level, and temperature variations among the RBC samples were observed. Results showed that the prediction performance of a dataset which contained samples that differed in all three parameters had a standard error of 29.3 mg/dL. Multiplicative scatter correction (MSC) preprocessing method was also found to be effective in minimizing the variations in scattering patterns created by various sample properties. The results suggest that the diffuse-reflectance spectroscopy may provide another avenue for the detection of bacterial contamination in red cell concentrations (RCC) products.
For monitoring the blood glucose level noninvasively from the skin spectra, improvement of signal to noise ratio (S/N) of the glucose signal is critical. This cannot be achieved by the reduction of instrumental noise alone. To reduce the interference from undesired optical signals arising from the stratum corneum and the subcutaneous tissue, we designed a novel optical fiber probe for the skin spectra. The probe consisted of one central optical fiber around which several optical fibers were arranged in circle. The separation of the central optical fiber from each of the surrounding fibers was set at less than 1 mm. This probe was attached to the skin surface vertically when spectral measurements were performed. The measuring light was shone onto the skin surface through the circle fibers and scattered light reaching the central detecting fiber was collected and transmitted to the detection system. The true light path is not defined at present, but light passing through a long path could be neglected with this geometry. When we choose an adequate fiber distance, we can measure the dermis spectra selectively. Glucose intake experiments were performed with volunteers, for whom near-infrared (NIR) spectra were measured at the forearm, from which the blood glucose level was calculated. Partial least square regression (PLSR) analysis was carried out and we found good correlation between the optically estimated values of the glucose level and directly measured values of blood samples. The correlation coefficient characteristic had a positive peak at around 1600 nm, a typical of the glucose spectrum. In conclusion, our system using the novel optical fiber probe detected the changes in the glucose in the human skin tissue quantitatively and noninvasively.
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