New Methodology to Obtain a Calibration Model for Noninvasive Near-Infrared Blood Glucose Monitoring

Abstract

This paper reports new methodology to obtain a calibration model for noninvasive blood glucose monitoring using diffuse reflectance near-infrared (NIR) spectroscopy. Conventional studies of noninvasive blood glucose monitoring with NIR spectroscopy use a calibration model developed by in vivo experimental data sets. In order to create a calibration model, we have used a numerical simulation of light propagation in skin tissue to obtain simulated NIR diffuse reflectance spectra. The numerical simulation method enables us to design parameters affecting the prediction of blood glucose levels and their variation ranges for a data set to create a calibration model using multivariate analysis without any in vivo experiments in advance. By designing the parameters and their variation ranges appropriately, we can prevent a calibration model from chance temporal correlations that are often observed in conventional studies using NIR spectroscopy. The calibration model (regression coefficient vector) obtained by the numerical simulation has a characteristic positive peak at the wavelength around 1600 nm. This characteristic feature of the regression coefficient vector is very similar to those obtained by our previous in vitro and in vivo experimental studies. This positive peak at around 1600 nm also corresponds to the characteristic absorption band of glucose. The present study has reinforced that the characteristic absorbance of glucose at around 1600 nm is useful to predict the blood glucose level by diffuse reflectance NIR spectroscopy. We have validated this new calibration methodology using in vivo experiments. As a result, we obtained a coefficient of determination, r2, of 0.87 and a standard error of prediction (SEP) of 12.3 mg/dL between the predicted blood glucose levels and the reference blood glucose levels for all the experiments we have conducted. These results of in vivo experiments indicate that if the parameters and their vibration ranges are appropriately taken into account in a numerical simulation, the new calibration methodology provides us with a very good calibration model that can predict blood glucose levels with small errors without conducting any experiments in advance to create a calibration model for each individual patient. This new calibration methodology using numerical simulation has promising potential for NIR spectroscopy, especially for noninvasive blood glucose monitoring.

Near-Infrared Spectroscopy—Its Versatility in Analytical Chemistry

“…4·4·1 In vivo non-invasive measurement of blood glucose by near-infrared diffuse-reflectance spectroscopy NIR spectroscopy has been known to have a potential for realizing noninvasive blood glucose monitoring, and NIR noninvasive blood glucose assay has been investigated extensively for many years. [67][68][69][70][71][72][73][74][75][76][77][78] Robinson et al 71 and Muller et al 72 used a shorter wavelength NIR region, i.e. the region between 800 and 1300 nm (or 1350 nm for Muller et al 72 ) for finger DR spectra measurements.…”

Sensory Elements and Devices Operational Diagnostic Blood Glucose Using Near Infrared Radiation

“…[9] Based on the analyzed components designed and manufactured an experimental model of a portable device for measuring blood glucose level using noninvasive optical technique of near infrared radiation. The microcontroller is programmed based on the regression equation (3). This equation is formed so that glucose can be measured non-invasively.…”

“…1 schematically shows the effect of glucose molecules in the light path [3][4][5]. Fewer glucose results in less scattering, shorter path and hence less absorption, while more tissue glucose leads to greater dispersion of greater length optical path and hence greater tissue uptake.…”

“…In near infrared spectroscopy [3], the cells will produce glucose weakest signals absorption in humans, since glucose is one of the biological components present within the human body. When measuring glucose NIR spectroscopy enables signals to penetrate into the tissue to a depth ranging from 1 to 100 millimeters.…”

Net analyte signal with floating reference theory in non-invasive blood glucose sensing by near-infrared spectroscopy

“…The glucose signal of human skin in the NIR spectra is very weak compared with that from other skin tissue components or body temperature change. Thus, chance temporal correlation may occur easily from unreasonable experimental and analytical processes [4,5] . In addition, the most widely used PLS regression algorithm, which is designed to accentuate all signals, may result in functional models based on some chance correlation factors.…”