Search Results (2)

For many years, successful noninvasive blood glucose monitoring assays have been announced, among which near-infrared (NIR) spectroscopy of skin is a promising analytical method. Owing to the tiny absorption bands of the glucose buried among a dominating variable spectral background, multivariate calibration is required to achieve applicability for blood glucose self-monitoring. The most useful spectral range with important analyte fingerprint signatures is the NIR spectral interval containing combination and overtone vibration band regions. A strategy called science-based calibration (SBC) has been developed that relies on a priori information of the glucose signal (“response spectrum”) and the spectral noise, i.e., estimates of the variance of a sample population with negligible glucose dynamics. For the SBC method using transcutaneous reflection skin spectra, the response spectrum requires scaling due to the wavelength-dependent photon penetration depth, as obtained by Monte Carlo simulations of photon migration based on estimates of optical tissue constants. Results for tissue glucose concentrations are presented using lip NIR-spectra of a type-1 diabetic subject recorded under modified oral glucose tolerance test (OGTT) conditions. The results from the SBC method are extremely promising, as statistical calibrations show limitations under the conditions of ill-posed equation systems as experienced for tissue measurements. The temporal profile differences between the glucose concentration in blood and skin tissue were discussed in detail but needed to be further evaluated. Full article

This article describes a new photoacoustic FT-IR system capable of operating at elevated temperatures. The key hardware component is an optical-readout cantilever microphone that can work up to 200 °C. All parts in contact with the sample gas were put into a heated oven, incl. the photoacoustic cell. The sensitivity of the built photoacoustic system was tested by measuring 18 different VOCs. At 100 ppm gas concentration, the univariate signal to noise ratios (1σ, measurement time 25.5 min, at highest peak, optical resolution 8 cm⁻¹) of the spectra varied from minimally 19 for o-xylene up to 329 for butyl acetate. The sensitivity can be improved by multivariate analyses over broad wavelength ranges, which effectively co-adds the univariate sensitivities achievable at individual wavelengths. The multivariate limit of detection (3σ, 8.5 min, full useful wavelength range), i.e., the best possible inverse analytical sensitivity achievable at optimum calibration, was calculated using the SBC method and varied from 2.60 ppm for dichloromethane to 0.33 ppm for butyl acetate. Depending on the shape of the spectra, which often only contain a few sharp peaks, the multivariate analysis improved the analytical sensitivity by 2.2 to 9.2 times compared to the univariate case. Selectivity and multi component ability were tested by a SBC calibration including 5 VOCs and water. The average cross selectivities turned out to be less than 2% and the resulting inverse analytical sensitivities of the 5 interfering VOCs was increased by maximum factor of 2.2 compared to the single component sensitivities. Water subtraction using SBC gave the true analyte concentration with a variation coefficient of 3%, although the sample spectra (methyl ethyl ketone, 200 ppm) contained water from 1,400 to 100k ppm and for subtraction only one water spectra (10k ppm) was used. The developed device shows significant improvement to the current state-of-the-art measurement methods used in industrial VOC measurements. Full article