Greig W. Small

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An improved genetic algorithm (GA)-based wavelength selection procedure is developed to optimize both the near-infrared wavelengths used and the number of latent variables employed in building partial least-squares (PLS) calibration models. This GA-based wavelength selection algorithm is applied to the determination of glucose in two different biological(More)
A method is described for measuring clinically relevant levels of glucose in a protein matrix by near-infrared (near-IR) absorption spectroscopy. Results from an initial screening of major blood constituents identify protein as a major potential interference to the near-IR measurement of glucose in blood. The interference by protein is caused by relatively(More)
The validity of published reports claiming to have successfully measured in vivo blood glucose from noninvasive near-infrared spectra collected in a time-dependent manner is challenged on the basis of results obtained from a phantom glucose spectral data set. An in vitro model is used to simulate noninvasive human near-IR spectra. The phantom glucose data(More)
A procedure is described for the measurement of clinically relevant concentrations of glucose in aqueous solutions with near-infrared (NIR) absorbance spectroscopy. A glucose band centered at 4400 cm-1 is used for this analysis. NIR spectra are collected over the frequency range 5000-4000 cm-1 with a Fourier transform spectrometer. A narrow-band-pass(More)
Noninvasive blood glucose measurements are characterized in human subjects. A series of first overtone transmission spectra are collected across the tongues of five human subjects with type 1 diabetes. The noninvasive human spectra are collected by an experimental protocol that is designed to minimize chance correlations with blood glucose levels. In one(More)
A multivariate calibration procedure is described that is based on the use of a genetic algorithm (GA) to guide the coupling of bandpass digital filtering and partial least-squares (PLS) regression. The measurement of glucose in three different biological matrices with near-infrared spectroscopy is employed to develop this protocol. The GA is employed to(More)
Protocols are established for coupling digital filtering techniques with partial least-squares (PLS) regression for use in constructing multivariate calibration models from Fourier transform near-infrared absorbance spectra. Calibration models are developed to predict glucose concentrations in bovine plasma samples. Employing a calibration data set of 300(More)
Genetic algorithms (GAs) are used to implement an automated wavelength selection procedure for use in building multivariate calibration models based on partial least-squares regression. The method also allows the number of latent variables used in constructing the calibration models to be optimized along with the selection of the wavelengths. The data used(More)
Kromoscopy involves the transmission of a broad band of electromagnetic radiation through the sample of interest. The transmitted light is collected and divided evenly into four detector channels with complementary bandpass functions. This optical configuration provides high signal-to-noise ratios that are ideal for analytical measurements. The molecular(More)
A multivariate calibration method is described in which Fourier transform near-infrared interferogram data are used to determine clinically relevant levels of glucose in an aqueous matrix of bovine serum albumin (BSA) and triacetin. BSA and triacetin are used to model the protein and triglycerides in blood, respectively, and are present in levels spanning(More)