Near-infrared spectroscopy has proven to be one of the most promising techniques for the development of a noninvasive blood glucose monitoring system for diabetic patients. In this work, Fourier transform infrared (FT-IR) transmission measurements of the combination band region (4000 - 5000 cm-1) were analyzed for samples containing glucose (analyte) in a matrix of bovine serum albumin and triacetin (models for proteins and fats), all spanning physiological levels relevant for a diabetic patient. The first part of the study investigated the required spectral point-spacing for accurate detection of glucose. This was studied by systematically truncating interferograms before Fourier transforming them to single-beam spectra. A set of training data (70 samples) was collected for multivariate calibration using partial least-squares (PLS) and an external prediction set was used to verify the success of modeling glucose quantitatively. It was found that a relatively large point-spacing (16 cm-1) was successful for prediction of glucose, meaning that a shorter interferogram could be collected. The second part of the study involved collecting interferograms such that the spectral resolution was 16 cm-1, and investigating methods to extend the usefulness of calibration models for long-term data collection. Near-infrared spectroscopy often suffers from weak signals that are overwhelmed by significant instrumental drift, meaning that calibration models tend to be unsuccessful for data collected several days or months outside the calibration. For updating the calibration models, a set of 50 backgrounds containing only matrix constituents without analyte was collected on each analysis day, and used to update the original calibration model so that instrumental drift features were incorporated into the model. Background updating was found to be successful in single-beam format, producing a background-augmented (BA) PLS model that significantly improved single-beam data analysis. The standard error of prediction using the original model (PLS) and the updated model (BA-PLS) were 13.4 and 0.79 mM glucose, respectively, for a prediction set taken 176 days outside of the calibration. The matrix data also allowed for studies in background selection methods for absorbance computations as well as adaptive digital filtering that was guided by the background data.

Polarized light has the ability to increase the specificity of the investigation of biomedical samples and is finding greater utilization in the fields of medical diagnostics, sensing, and measurement. In particular, this dissertation focuses on the application of polarized light to address a major obstacle in the development of an optical based polarimetric non-invasive glucose detector that has the potential to improve the quality of life and prolong the life expectancy of the millions of people afflicted with the disease diabetes mellitus. By achieving the mapping of the relative variations in rabbit corneal birefringence, it is hoped that the understanding of the results contained herein will facilitate the development of techniques to eliminate the effects of changing corneal birefringence on polarimetric glucose measurement through the aqueous humor of the eye. This dissertation also focuses on the application of polarized light to address a major downside of cardiovascular biomechanics research, which is the utilization of toxic chemicals to prepare samples for histological examination. To this end, a polarization microscopy image processing technique is applied to non-stained cardiovascular samples as a means to eliminate, for certain cardiac samples, the necessity for staining using toxic chemicals. The results from this work have the potential to encourage more investigators to join the field of cardiac biomechanics, which studies the remodeling processes responsible for cardiovascular diseases such as myocardial infarct (heart attacks) and congestive heart failure. Cardiovascular disease is epidemic, particularly amongst the population group older than 65 years, and the number of people affected by this disease is expected to increase appreciably as the baby boomer generation transitions into this older, high risk population group. A better understanding of the responsible mechanisms for cardiac tissue remodeling will facilitate the development of better prevention and treatment regimens by improving the early detection and diagnosis of this disease.

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