Abstract: A method of calibrating a non-invasive blood glucose measurement instrument to a diabetic test subject employs targeted glycemic profiles in anti-correlated pairs. During calibration, reference blood glucose determinations are made using conventional invasive sampling methods. Concurrently, noninvasive spectral measurements are made using the noninvasive glucose monitor. Through controlled oral ingestion by the subject of calculated amounts of carbohydrate, the subject's blood glucose level is manipulated to mimic the patterns of the targeted profiles. During a first visit, a first profile of a pair is induced; during a second visit the inverse of the first profile is induced. The targeted profiles produce reference blood glucose values in which correlation to sampling factors is reduced or eliminated, thus the resulting calibration is correlated to glucose, and not to other analytes, sampling factors or environmental factors.

Abstract: The invention provides a class of samples that model the human body. This family of samples is based upon emulsions of oil in water with lecithin acting as the emulsifier. These solutions that have varying particle sizes may be spiked with basis set components (albumin, urea and glucose) to simulate skin tissues further. The family of samples is such that other organic compounds such as collagen, elastin, globulin and bilirubin may be added, as can salts such as Na+, K+ and Cl−. Layers of varying thickness with known index of refraction and particle size distributions may be generated using simple crosslinking reagents, such as collagen (gelatin). The resulting samples are flexible in each analyte's concentration and match the skin layers of the body in terms of the samples reduced scattering and absorption coefficients, &mgr;ms and &mgr;ma. This family of samples is provided for use in the medical field where lasers and spectroscopy based analyzers are used in treatment of the body.

Abstract: A novel approach to measuring the overall and layer-by-layer thickness of in vivo skin tissue based on near infrared absorbance spectra is described. The different biological and chemical compounds present in the various layers of a tissue sample have differing absorbance spectra and scattering properties that enable them to be discerned and quantified, thus allowing an estimate of the thickness of the tissue being sampled. The method of the invention also yields the chemical composition of the absorbing and/or scattering species of each layer. Additionally, a method of path length normalization for the purpose of noninvasive analyte prediction on the basis of skin thickness and layer constituents is provided.

Abstract: A method of calibrating a non-invasive blood glucose measurement instrument to a diabetic test subject employs targeted glycemic profiles in anti-correlated pairs. During calibration, reference blood glucose determinations are made using conventional invasive sampling methods. Concurrently, noninvasive spectral measurements are made using the noninvasive glucose monitor. Through controlled oral ingestion by the subject of calculated amounts of carbohydrate, the subject's blood glucose level is manipulated to mimic the patterns of the targeted profiles. During a first visit, a first profile of a pair is induced; during a second visit the inverse of the first profile is induced. The targeted profiles produce reference blood glucose values in which correlation to sampling factors is reduced or eliminated, thus the resulting calibration is correlated to glucose, and not to other analytes, sampling factors or environmental factors.

Abstract: An apparatus and method for non-invasively quantifying the hydration of the stratum corneum of a living subject utilizes in vivo spectral measurements made by irradiating skin tissue with near infrared (NIR) light. The apparatus includes a spectroscopic instrument in conjunction with a subject interface. The resulting NIR absorption spectra are passed to an analyzer for further processing, which includes detecting and eliminating invalid spectral measurements, and preprocessing to increase the signal-to-noise ratio. Finally, a calibration model developed from an exemplary set of measurements is applied to predict the SC hydration for the sample. The method of SC hydration measurement provides additional information about primary sources of systematic tissue variability, namely, the water content of the epidermal layer of skin and the penetration depth of the incident light.

Abstract: The invention provides a design process that is used in the determination of the pattern of detector and illumination optical fibers at the sampling area of a subject. Information about the system, specifically a monochromator (e.g. to determine the optimal number of fibers at an output slit) and the bundle termination at a detector optics stack (e.g. to determine the optimal number of fibers at the bundle termination), is of critical importance to this design. It is those numbers that determine the ratio and number of illumination to detection fibers, significantly limiting and constraining the solution space. Additional information about the estimated signal and noise in the skin is necessary to maximize the signal-to-noise ratio in the wavelength range of interest. Constraining the fibers to a hexagonal perimeter and prescribing a hex-packed pattern, such that alternating columns contain illumination and detection fibers, yields optimal results.

Abstract: An in vivo, non-invasive method of tissue classification using near-IR (NIR) spectral measurements. A classification model is based on NIR spectral absorbance measurements from an exemplary population. Spectral features representing variation between tissue types are identified. Analytic techniques enhance the features of interest and correct spectral interference to improve the predictive ability of the classification model. A classification routine defines classes based on variation between tissue types, such that variation within a class is small compared to variation between classes. A decision rule assigns individual samples from the exemplary population to classes. An in-vivo, non-invasive procedure applies the classification model to individual tissue samples. A preferred embodiment of the invention distinguishes transgenic mice from non-transgenic individuals based on variation in fat composition within muscle tissue.

Abstract: A method and apparatus for minimizing confounding effects in a noninvasive in-vivo spectral measurement caused by fluctuations in tissue state monitors a selected tissue state parameter spectroscopically and maintains the selected parameter within a target range, at which spectral effects attributable to the changes in the selected parameter are minimized. The invention includes means for both active and passive control.

Abstract: A method of multi-tier classification and calibration in noninvasive blood analyte prediction minimizes prediction error by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instrumental skin measurements, including in vivo near-IR spectral measurements. A multi-tier intelligent pattern classification sequence organizes spectral data into clusters having a high degree of internal consistency in tissue properties. In each tier, categories are successively refined using subject demographics, spectral measurement information and other device measurements suitable for developing tissue classifications.

Abstract: An intelligent system for measuring blood analytes noninvasively operates on a near infrared absorbance spectrum of in vivo skin tissue. An hierarchical architecture employs a pattern classification engine to adapt the calibration to the structural properties and physiological state of the subject as manifested in the absorbance spectrum. A priori information about the primary sources of sample variability are used to establish general categories of subjects. By applying calibration schemes specific to the various categories, the spectral interference is reduced resulting in improved prediction accuracy and parsimonious calibrations. Two classification rules are disclosed. The first rule assumes the classes are mutually exclusive and applies specific calibration models to the various subject categories. The second rule uses fuzzy set theory to develop calibration models and blood analyte predictions.