Abstract: A method of and system for authenticating concealed and statistically varying multi-dimensional data comprising: acquiring an initial measurement of an item, wherein the initial measurement is subject to measurement error; applying a transformation to the initial measurement to generate reference template data; acquiring a subsequent measurement of an item, wherein the subsequent measurement is subject to measurement error; applying the transformation to the subsequent measurement; and calculating a Euclidean distance metric between the transformed measurements; wherein the calculated Euclidean distance metric is identical to a Euclidean distance metric between the measurement prior to transformation.

Abstract: A method and apparatus for measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved instrument-tailored or subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate instrument-specific attributes, resulting in a calibration data set modeling intra-instrument or intra-subject variation. In a prediction phase, the prediction process is tailored for each target instrument separately using a minimal number of spectral measurements from each instrument or subject.

Abstract: A method and apparatus for measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved instrument-tailored or subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate instrument-specific attributes, resulting in a calibration data set modeling intra-instrument or intra-subject variation. In a prediction phase, the prediction process is tailored for each target instrument separately using a minimal number of spectral measurements from each instrument or subject.

Abstract: A method and apparatus for non-invasively measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate subject-specific attributes, resulting in a calibration data set modeling within- subject physiological variation, sample location, insertion variations, and instrument variation. In a prediction phase, the prediction process is tailored for each target subject separately using a minimal number of spectral measurements from each subject.

Abstract: A method and apparatus for measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved instrument-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate instrument-specific attributes, resulting in a calibration data set modeling intra-instrument variation. In a prediction phase, the prediction process is tailored for each target instrument separately using a minimal number of spectral measurements from each instrument.

Abstract: A method and apparatus for non-invasively measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate subject-specific attributes, resulting in a calibration data set modeling within--subject physiological variation, sample location, insertion variations, and instrument variation. In a prediction phase, the prediction process is tailored for each target subject separately using a minimal number of spectral measurements from each subject.

Abstract: Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=f (cost, performance).

Abstract: This invention relates to methods and apparatus for, preferably, determining non-invasively and in vivo at least two of the five blood gas parameters (i.e., pH, [HCO.sub.3.sup.- ], PCO.sub.2, PO.sub.2, and O.sub.2 sat.) in a human.

Abstract: Multivariate classification techniques are applied to spectra from cell and tissue samples irradiated with infrared radiation to determine if the samples are normal or abnormal (cancerous). Mid and near infrared radiation can be used for in vivo and in vitro classifications using at least different wavelengths.

Abstract: Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance).

Abstract: Methods and apparatus for, preferably, determining noninvasively and in vivo at least two of the five blood gas parameters (i.e., pH, PCO.sub.2, [HCO.sub.3.sup.- ], PO.sub.2, and O.sub.2 sat.) in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 500 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of at least two of pH, [HCO.sub.3.sup.- ], PCO.sub.2 and a measure of oxygen concentration. The determined values are within the physiological ranges observed in blood containing tissue. The method also includes the steps of providing calibration samples, determining if the spectral intensities v. wavelengths from the tissue represents an outlier, and determining if any of the calibration samples represents an outlier.