Methods and apparatus for tailoring spectroscopic calibration models
First Claim
1. A method for generating a prediction result for use on a specific subject to predict a biological attribute of that subject using spectroscopy as a surrogate indirect measurement for a direct measurement of said biological attribute, said method comprising the steps of:
- (a) acquiring a calibration data set and modifying said calibration data set in a manner that reduces the spectral variation due to subject specific attributes;
(b) generating a model by applying multivariate analysis to said. modified calibration data set; and
(c) using a prediction process to predict an unknown amount of said biological attribute in a target spectroscopic measurement from said specific subject, said prediction process utilizing said model in conjunction with one or more reference measurements.
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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.
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Citations
64 Claims
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1. A method for generating a prediction result for use on a specific subject to predict a biological attribute of that subject using spectroscopy as a surrogate indirect measurement for a direct measurement of said biological attribute, said method comprising the steps of:
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(a) acquiring a calibration data set and modifying said calibration data set in a manner that reduces the spectral variation due to subject specific attributes; (b) generating a model by applying multivariate analysis to said. modified calibration data set; and (c) using a prediction process to predict an unknown amount of said biological attribute in a target spectroscopic measurement from said specific subject, said prediction process utilizing said model in conjunction with one or more reference measurements. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method of generating a calibration model that is essentially free from subject specific effects comprising building a generic model by:
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(a) obtaining a series of indirect measurements from a number of subjects, and obtaining a direct measurement for each subject corresponding to each indirect measurement; (b) forming the mean indirect measurement and the mean direct measurement for each subject based on the number of measurements from said each subject; (c) meancentering the series of indirect measurements by subject by subtracting the mean indirect measurement from each subject from each indirect;
measurement, and meancentering the direct measurement by subtracting the mean direct measurement from each direct measurement for each subject; and(d) forming a generic calibration model from the meancentered direct and indirect measurements. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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26. A method for generating a prediction result for use on a specific subject to predict a biological attribute of said specific subject using spectroscopy as a surrogate indirect measurement for a direct measurement of said biological attribute, said method comprising the steps of:
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(a) using a modified calibration data set previously processed in a manner that reduces the spectral variation due to subject specific attributes; (b) generating a calibration model through application of a multivariate algorithm that uses a composite calibration data set formed by combining the modified calibration data with two or more reference measurements; and (c) predicting an unknown amount of said biological attribute in a target spectroscopic measurement utilizing said calibration model. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A method for predicting a measure of a biological attribute for a specific subject, comprising:
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(a) obtaining a calibration data set of direct and indirect measurements of the biological attribute from a plurality of calibration subjects, wherein the calibration data set has been modified to reduce variations therein due to subject specific attributes for each calibration subject; (b) developing a subject-specific calibration model from said modified calibration data set tailored for the specific subject with at least one reference measurement of the biological attribute from the specific subject; (c) obtaining at least one indirect measurement of the biological attribute for the specific subject; and (d) using the said subject-specific calibration model and said "at least one" indirect measurement of the biological attribute for the specific subject to predict a measure of the biological attribute in the specific subject. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44, 45, 46, 47)
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48. A non-invasive method for measuring a biological attribute in human tissue of a specific subject comprising the steps of:
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(a) providing an apparatus for measuring infrared absorption, said apparatus including an energy source emitting infrared energy at multiple wavelengths operatively connected to an input element, said apparatus further including an output element operatively connected to a spectrum analyzer; (b) coupling said input and output elements to said human tissue; (c) irradiating said tissue through said input element with multiple wavelengths of infrared energy with resulting differential absorption of at least some of said wavelengths; (d) collecting at least a portion of the non-absorbed infrared energy with said output element followed by determining the intensities of said wavelengths of the non-absorbed infrared energy; and (e) predicting the biological attribute of said specific subject utilizing a model, wherein said subject specific prediction method uses spectroscopic variation from multiple subjects and one or more reference measurements from said specific subject, each of said reference measurements including spectroscopic and corresponding direct measurement of said biological attribute.
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49. A quantitative analysis instrument for non-invasive measurement of a biological attribute in human tissue of a specific subject, said instrument comprising:
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(a) a source of multiple wavelengths of infrared energy; (b) an input sensor element for directing said wavelengths of infrared energy into said tissue and an output sensor element for collecting at least a portion of the non-absorbed diffusely reflected infrared energy from said tissue, said input and said output sensors adapted to couple to the surface of said tissue; (c) at least one detector for measuring the intensities of at least a portion of said wavelengths collected by said output sensor element; and (d) electronics for processing said measured intensities and indicating a value for said biological attribute, said electronics including a processing method incorporated therein, said method utilizing calibration data which has been developed in a manner that reduces subject specific spectral attributes and said method utilizes one or more reference measurements from said specific subject. - View Dependent Claims (50, 51, 52, 53, 54)
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55. An instrument for the non-invasive measurement of a biological attribute for a specific subject, comprising:
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(a) a memory adapted to store a calibration data set of direct and indirect measurements of the biological attribute obtained from a plurality of calibration subjects, wherein the calibration data set has been modified to reduce variations therein due to subject specific attributes for each calibration subject; (b) means for developing a subject-specific calibration model from said modified calibration data set wherein said data set is tailored for the specific subject with at least one reference measurement of the biological attribute from the specific subject; (c) means for obtaining at least one indirect measurement of the biological attribute from the specific subject; and (d) means for obtaining a measurement of the biological attribute for the specific subject using the subject-specific calibration model and at least one indirect measurement of the biological attribute for the specific subject. - View Dependent Claims (56, 57, 58, 59, 60)
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61. A method for predicting a variable, comprising:
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(a) obtaining a calibration data set of direct measurements and indirect spectral measurements of the variable from a plurality of environments, wherein the calibration data set has been modified to reduce variations therein due to environment-specific attributes for each environment; (b) developing a environment-specific calibration model from said modified calibration data set tailored for the specific environment with at least one reference measurement of the variable from the specific environment; (c) obtaining at least one indirect measurement of the variable for the specific environment; and (d) using the said environment-specific calibration model and said "at least one" indirect measurement of the variable for the specific environment to predict a measure of the variable in the specific environment. - View Dependent Claims (62, 63, 64)
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Specification