Methods for measuring analyte in a subject and/or compensating for incomplete reaction involving detection of the analyte
First Claim
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1. A method for measuring glucose present in a subject, said method comprising:
- (A) transdermally extracting a sample comprising glucose from the subject using a sampling system that is in operative contact with a skin or mucosal surface of said subject, the system including first and second iontophoresis electrodes such that current flows through the first electrode to a first conductive medium into the skin, and back out from the skin through a second conductive medium to the second electrode;
(B) obtaining a measured signal over time, comprising a measured signal response curve, from the extracted glucose, wherein said measured signal is specifically related to the amount or concentration of glucose, and said measured signal response curve comprises kinetic and equilibrium regions;
(C) using (i) a mathematical model comprising selected parameters, wherein said model describes the measured signal response curve, and said mathematical model is selected from the group consisting of a first order process, combined first order and zero order process, a parallel multiple first order process, a flux process, and an n.sup.th order process, and (ii) an error minimization method, to iteratively estimate values of the parameters using said model and error minimization method to fit a predicted response curve to said measured signal response curve, wherein (a) the error minimization method provides a calculated error based on differences between said predicted and measured signal response curves, and (b) said estimating is iteratively performed until the calculated error between the predicted and measured signal response curves falls within an acceptable range or until no further statistically significant change is seen in the calculated error, at which time iterative estimation of the parameters is stopped, said iterative estimation and error minimization results in a predicted response curve corresponding to said measured signal response curve, said predicted response curve yields a predicted end-point value and a measurement correlated to the amount or concentration of the glucose in the sample of the subiect.
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Abstract
The present invention relates to a predictive-kinetic method for use with data processing of a sensor-generated signal, as well as, microprocessors and monitoring systems employing such a predictive-kinetic method. Data from a transient region of a signal is used with suitable models and curve-fitting methods to predict the signal that would be measured for the system at the completion of the reaction. The values resulting from data processing of sensor response using the methods of the present invention are less sensitive to measurement variables.
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Citations
19 Claims
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1. A method for measuring glucose present in a subject, said method comprising:
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(A) transdermally extracting a sample comprising glucose from the subject using a sampling system that is in operative contact with a skin or mucosal surface of said subject, the system including first and second iontophoresis electrodes such that current flows through the first electrode to a first conductive medium into the skin, and back out from the skin through a second conductive medium to the second electrode; (B) obtaining a measured signal over time, comprising a measured signal response curve, from the extracted glucose, wherein said measured signal is specifically related to the amount or concentration of glucose, and said measured signal response curve comprises kinetic and equilibrium regions; (C) using (i) a mathematical model comprising selected parameters, wherein said model describes the measured signal response curve, and said mathematical model is selected from the group consisting of a first order process, combined first order and zero order process, a parallel multiple first order process, a flux process, and an n.sup.th order process, and (ii) an error minimization method, to iteratively estimate values of the parameters using said model and error minimization method to fit a predicted response curve to said measured signal response curve, wherein (a) the error minimization method provides a calculated error based on differences between said predicted and measured signal response curves, and (b) said estimating is iteratively performed until the calculated error between the predicted and measured signal response curves falls within an acceptable range or until no further statistically significant change is seen in the calculated error, at which time iterative estimation of the parameters is stopped, said iterative estimation and error minimization results in a predicted response curve corresponding to said measured signal response curve, said predicted response curve yields a predicted end-point value and a measurement correlated to the amount or concentration of the glucose in the sample of the subiect. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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Specification