Method and device for predicting physiological values
First Claim
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1. A method for continually or continuously measuring an analyte present in a biological system, said method comprising:
- (a) transdermally extracting the analyte from the biological system using a sampling system that is in operative contact with a skin or mucosal surface of said biological system;
(b) obtaining a raw signal from the extracted analyte, wherein said raw signal is specifically related to the analyte;
(c) performing a calibration step which correlates the raw signal obtained in step (b) with a measurement value indicative of the concentration of analyte present in the biological system at the time of extraction;
(d) repeating steps (a)-(b) to obtain a series of measurement values at selected time intervals, wherein the sampling system is maintained in operative contact with the skin or mucosal surface of said biological system to provide for a continual or continuous analyte measurement; and
(e) predicting a measurement value based on the series of measurement values using the Mixtures of Experts algorithm, where the individual experts have a linear form wherein (An) is an analyte of interest, n is the number of experts, Ani is the analyte predicted by Expert i; and
wi is a parameter, and the individual experts Ani are further defined by the expression shown as Equation (2) wherein, Ani is the analyte predicted by Expert i;
Pj is one of m parameters, m is typically less than 100;
aij are coefficients; and
zi is a constant; and
further where the weighting value, wi, is defined by the formula shown as Equation (3) where e refers to the exponential function and the dk (note that the di in the numerator of Equation 3 is one of the dk) are a parameter set analogous to Equation 2 that is used to determine the weights wi, The dk are given by Equation 4 where α
jk is a coefficient, Pj is one of m parameters, and where ω
k is a constant.
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Abstract
The invention relates generally to methods, systems, and devices for measuring the concentration of target analytes present in a biological system using a series of measurements obtained from a monitoring system and a Mixtures of Experts (MOE) algorithm. In one embodiment, the present invention describes a method for measuring blood glucose in a subject.
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Citations
24 Claims
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1. A method for continually or continuously measuring an analyte present in a biological system, said method comprising:
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(a) transdermally extracting the analyte from the biological system using a sampling system that is in operative contact with a skin or mucosal surface of said biological system;
(b) obtaining a raw signal from the extracted analyte, wherein said raw signal is specifically related to the analyte;
(c) performing a calibration step which correlates the raw signal obtained in step (b) with a measurement value indicative of the concentration of analyte present in the biological system at the time of extraction;
(d) repeating steps (a)-(b) to obtain a series of measurement values at selected time intervals, wherein the sampling system is maintained in operative contact with the skin or mucosal surface of said biological system to provide for a continual or continuous analyte measurement; and
(e) predicting a measurement value based on the series of measurement values using the Mixtures of Experts algorithm, where the individual experts have a linear form wherein (An) is an analyte of interest, n is the number of experts, Ani is the analyte predicted by Expert i; and
wi is a parameter, and the individual experts Ani are further defined by the expression shown as Equation (2)wherein, Ani is the analyte predicted by Expert i;
Pj is one of m parameters, m is typically less than 100;
aij are coefficients; and
zi is a constant; and
further where the weighting value, wi, is defined by the formula shown as Equation (3)where e refers to the exponential function and the dk (note that the di in the numerator of Equation 3 is one of the dk) are a parameter set analogous to Equation 2 that is used to determine the weights wi, The dk are given by Equation 4 where α
jk is a coefficient, Pj is one of m parameters, and where ω
k is a constant. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for measuring blood glucose in a subject, said method comprising:
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(a) obtaining a raw signal from a sensing apparatus, wherein said raw signal is specifically related to the glucose detected by the sensing apparatus;
(b) performing a calibration step which correlates the raw signal obtained in step (a) with a measurement value indicative of the subject'"'"'s blood glucose concentration;
(c) repeating step (a) to obtain a series of measurement values at selected time intervals; and
(d) predicting a measurement value using the Mixtures of Experts algorithm, where the individual experts have a linear form;
wherein (An) is blood glucose value, n is the number of experts, Ani is the blood glucose value predicted by Expert i; and
wi is a parameter, and the individual experts Ani are further defined by the expression shown as Equation (2)wherein, Ani is the blood glucose value predicted by Expert i;
Pj is one of m parameters, m is typically less than 100;
aij are coefficients; and
zi is a constant; and
further where the weighting value, wi, is defined by the formula shown as Equation (3),where e refers to the exponential function and the dk (note that the di in the numerator of Equation 3 is one of the dk) are a parameter set analogous to Equation 2 that is used to determine the weights wi, The dk are given by Equation 4 where α
jk is a coefficient, Pj is one of m parameters, and where ω
k is a constant. - View Dependent Claims (11, 12, 13, 14, 16, 17, 18, 19)
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15. A monitoring system for continually or continuously measuring an analyte present in a biological system, said system comprising, in operative combination:
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(a) sampling means for continually or continuously extracting the analyte from the biological system, wherein said sampling means is adapted for extracting the analyte across a skin or mucosal surface of said biological system;
(b) sensing means in operative contact with the analyte extracted by the sampling means, wherein said sensing means obtains a raw signal from the extracted analyte and said raw signal is specifically related to the analyte; and
(c) microprocessor means in operative communication with the sampling means and the sensing means, wherein said microprocessor means (i) is used to control the sampling means and the sensing means to obtain a series of raw signals at selected time intervals during a continual or continuous measurement period, (ii) correlate the raw signals with measurement values indicative of the concentration of analyte present in the biological system, and (iii) predict a measurement value using the Mixtures of Experts algorithm, where the individual experts have a linear form wherein (An) is an analyte of interest, n is the number of experts, Ani is the analyte predicted by Expert i; and
wi is a parameter, and the individual experts Ani are further defined by the expression shown as Equation (2)wherein, Ani is the analyte predicted by Expert i;
Pj is one of m parameters, m is typically less than 100;
aij are coefficients; and
zi is a constant; and
further where the weighting value, wi, is defined by the formula shown as Equation (3)where e refers to the exponential function and the dk (note that the di in the numerator of Equation 3 is one of the dk) are a parameter set analogous to Equation 2 that is used to determine the weights wi. The dk are given by Equation 4 where α
k is a coefficient, Pj is one of m parameters, and where ω
k is a constant.
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20. A monitoring system for measuring blood glucose in a subject, said system comprising, in operative combination:
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(a) sensing means in operative contact with the subject or with a glucose-containing sample extracted from the subject, wherein said sensing means obtains a raw signal specifically related to blood glucose in the subject; and
(b) microprocessor means in operative communication with the sensing means, wherein said microprocessor means (i) is used to control the sensing means to obtain a series of raw signals at selected time-intervals, (ii) correlates the raw signals with measurement values indicative of the concentration of blood glucose present in the subject, and (iii) predicts a measurement value at a further time interval using the Mixtures of Experts algorithm, where the individual experts have a linear form BG=w1BG1+w2BG2+w3BG3
(5)wherein (BG) is blood glucose, there are three experts (n=3) and BGi is the analyte predicted by Expert i;
wi is a parameter, and the individual Experts BGi are further defined by the expression shown as Equations 6, 7, and 8BG1=p1(time)+q1(active)+r1(signal)+s1(BG|cp)+ti
(6) BG2=p2(time)+q2(active)+r2(signal)+s2(BG|cp)+t2
(7) BG3=p3(time)+q3(active)+r3(signal)+s3(BG|cp)+t3
(8)wherein, BGi is the analyte predicted by Expert i;
parameters include, time (elapsed time since the sampling system was placed in operative contact with said biological system), active (active signal), signal (calibrated signal), and BG/cp (blood glucose value at a calibration point);
pi, qi, ri, and si are coefficients; and
ti is a constant; and
further where the weighting value, wi, is defined by the formulas shown as Equations 9, 10, and 11where e refers to the exponential function and di is a parameter set (analogous to Equations 6, 7, and
8) that are used to determine the weights wi, given by Equations 9, 10, and 11, andd1=τ
1(time)+β
1(active)+γ
1(signal)+δ
1(BG|cp)+ε
1
(12)d2=τ
2(time)+β
2(active)+γ
2(signal)+δ
2(BG|cp)+ε
2
(13) d3=τ
3(time)+β
3(active)+γ
3(signal)+δ
3(BG|cp)+ε
3
(14)where τ
i, β
i, γ
i and δ
i are coefficients, and where ε
i is a constant. - View Dependent Claims (22, 23, 24)
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21. A monitoring system for measuring blood glucose in a subject, said system comprising, in operative combination:
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(a) sensing means in operative contact with the subject or with a glucose-containing sample extracted from the subject, wherein said sensing means obtains a raw signal specifically related to blood glucose in the subject; and
(b) microprocessor means in operative communication with the sensing means, wherein said microprocessor means (i) is used to control the sensing means to obtain a series of raw signals at selected time intervals, (ii) correlates the raw signals with measurement values indicative of the concentration of blood glucose present in the subject, and (iii) predicts a measurement value at a further time interval using the Mixtures of Experts algorithm, where the individual experts have a linear form BG=w1BG1+w2BG2+w3BG3
(15)wherein (BG) is blood glucose, there are three experts (n=3) and BGi is the analyte predicted by Expert i;
wi is a parameter, and the individual Experts BGi are further defined by the expression shown as Equations 16, 17, and 18BG1=p1(timec)+q1(active)+r1(signal)+s1(BG|cp)+t1
(16) BG2=p2(timec)+q2(active)+r2(signal)+s2(BG|cp)+t2
(17) BG3=p3(timec)+q3(active)+r3(signal)+s3(BG|cp)+t3
(18)wherein, BGi is the analyte predicted by Expert i;
parameters include, time, (elapsed time from a calibration of said sampling system), active (active signal), signal (calibrated signal), and BG/cp (blood glucose value at a calibration point) ;
pi, qi, ri, and si are coefficients; and
ti is a constant; and
further where the weighting value, wi, is defined by the formulas shown as Equations 19, 20, and 21where e refers to the exponential function and di is a parameter set (analogous to Equations 6, 7, and
8) that are used to determine the weights wi, given by Equations 19, 20, and 21, andd1=τ
1(timec)+β
1(active)+γ
1(signal)+δ
1(BG|cp)+ε
1
(22) d2=τ
2(timec)+β
2(active)+γ
2(signal)+δ
2(BG|cp)+ε
2
(23) d3=τ
3(timec)+β
3(active)+γ
3(signal)+δ
3(BG|cp)+ε
3
(24)where τ
i, β
i, γ
i and δ
i are coefficients, and where ε
i is a constant.
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Specification