Method and device for predicting physiological values
AssigneeAnimas Technologies, LLC
InventorsTimothy C. Dunn, Yalia Jayalakshmi, Ronald T. Kurnik, Matthew J. Lesho, Jonathan James Oliver, Russell O. Potts, Janet A. Tamada, Steven Richard Waterhouse, Charles W. Wei
Life of this patent
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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.
Claims1
A method of calibrating an analyte monitoring device for use in measuring analyte amount or concentration in a biological system, and said method comprising
- determining a calibration ratio (CalRatio) value, wherein
- CalRatio
- =
- BG
- cp
- (
- active
- cp
- +
- offset
- )
- wherein BGcp is a blood glucose concentration at the calibration point, activecp is an active signal that corresponds to an electrochemical sensor signal at the calibration point, and offset was a constant value;
- providing two or more ranges of CalRatio values;
- identifying a range in which said determined CalRatio value falls;
- employing an algorithm to predict further measurement values, the algorithm selected from one of a first algorithm and a second algorithm, the first algorithm comprising:
- BG=w1BG1+w2BG2+w3BG3
- where
- BG1=p1(time)+q1(active)+r1(signal)+s1(BG|cp)+t1
- BG2=p2(time)+q2(active)+r2(signal)+s2(BG|cp)+t2
- BG3=p3(time)+q3(active)+r3(signal)+s3(BG|cp)+t3
- w
- 1
- =
- ⅇ
- d
- 1
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- w
- 2
- =
- ⅇ
- d
- 2
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- w
- 3
- =
- ⅇ
- d
- 3
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- d1τ1(time)+β1(active)+γ1(signal)+δ1(BG|cp)+ε1
- d2τ2(time)+β2(active)+γ2(signal)+δ2(BG|cp)+ε2
- d3τ3(time)+β3(active)+γ3(signal)+δ3(BG|cp)+ε3
- in which BGi is the analyte predicted, BG/cp is the blood glucose value at a calibration point, time is the elapsed time, ative is the active signal, signal being the calibrated signal, pi, qi, ri are coefficients, ti is a constant, e indicates an exponential function, di is a parameter set usable to determine weightings wi, with τi, βi, γi, δi, and εi are constants, and the second equation comprising:
- BG=w1BG1+w2BG2+w3BG3
- where
- BG1=p1(timec)+q1(active)+r1(signal)+s1(BG|cp)+t1
- BG2=p2(timec)+q2(active)+r2(signal)+s2(BG|cp)+t2
- BG3=p3(timec)+q3(active)+r3(signal)+s3(BG|cp)+t3
- w
- 1
- =
- ⅇ
- d
- 1
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- w
- 2
- =
- ⅇ
- d
- 2
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- w
- 3
- =
- ⅇ
- d
- 3
- ⅇ
- d
- 1
- +
- ⅇ
- d
- 2
- +
- ⅇ
- d
- 3
- d1τ1(timec)+β1(active)+γ1(signal)+δ1(BG|cp)+ε1
- d2τ2(timec)+β2(active)+γ2(signal)+δ2(BG|cp)+ε2
- d3τ3(timec)+β3(active)+γ3(signal)+δ3(BG|cp)+ε3
- in which BGi is the analyte predicted, timec is the elapsed time since calibration, active is the active signal, signal is the calibrated signal, BG/cp is the blood glucose value at a calibration point, pi, qi, ri are coefficients, ti is a constant, e indicates an exponential function, di is a parameter set usable to determine weightings wi, with τi, βi, γi, δi, and εi are constants, wherein each of said algorithms is optimized for performance in the identified range;
- and
- generating further measurement values indicative of amount or concentration of analyte present in the biological system, said generating comprising obtaining a raw signal specifically related to analyte amount or concentration in the biological system and using said algorithm to correlate the raw signal with a measurement value.
Dependencies are inferred from the claim text.