System and method for using multiple sensor calibration methods

• US 10,327,685 B2
• Filed: 12/19/2013
• Issued: 06/25/2019
• Est. Priority Date: 12/20/2012
• Status: Active Grant

• Current Assignee: Becton, Dickinson & Co
• Original Assignee: Becton, Dickinson & Co
• Inventors: Keith, Steven, Fu, Yongji, McVey, Elaine, Zhang, Yiwen
• Primary Examiner(s): Weare, Meredith
• Application Number:
  US14/134,881
• Publication Number:
  US 20140180048A1
• Time in Patent Office: 2,014 Days
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B

Abstract

The present invention relates to a system and method for improving glucose sensor accuracy by utilizing multiple calibration methods and selecting the most accurate method depending on a consensus glucose concentration estimate. Embodiments of the present invention comprise the steps of performing at least one in vivo update of surrounding glucose to acquire glucose values; calculating multiple updated calibration estimates using the updated glucose values; calculating an initial consensus glucose estimate from sensor output using each updated calibration estimate; applying a smooth crossover function to the multiple calibration estimates based on the value of the initial consensus glucose estimate; and adding weights to the multiple calibration estimates to acquire a consensus glucose estimate.

Claims

1. A method for improving glucose sensor accuracy by utilizing multiple calibration estimates, the method comprising the steps of:

performing at least one in vivo update of surrounding glucose to acquire glucose values with the glucose sensor;

applying multiple calibration estimates to the updated glucose values;

calculating multiple updated calibration estimates using the updated glucose values;

wherein each of the multiple calibration estimates is more accurate than the other of the multiple calibration estimates within one of a plurality of glucose concentration ranges;

calculating an initial consensus glucose estimate value from sensor output using each updated calibration estimate;

weighting the multiple updated calibration estimates based on the value of the initial consensus glucose estimate value such that the weights sum to unity, wherein the weights are smoothly shifted from zero to one among the multiple calibration estimates as a function of the initial consensus glucose estimate value in glucose concentration regions around boundaries of the plurality of glucose concentration ranges;

determining a glucose level with the glucose sensor based on a weighted multiple calibration estimates; and

displaying the determined glucose level on a display of a glucose blood measurement device.

2. The method of claim 1, wherein the initial consensus glucose estimate is calculated by calculating a median of the multiple updated calibration estimates.

3. The method of claim 1, further comprising determining a calibration estimate by comparative analysis of a representative set of in vivo data.

4. The method of claim 1, further comprising setting a nocturnal hypoglycemia alarm in a glucose region between 70 to 110 mg/dL.

5. The method of claim 1, wherein the multiple updated calibration estimates are calculated based on the equation:

S=(S0+Sinf*Glucose/KD)/(1+Glucose/KD) or

Glucose=KD*(S−

S0)/(Sinf−

S), where

S=sensor output,

KD=apparent binding constant,

S0=sensor output when no glucose is present, and

Sinf=sensor output when glucose is present at saturating levels.

6. The method of claim 5, wherein glucose level is determined based on a diffusion-based transport equation:

PG=DF*{ISFG+Tau*d(ISFG)/dt}, where

PG=plasma glucose concentration,

ISFG=interstitial glucose concentration,

DF=in vivo dilution factor,

Tau=in vivo time constant, and

d(ISFG)/dt=the time rate of change of the interstitial glucose.

7. The method of claim 6, wherein glucose level is determined based on an equation for plasma glucose expressed as:

PG=DF*{KD*(S−

S0)/(Sinf−

S)+Tau*d[KD*(S−

S0)/(Sinf−

S)}]/dt}.