SYSTEM AND METHOD FOR USING MULTIPLE SENSOR CALIBRATION METHODS

• US 20140180048A1
• Filed: 12/19/2013
• Published: 06/26/2014
• 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
• Granted Patent: US 10,327,685 B2
• Time in Patent Office: Days
• US Class Current: 600/347
• 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;

applying multiple calibration estimates to the updated 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.

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

3. The method of claim 1, wherein glucose region boundaries are variously set according to the final use of the multiple glucose estimates.

4. The method of claim 3, wherein the smooth crossover function applies a continuous weighting function to the output of each calibration estimate so that at any glucose level the combined weight of the multiple calibration estimates is equal to one.

5. The method of claim 3, wherein within each glucose region, only one calibration estimate is fully weighted.

6. The method of claim 3, wherein at boundaries between glucose regions, the weights for each estimate are changed so that the total weight is always equal to one.

7. The method of claim 1, wherein a calibration estimate is selected by comparative analysis of a representative set of in vivo data.

8. The method of claim 1, wherein the smooth crossover function is determined by an optimization of the closest calibration estimates according to the intended use of the closest calibration estimates.

9. The method of claim 3, wherein a nocturnal hypoglycemia alarm is set in a glucose region of approximately 70 to 110 mg/dL.

10. The method of claim 1, wherein a relationship between sensor output and surrounding glucose can be expressed 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.

11. The method of claim 10, wherein sensor outputs and plasma are related by 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.

12. The method of claim 11, wherein an equation for plasma glucose is expressed as:

PG=DF*{KD*(S−

S0)/(Sinf−

S)+Tau*d[KD*(S−

S0)/(Sinf−

S)}]/dt }.