Method and System for Evaluating Analyte Sensor Response Characteristics

• US 20110320167A1
• Filed: 06/22/2011
• Published: 12/29/2011
• Est. Priority Date: 06/23/2010
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Budiman, Erwin Satrya
• Granted Patent: US 8,635,046 B2
• Time in Patent Office: Days
• US Class Current: 702/179
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04

Abstract

Apparatus, method, system and kit for receiving a plurality of continuous analyte sensor values for corresponding reference analyte values, calculating a rate of change value for the continuous analyte sensor values, defining a plurality of data range windows of the reference analyte values, evaluating the corresponding continuous analyte sensor values, the rate of change values, the reference analyte values, and/or a plurality of corresponding difference values for the plurality of data range windows, and determining a best fit based on the evaluation of the plurality of data range windows are provided.

Claims

1. A method for evaluating characteristics of a continuous analyte sensor, the method comprising:

receiving a plurality of continuous analyte sensor values for corresponding reference analyte values;

calculating a rate of change value for the continuous analyte sensor values;

defining a plurality of data range windows of the reference analyte values;

evaluating the corresponding continuous analyte sensor values, the rate of change values, the reference analyte values, and/or a plurality of corresponding difference values for the plurality of data range windows; and

determining a best fit based on the evaluation of the plurality of data range windows.

2. The method of claim 1, wherein the difference value is the difference between the continuous analyte sensor value and the corresponding reference analyte value.

3. The method of claim 2, wherein determining the best fit includes determining a least-squares line based on a graphical representation of the rate of change values and the difference values for each of the plurality of data range windows.

4. The method of claim 3, further comprising determining a slope and an intercept of the least-squares line for each of the plurality of data range windows.

5. The method of claim 4, further comprising determining a best fit function based on a graphical representation of the intercepts of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a linearity characteristic of the continuous analyte sensor.

6. The method of claim 5, wherein determining the best fit function includes determining a best fit function based on a weighted graphical representation of the intercepts of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows.

7. The method of claim 6, wherein the weighted graphical representation includes scaling by the number of points in each data range window, scaling by the inverse of the square of the standard error of the slope in each data range window, or scaling by the inverse of the square of the standard deviation of the slope in each data range window.

8. The method of claim 4, further comprising determining a best fit function based on a graphical representation of the slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a lag characteristic of the continuous analyte sensor.

9. The method of claim 8, wherein determining the best fit function includes determining a best fit function based on a weighted graphical representation of the slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows.

10. The method of claim 9, wherein the weighted graphical representation includes scaling by the number of points in each data range window, scaling by the inverse of the square of the standard error of the slope in each data range window, or scaling by the inverse of the square of the standard deviation of the slope in each data range window.

11. The method of claim 4, further comprising determining a corrected slope for each of the slopes of the least-squares lines of each of the plurality of data range windows and determining a best fit function based on a graphical representation of the corrected slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a lag characteristic of the continuous analyte sensor.

12. The method of claim 9, wherein the corrected slope is determined based on weighted slopes of the least-squares lines of each of the plurality of data range windows.

13. An apparatus for evaluating characteristics of a continuous analyte sensor, the apparatus comprising:

one or more processors; and

a memory operatively coupled to the one or more processors, the memory storing instructions which, when executed by the one or more processors, causes the one or more processors to receive a plurality of continuous analyte sensor values for corresponding reference analyte values, calculate a rate of change value for the continuous analyte sensor values, define a plurality of data range windows of the reference analyte values, evaluate the corresponding continuous analyte sensor values, the rate of change values, the reference analyte values, and/or a plurality of corresponding difference values for the plurality of data range windows, and determine a best fit based on the evaluation of the plurality of data range windows.

14. The apparatus of claim 13, wherein the difference value is the difference between the continuous analyte sensor value and the corresponding reference analyte value.

15. The apparatus of claim 14, wherein the instructions to determine the best fit includes instructions to determine a least-squares line based on a graphical representation of the rate of change values and the difference values for the plurality of data range windows.

16. The apparatus of claim 15, wherein the memory further includes instructions which, when executed by the one or more processors, causes the one or more processors to determine a slope and an intercept of the least-squares line for the plurality of data range windows.

17. The apparatus of claim 16, wherein the memory further includes instructions which, when executed by the one or more processors, causes the one or more processors to determine a best fit function based on a graphical representation of the intercepts of the least-squares lines of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a linearity characteristic of the continuous analyte sensor.

18. The apparatus of claim 17, wherein the instructions to determine the best fit function includes instructions to determine a best fit function based on a weighted graphical representation of the intercepts of the least-squares lines of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows.

19. The apparatus of claim 18, wherein the weighted graphical representation includes scaling by the number of points in each data range window, scaling by the inverse of the square of the standard error of the slope in each data range window, or scaling by the inverse of the square of the standard deviation of the slope in each data range window.

20. The apparatus of claim 16, wherein the memory further includes instructions which, when executed by the one or more processors, causes the one or more processors to determine a best fit function based on a graphical representation of the slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a lag characteristic of the continuous analyte sensor.

21. The apparatus of claim 20, wherein the instructions to determine the best fit function includes instructions to determine a best fit function based on a weighted graphical representation of the slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows.

22. The apparatus of claim 21, wherein the weighted graphical representation includes scaling by the number of points in each data range window, scaling by the inverse of the square of the standard error of the slope in each data range window, or scaling by the inverse of the square of the standard deviation of the slope in each data range window.

23. The apparatus of claim 16, wherein the memory further includes instructions which, when executed by the one or more processors, causes the one or more processors to determine a corrected slope for each of the slopes of the least-squares lines of each of the plurality of data range windows and determine a best fit function based on a graphical representation of the corrected slopes of the least-squares lines of each of the plurality of data range windows and the reference analyte values at the centers of the plurality of data range windows, wherein the best fit function corresponds to a lag characteristic of the continuous analyte sensor.

24. The apparatus of claim 23, wherein the corrected slope is determined based on weighted slopes of the least-squares lines of each of the plurality of data range windows.