Signal processing for continuous analyte sensor

• US 8,290,561 B2
• Filed: 09/23/2009
• Issued: 10/16/2012
• Est. Priority Date: 12/09/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Brauker, James H., Carr-Brendel, Victoria, Goode, Paul V., Kamath, Apurv U., Thrower, James P., Xavier, Ben
• Primary Examiner(s): Natnithithadha, Navin
• Application Number:
  US12/565,180
• Publication Number:
  US 20100010324A1
• Time in Patent Office: 1,119 Days
• Field of Search: 600/309, 600345-366
• US Class Current: 600/345
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/1451 for interstitial fluid
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1468 using chemical or electrochemical methods, e.g. by polarographic means A61B5/1486 takes precedence
• CPC Class Codes: A61B 5/1473 invasive, e.g. introduced into the body by a catheter A61B5/1482 takes precedence
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation
• 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
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Systems and methods for dynamically and intelligently estimating analyte data from a continuous analyte sensor, including receiving a data stream, selecting one of a plurality of algorithms, and employing the selected algorithm to estimate analyte values. Additional data processing includes evaluating the selected estimative algorithms, analyzing a variation of the estimated analyte values based on statistical, clinical, or physiological parameters, comparing the estimated analyte values with corresponding measure analyte values, and providing output to a user. Estimation can be used to compensate for time lag, match sensor data with corresponding reference data, warn of upcoming clinical risk, replace erroneous sensor data signals, and provide more timely analyte information encourage proactive behavior and preempt clinical risk.

Claims

1. A method for estimating an analyte value from a continuous analyte sensor, the method comprising:

receiving a data stream from the continuous analyte sensor for a first time period, thereby obtaining a measured analyte value;

estimating at least one analyte value for a second time period based on the data stream;

comparing, using electronic circuitry, the estimated analyte value with the measured analyte value; and

determining a confidence interval based on the comparing.

2. The method of claim 1, wherein the step of comparing is performed continuously.

3. The method of claim 1, wherein the step of comparing comprises determining a correlation and/or deviation between the estimated analyte value and the measured analyte value.

4. The method of claim 1, further comprising analyzing a variation of one or more estimated analyte values based at least in part on the step of comparing.

5. The method of claim 1, wherein the step of estimating comprises selecting an algorithm from a plurality of algorithms based at least in part on the step of comparing.

6. The method of claim 1, wherein the step of comparing comprises comparing a first matched data pair formed from the measured analyte value and a reference analyte value with a second matched data pair formed from the estimated analyte value and a reference analyte value.

7. The method of claim 1, further comprising a step of providing output based at least in part on the comparing step.

8. The method of claim 7, wherein the output comprises displaying the measured analyte value.

9. The method of claim 7, wherein the output comprises displaying the estimated analyte value.

10. The method of claim 7, wherein the output comprises displaying an estimated analyte value for a future time period.

11. The method of claim 1, wherein the second time period comprises a future time period.

12. The method of claim 1, wherein the second time period is the same as and/or overlaps the first time period.

13. The method of claim 7, further comprising outputting the confidence interval.

14. A system for estimating analyte data from a continuous analyte sensor, the system comprising:

an input module operatively connected to the continuous analyte sensor that receives a data stream for a first time period; and

a processor module comprising programming configured to estimate at least one analyte value for a second time period based on the data stream, wherein the processor module further comprises programming configured to compare the estimated analyte value with a corresponding measured analyte value and determine a confidence interval therefrom.

15. The system of claim 14, wherein the programming configured to estimate at least one analyte value estimates the at least one analyte value continuously.

16. The system of claim 14, wherein the programming configured to compare the estimated analyte value with a corresponding measured analyte value determines a correlation and/or deviation between the estimated analyte value and the measured analyte value.

17. The system of claim 14, wherein the processor module further comprises programming configured to analyze a variation of one or more estimated analyte values based at least in part on the comparison.

18. The system of claim 14, wherein the programming configured to estimate at least one analyte value comprises selects an algorithm from a plurality of algorithms based at least in part on the comparison.

19. The system of claim 14, wherein the processor module further comprises programming configured to compare a first matched data pair formed from the measured analyte value and a reference analyte value with a second matched data pair formed from the estimated analyte value and a reference analyte value.

20. The system of claim 14, wherein the processor module further comprises programming configured to provide output based at least in part on the comparison.

21. The system of claim 20, wherein the output is configured to display the measured analyte value.

22. The system of claim 20, wherein the output is configured to display the estimated analyte value.

23. The system of claim 20, wherein the output is configured to display an estimated analyte value for a future time period.

24. The system of claim 14, wherein the second time period is a future time period.

25. The system of claim 14, wherein the second time period is the same as and/or overlaps the first time period.

26. The system of claim 20, wherein the output comprises the confidence interval.