Signal processing for continuous analyte sensor

• US 9,364,173 B2
• Filed: 09/23/2009
• Issued: 06/14/2016
• 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
• Assistant Examiner(s): MESSERSMITH, ERIC J
• Application Number:
  US12/565,231
• Publication Number:
  US 20100010332A1
• Time in Patent Office: 2,456 Days
• Field of Search: 600/300, 600/309, 600/316, 600345-366, 702/19, 702/22, 702/23
• US Class Current: 1/1
• 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 processing sensor data from a continuous analyte sensor, comprising:

receiving sensor data from a continuous analyte sensor for a first time period, wherein the sensor data comprises at least one sensor data point;

processing, using one or more processors, the at least one sensor data point to obtain a range of target analyte values for a future time period; and

providing, using the one or more processors, output, wherein providing output comprises the one or more processors selecting whether or not to display an object representative of the range of target analyte values on a user interface based at least in part on a variability analysis of the sensor data using the one or more processor.

2. The method of claim 1, wherein, the target glucose value is based on an individual physiological pattern.

3. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining whether the target analyte value or range of target analyte values is based on a clinical acceptability.

4. The method of claim 1, wherein the continuous analyte sensor is a continuous glucose sensor.

5. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining the range of target analyte values based at least in part on at least one parameter that is customizable by the user.

6. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining the range of target analyte values based at least in part on an amount and/or timing of a medicament delivery and/or caloric consumption.

7. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining the range of target analyte values based at least in part on a host'"'"'s physiological pattern.

8. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining the range of target analyte values based at least in part on the sensor data.

9. The method of claim 1, wherein processing the at least one sensor data point to obtain a range of target analyte values for a future time period comprises determining the range of target analyte values based at least in part on the variation analysis of the sensor data using a clinical, physiological, and/or statistical variation analysis.

10. The method of claim 1, wherein providing output comprises displaying the range of target analyte values along a path of target analyte values.

11. The method of claim 1, wherein providing output comprises simultaneously displaying a real-time analyte value and the range of target analyte values on the user interface.

12. The method of claim 1, wherein processing further comprises determining a therapy recommendation to guide a user to achieve a target analyte value.

13. The method of claim 12, the therapy recommendation comprises at least one of a type of medicament and an amount of a medicament.

14. The method of claim 12, wherein providing output further comprises displaying the therapy recommendation on the user interface.

15. A system for processing sensor data from a continuous analyte sensor, the system comprising:

an input module operatively connected to a continuous analyte sensor so as to receive sensor data from the continuous analyte sensor, wherein the sensor data comprises at least one sensor data point;

a processor module that processes the at least one sensor data point to obtain a range of target analyte values for a future time period; and

an output module configured to selectively display an object representative of a range of target analyte values on a user interface, the selective display based at least in part on a variation analysis of the sensor data using the processor module.

16. The system of claim 15, wherein the range of target analyte values is based on a clinically acceptability.

17. The system of claim 15, wherein the continuous analyte sensor is a continuous glucose sensor.

18. The system of claim 15, wherein the range of target analyte values is based at least in part on at least one parameter that is customizable by the user.

19. The system of claim 15, wherein the range of target analyte values is based at least in part on at least one of an amount of medicament delivery, a timing of a medicament delivery, and caloric consumption.

20. The system of claim 15, wherein the range of target analyte values is based at least in part on a host'"'"'s physiological pattern.

21. The system of claim 15, wherein the range of target analyte values is based at least in part on the sensor data.

22. The system of claim 15, wherein the range of target analyte values is based at least in part on the variation analysis of the sensor data using at least one of a clinical analysis, a physiological analysis, and a statistical variation analysis.

23. The system of claim 15, wherein the object representative of the range of target analyte values is displayed along a path of target analyte values.

24. The system of claim 15, wherein the output module is configured to simultaneously display a real-time analyte value and the range of target analyte values on the user interface.

25. The system of claim 15, wherein the processor module determines a therapy recommendation to guide a user to achieve a target analyte value.

26. The system of claim 25, wherein the therapy recommendation comprises at least one of a type of medicament and an amount of a medicament.

27. The system of claim 25, wherein the output module is configured to display the therapy recommendation on the user interface.

28. A method for processing sensor data from a continuous analyte sensor, comprising:

receiving sensor data from a continuous analyte sensor for a first time period, wherein the sensor data comprises at least one sensor data point;

processing, using one or more processors, the at least one sensor data point to obtain a range of target analyte values for a future time period; and

providing output, using the one or more processors, wherein providing output comprises displaying the range of target analyte values on a user interface, wherein providing output comprises the one or more processors selectively displaying the range of target analyte values in response to a present or future clinical risk being determined by the one or more processors.

29. A system for processing sensor data from a continuous analyte sensor, the system comprising:

an input module operatively connected to a continuous analyte sensor so as to receive sensor data from the continuous analyte sensor, wherein the sensor data comprises at least one sensor data point;

a processor module that processes the at least one sensor data point to obtain a range of target analyte values for a future time period; and

an output module configured to display an object representative of a range of target analyte values on a user interface, wherein the range of target analyte values is selectively displayed in response to a present or future clinical risk being determined by the processor module.