SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA

• US 20140257067A1
• Filed: 05/20/2014
• Published: 09/11/2014
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Goode, Paul V. Jr., Brauker, James H., Kamath, Apurv Ullas, Thrower, James Patrick
• Granted Patent: US 9,895,089 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 5/0015 characterised by features of the telemetry system
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• 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 5/7275 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: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• 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 processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.

Claims

1-20. -20. (canceled)

21. A system for continuous glucose monitoring, comprising:

an in vivo sensor configured to measure a concentration of glucose in a host;

a computer system configured to process sensor data generated by the in vivo sensor; and

a user interface configured to display the sensor data associated with the in vivo sensor.

22. The system of claim 21, wherein the user interface is configured for interactive selection, by a user, of a type of sensor data displayed.

24. The system of claim 21, comprising a personal digital assistant, the personal digital assistant comprising the user interface.

25. The system of claim 21, wherein the personal digital assistant is adapted to communicate with a remote server.

26. The system of claim 21, wherein the user interface is configured to accept input of mealtime, exercise, insulin administration, and reference glucose values.

27. The system of claim 26, wherein the computer system is configured to store the input of mealtime, exercise, insulin administration, and reference glucose values.

28. The system of claim 26, wherein the computer system is configured to use the input to determine likelihood of acceptable reference data.

29. The system of claim 21, wherein the computer system is configured to receive a self-monitored blood glucose meter value via a wired or wireless connection with a self-monitored blood glucose meter in response to an initiation of a connection between the computer system and the self-monitored blood glucose meter by a user.

30. The system of claim 21, wherein the computer system is configured to match reference blood glucose values received from a patient with sensor data from the in vivo sensor using a variable time delay to account for a time delay introduced by the data smoothing filter or physiological time lag.

31. The system of claim 21, wherein the computer system is configured to receive reference blood glucose values from a self-monitored blood glucose meter, wherein the computer system is further configured to pre-screen the reference blood glucose values according to environmental and physiological issues selected from the group consisting of time of day, oxygen concentration, postural effects, and patient-entered environmental data.

32. The system of claim 21, wherein the computer system is configured to receive reference blood glucose values from a self-monitored blood glucose meter for in vivo calibration of the sensor data, wherein the computer system is further configured to pre-screen the reference blood glucose values, and wherein pre-screen criteria for initial in vivo calibration is different from prescreen criteria for update in vivo calibration.

33. The system of claim 21, wherein the computer system is configured to convert the sensor data into estimated sensor data using two or more different conversions dependent on one or more parameters selected from the group comprising time of day, calories consumed, exercise and glucose concentration above or below a set threshold.

34. The system of claim 21, wherein the in vivo sensor comprises a working electrode, a counter electrode, and a reference electrode.

35. The system of claim 34, wherein the computer system is configured to monitor the counter electrode for sensor stability or functionality.

36. The system of claim 34, wherein the computer system is configured to monitor the counter electrode against predetermined operational circuitry limits.

37. The system of claim 21, wherein the computer system is configured to display, on the user interface, an indication of instability of the sensor data.

38. The system of claim 37, wherein the indication of instability of the sensor data comprises flashing or faded information.

39. The system of claim 21, wherein the computer system is configured to process the sensor data by predicting glucose values forward to compensate for a time lag, whereby the predicted glucose values are displayed to the user that represent an equivalent blood glucose value without a time delay.

40. The system of claim 21, wherein the computer system is configured to process the sensor data by determining insulin administration timing information that for evading a hypoglycemic condition.

41. The system of claim 40, wherein the computer system is configured to output the insulin administration timing information.

42. The system of claim 21, wherein the computer system is configured to calibrate the sensor data and determine a quality of the calibration.

44. The system of claim 42, wherein the quality of calibration is configured to control a plurality of different sensor data displays.

23. The system of claim 23, wherein the type of sensor data displayed is interactively selected from a group of sensor data displays consisting of:

a numeric representation;

a one hour of historical trend data representation;

three hours of historical trend data representation; and

nine hours of historical trend data representation.

43-1. The system of claim 43, wherein the plurality of different modes comprise an initial fail-safe and full fail-safe mode.

45. A method for continuous glucose monitoring, comprising:

measuring, using an in vivo sensor, a concentration of glucose in a host;

processing sensor data generated by the in vivo sensor; and

displaying, on a user interface, the sensor data associated with the in vivo sensor.

46. A system for continuous glucose monitoring, comprising:

means for measuring, using an in vivo sensor, a concentration of glucose in a host;

means for processing sensor data generated by the in vivo sensor; and

means for displaying, on a user interface, the sensor data associated with the in vivo sensor.