System and methods for processing analyte sensor data for sensor calibration
Systems and methods for processing sensor analyte data are disclosed, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. The sensor can be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. Reference data resulting from benchtop testing an analyte sensor prior to its insertion can be used to provide initial calibration of the sensor data. Reference data from a short term continuous analyte sensor implanted in a user can be used to initially calibrate or update sensor data from a long term continuous analyte sensor.
1. A method for calibrating a transcutaneous glucose sensor, comprising:
receiving a signal from a transcutaneous glucose sensor, wherein the signal is indicative of a glucose concentration in a host;
determining, using a processor module, a conversion function, wherein the conversion function comprises information associated with a sensitivity of the transcutaneous glucose sensor to glucose, wherein the information associated with the sensitivity of the transcutaneous glucose sensor to glucose is determined based at least in part on a joint probability distribution information associated with the sensitivity, wherein the joint probability distribution information is determined prior to sensor insertion;
converting sensor data using the conversion function, wherein the sensor data is associated with the signal indicative of the glucose concentration in the host;
generating an estimated glucose value based at least in part on the converted sensor data; and
displaying, on a display, the generated estimated glucose value.
2. The method of claim 1 , wherein determining the conversion function comprises selecting a most probable sensitivity based at least in part on the joint probability distribution information.
3. The method of claim 1 , wherein determining the conversion function comprises determining a baseline based at least in part on baseline distribution information determined prior to sensor insertion.
4. The method of claim 3 , wherein determining the baseline comprises selecting a most probable baseline based at least in part on the baseline distribution information.
5. The method of claim 1 , wherein the information associated with the sensitivity is, based at least in part on in-vitro sensitivity measurements.
6. The method of claim 1 , wherein the joint probability distribution information is based at least in part on vivo testing of at least one other transcutaneous glucose sensor or in vitro testing.
7. The method of claim 1 , further comprising displaying the converted sensor data in substantially real time.
8. The method of claim 1 , wherein the sensitivity of the transcutaneous glucose sensor to glucose is also based at least in part on an in vivo vs. in vitro sensitivity relationship that is determined prior to sensor insertion.
9. The method of claim 1 , wherein the processor is incorporated in a receiver.
10. The method of claim 1 , wherein the processor is incorporated in sensor electronics.
11. The method of claim 1 , wherein the processor is incorporated in a receiver.
12. The method of claim 1 , wherein the processor is incorporated in sensor electronics.
13. A method for calibrating a transcutaneous glucose sensor, comprising:
receiving a signal from a transcutaneous glucose sensor, wherein the signal is indicative of a glucose concentration in a host;
determining, using a processor module, a conversion function, wherein the conversion function comprises information associated with a sensitivity of the transcutaneous glucose sensor to glucose, wherein the information associated with the sensitivity of the transcutaneous glucose sensor to glucose is determined based at least in part on a distribution information associated with the sensitivity, wherein the distribution information is determined prior to sensor insertion, wherein the distribution information is derived at least in part from testing a plurality of sensors;
converting sensor data using the conversion function;
generating an estimated glucose value based at least in part on the converted sensor data; and
displaying, on a display, the generated estimated glucose value.
14. The method of claim 13 , wherein determining the conversion function comprises selecting a most probable sensitivity based at least in part on the distribution information.
15. The method of claim 13 , wherein determining the conversion function comprises determining a baseline based at least in part on baseline distribution information determined prior to sensor insertion.
16. The method of claim 15 , wherein determining the baseline comprises selecting a most probable baseline based at least in part on the baseline distribution information.
17. The method of claim 13 , wherein the information associated with the sensitivity is, based at least in part on in-vitro sensitivity information determined by a benchtop calibration process.
18. The method of claim 13 , further comprising displaying the converted sensor data is substantially real time.
19. The method of claim 13 , wherein the testing the plurality of sensors is performed in vitro.
20. The method of claim 13 , wherein the testing the plurality of sensors is performed in vivo.
21. The method of claim 13 , wherein the sensitivity of the transcutaneous glucose sensor to glucose is also based at least in part on an in vivo vs. in vitro sensitivity relationship that is determined prior to sensor insertion.