IP Library › Granted Patent US 12,165,757
Granted Patent B2
US 12,165,757 · App. 17/734,645 · Granted Dec 10, 2024

Systems and methods for processing sensor data

Inventors: Ying Li (San Diego, CA); Apurv Ullas Kamath (San Diego, CA); Aarthi Mahalingam (San Diego, CA); Michael R. Mensinger (San Diego, CA); J. Michael Dobbles (San Diego, CA)
Assignee: Dexcom, Inc.
G16H20/17A61B5/0031A61B5/14532A61B5/14546A61B5/14865A61B5/1495A61B5/4839A61B5/6848A61B5/7203A61B5/7221A61B5/742A61B5/7475A61M5/1723G16H20/00G16H20/10A61B5/0008A61B5/01A61B5/14542A61B5/7264A61B5/743A61B2560/0223A61B2560/04A61B2562/085G16H15/00G16H40/40G16H40/63G16H50/50Y02A90/10
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Quick Facts
Patent No.
US 12,165,757
App. No.
17/734,645
Granted
Dec 10, 2024
Kind
B2
Abstract

Systems and methods for processing sensor data are provided. In some embodiments, systems and methods are provided for calibration of a continuous analyte sensor. In some embodiments, systems and methods are provided for classification of a level of noise on a sensor signal. In some embodiments, systems and methods are provided for determining a rate of change for analyte concentration based on a continuous sensor signal. In some embodiments, systems and methods for alerting or alarming a patient based on prediction of glucose concentration are provided.

Claims (38)

1. A method for analyte monitoring, the method comprising:

receiving sensor data from a continuous analyte sensor applied to a host;

converting the sensor data to analyte data using a conversion function based at least on calibration information, wherein the conversion function includes one or more parameters;

determining a predictive accuracy of the calibration information used to calibrate the sensor data, the predictive accuracy comprising a value representing a degree of accuracy within a predefined range of accuracy, the degree of accuracy indicating a measure of the calibration information to produce calibrated sensor data that accurately predicts an analyte concentration in the host, wherein the value is different from the one or more parameters of the conversion function used for converting sensor data to analyte data; and

generating instructions for delivery of a medicament dosage according to the predictive accuracy of the calibration information.

2. The method of claim 1 , wherein the instructions instruct a computer system to request user interaction prior to the delivery of the medicament dosage based on the predictive accuracy.

3. The method of claim 2 , wherein the user interaction is a validation of the medicament dosage.

4. The method of claim 1 , wherein the instructions control a medicament delivery system in a closed loop to deliver the medicament dosage based on the predictive accuracy.

5. The method of claim 4 , wherein the medicament delivery system is an insulin delivery system that delivers doses of insulin to the host.

6. The method of claim 1 , further comprising controlling a medicament delivery system to deliver the medicament dosage to the host based on the instructions.

7. The method of claim 1 , wherein the continuous analyte sensor is a glucose sensor, and the sensor data is calibrated to predict a concentration of glucose in the host.

8. The method of claim 1 , wherein the calibration information is derived from a plurality of matched data pairs, each matched data pair including an analyte sensor signal and a corresponding analyte concentration.

9. The method of claim 1 , further comprising:

comparing the predictive accuracy with one or more accuracy level thresholds; and

generating the instructions for the delivery based on the comparing.

10. The method of claim 1 , wherein the degree of accuracy indicates a leverage of the calibration information based on the analyte concentration associated with the calibration information.

11. The method of claim 1 , wherein the value further represents a quantity of the calibration information that produces calibrated sensor data that accurately predicts the analyte concentration in the host.

12. The method of claim 1 , wherein the value quantifies an extent of deviation of the calibration information within the predefined range of accuracy.

13. A system comprising:

one or more processors; and

a memory storing instructions that are executable by the one or more processors to cause the system to perform operations including:

receiving sensor data from a continuous analyte sensor applied to a host;

converting the sensor data to analyte data using a conversion function based at least on calibration information, wherein the conversion function includes one or more parameters;

determining a predictive accuracy of the calibration information used to calibrate the sensor data, the predictive accuracy comprising a value representing a degree of accuracy within a range of accuracy, the degree of accuracy indicating a measure of the calibration information to produce calibrated sensor data that accurately predicts an analyte concentration in the host, wherein the value is different from the one or more parameters of the conversion function used for converting sensor data to analyte data; and

generating therapy instructions for delivery of a medicament dosage according to the predictive accuracy of the calibration information.

14. The system of claim 13 , wherein the therapy instructions instruct at least one device to output a request for user interaction prior to the delivery of the medicament dosage based on the predictive accuracy, and wherein the user interaction is a validation of the medicament dosage.

15. The system of claim 13 , wherein the therapy instructions control a medicament delivery system operatively connected in a closed loop to deliver the medicament dosage based on the predictive accuracy, and wherein the medicament delivery system is an insulin delivery system that delivers doses of insulin to the host.

16. The system of claim 13 , further comprising the continuous analyte sensor and a medicament delivery system operatively connected in a closed loop.

17. The system of claim 13 , wherein the operations further include controlling a medicament delivery system to deliver the medicament dosage to the host based on the therapy instructions.

18. The system of claim 13 , wherein the calibration information is derived from a plurality of matched data pairs, each matched data pair including an analyte sensor signal and a corresponding analyte concentration.

19. The system of claim 13 , wherein the operations further include:

comparing the predictive accuracy with one or more accuracy level thresholds; and

generating the therapy instructions based on the comparing.

20. A non-transitory computer storage component storing instructions that are executable by one or more processors to perform operations comprising:

receiving sensor data from a continuous analyte sensor applied to a host;

converting the sensor data to analyte data using a conversion function based at least on calibration information, wherein the conversion function includes one or more parameters;

determining a predictive accuracy of the calibration information used to calibrate the sensor data, the predictive accuracy comprising a value representing a degree of accuracy, the degree of accuracy indicating a measure of the calibration information to produce calibrated sensor data that accurately predicts an analyte concentration in the host, wherein the value is different from the one or more parameters of the conversion function used for converting sensor data to analyte data; and

generating therapy instructions for delivery of a medicament dosage according to the predictive accuracy of the calibration information.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 2, 2022
From: LI, YING; KAMATH, APURV ULLAS; MAHALINGAM, AARTHI; MENSINGER, MICHAEL R.; DOBBLES, JOHN MICHAEL
To: DEXCOM, INC.
Reel/Frame 059783/0776 →
Continuity (6)
Continuation 16537461 · Aug 9, 2019
Continuation 13899905 · May 22, 2013
Continuation 13495956 · Jun 13, 2012
Continuation 12258318 · Oct 24, 2008
Provisional Application 61014398 · Dec 17, 2007
Related Publication 20220262477A1 · Aug 18, 2022