Indicator and analytics for sensor insertion in a continuous analyte monitoring system and related methods

• US 9,610,013 B2
• Filed: 11/12/2014
• Issued: 04/04/2017
• Est. Priority Date: 11/14/2013
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Koehler, Katherine Yerre, Bowman, Leif N., Draeger, Rian, Dunn, Laura, Reihman, Eli
• Primary Examiner(s): FILE, ERIN M
• Application Number:
  US14/539,956
• Publication Number:
  US 20150135118A1
• Time in Patent Office: 874 Days
• CPC Class Codes: A61B 2560/0487 Special user inputs or interfaces
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/684 Indicating the position of the sensor on the body
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/748 Selection of a region of interest, e.g. using a graphics tablet
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• 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

The present embodiments provide systems and methods for, among others, tracking sensor insertion locations in a continuous analyte monitoring system. Data gathered from sensor sessions can be used in different ways, such as providing a user with a suggested rotation of insertion locations, correlating data from a given sensor session with sensor accuracy and/or sensor session length, and providing a user with a suggested next insertion location based upon past sensor accuracy and/or sensor session length at that location.

Claims

1. A method for continuous analyte monitoring, comprising:

detecting, by a continuous analyte monitoring system, continuously monitored analyte data using a sensor of the continuous analyte monitoring system inserted into skin of a host for a first sensor session of the continuous analyte monitoring system;

providing, by the continuous analyte monitoring system, the detected continuously monitored analyte data to one or both of a user computing device and a cloud-based server;

determining quantitative data associated with the continuously monitored analyte data relating to the first sensor session;

correlating the quantitative data with the insertion location to form sensor location performance data;

analyzing the sensor location performance data with one or more other sensor location performance data associated with a different insertion location to generate a recommended location for a second sensor session;

displaying, on the user computing device having a display, a diagram of a body; and

indicating, on the diagram, the recommended location for insertion of a sensor of the continuous analyte monitoring system for the second sensor session.

2. The method of claim 1, wherein the one or more other sensor location performance data associated with a different insertion location includes data pertaining to at least one other host.

3. The method of claim 1, wherein the quantitative data relates to accuracy and/or reliability of the continuously monitored analyte data.

4. The method of claim 3, wherein the quantitative data pertains to at least one of a sensor accuracy metric, a sensor session length metric, a sensor baseline metric, a sensor sensitivity metric, a sensor sensitivity decline over time metric, or a sensor performance metric.

5. The method of claim 4, wherein the sensor performance metric includes one or more of sensor performance vs. past performance in a same person, sensor performance vs. past performance in a population of users, sensor performance by days or wear, sensor performance by geographical location, sensor performance by external environment, or sensor performance by activity level.

6. The method of claim 3, wherein the quantitative data pertains to at least one of signal noise, time spent out of communication range, adhesive data, data capture, noise metrics, detected faults, end of life metrics, or confidence levels.

7. The method of claim 1, further comprising receiving as an input personal information of the host.

8. The method of claim 7, wherein the personal information includes at least one of height, weight, age, sex, body mass index, the host'"'"'s current mood, the host'"'"'s current pain level, the host'"'"'s current comfort level, the host'"'"'s current confidence level, the host'"'"'s perception of sensor performance, a location of an insulin infusion pump relative to the sensor, adhesive irritation, or adhesive success rate.

9. A method for continuous analyte monitoring, comprising:

receiving, using a user computing device, input indicative of an insertion location on a body where a sensor of a continuous analyte monitoring system was inserted into skin of a host for a sensor session;

storing, at the user computing device, the input indicative of the insertion location;

detecting, by the continuous analyte monitoring system, continuously monitored analyte data relating to the sensor session of the sensor;

providing, by the continuous analyte monitoring system, the detected continuously monitored analyte data to the user computing device;

determining quantitative data associated with the continuously monitored analyte data relating to the sensor session; and

correlating the quantitative data with the insertion location to form sensor location performance data.

10. The method of claim 9, further comprising providing a recommendation for a next insertion location based on the sensor location performance data.

11. The method of claim 9, further comprising storing, at the user computing device, the sensor location performance data.

12. The method of claim 9, further comprising transmitting the sensor location performance data to a database, the database including other sensor location performance data associated with other hosts.

13. The method of claim 9, wherein the remote computing device performs at least one of the steps of determining the quantitative data, or correlating the quantitative data with the insertion location.

14. The method of claim 9, wherein the quantitative data relates to accuracy and/or reliability of the continuously monitored analyte data.

15. The method of claim 14, wherein the quantitative data pertains to at least one of a sensor accuracy metric, a sensor session length metric, a sensor baseline metric, a sensor sensitivity metric, a sensor sensitivity decline over time metric, or a sensor performance metric.

16. The method of claim 15, wherein the sensor performance metric includes one or more of sensor performance vs. past performance in a same person, sensor performance vs. past performance in a population of users, sensor performance by days or wear, sensor performance by geographical location, sensor performance by external environment, or sensor performance by activity level.

17. The method of claim 14, wherein the quantitative data pertains to at least one of signal noise, time spent out of communication range, adhesive data, data capture, noise metrics, detected faults, end of life metrics, or confidence levels.

18. The method of claim 9, further comprising receiving as an input personal information of the host.

19. The method of claim 18, wherein the personal information includes at least one of height, weight, age, sex, body mass index, the host'"'"'s current mood, the host'"'"'s current pain level, the host'"'"'s current comfort level, the host'"'"'s current confidence level, the host'"'"'s perception of sensor performance, a location of an insulin infusion pump relative to the sensor, adhesive irritation, or adhesive success rate.

20. The method of claim 9, further comprising transmitting the input indicative of the insertion location and the detected continuously monitored analyte data to a server, wherein the server performs at least one of the steps of determining the quantitative data, or correlating the quantitative data with the insertion location.