SYSTEMS AND METHODS FOR LEVERAGING SMARTPHONE FEATURES IN CONTINUOUS GLUCOSE MONITORING

• US 20140012510A1
• Filed: 03/13/2013
• Published: 01/09/2014
• Est. Priority Date: 07/09/2012
• Status: Abandoned Application

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Mensinger, Michael Robert, Bhavaraju, Naresh C., Bowman, Leif N., Carlton, Alexandra Lynn, DeRenzy, David, Garcia, Arturo, Gauba, Indrawati, Hall, Ashley, Hall, Thomas, Hampapuram, Hari, Kazalbash, Murrad, Mahalingam, Aarthi, Pryor, Jack, Rack-Gomer, Anna Leigh, Reihman, Eli, San Vicente, Kenneth, Simpson, Peter C., Steele, Alexander, Valdes, Jorge, Estes, Michael J., Cohen, Eric
• Application Number:
  US13/801,445
• Publication Number:
  US 20140012510A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• 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 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6801 specially adapted to be attached to or worn on the body surface
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7435 Displaying user selection data, e.g. icons in a graphical user interface
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: F04C 2270/041 Controlled or regulated
• CPC Class Codes: G08B 21/0453 worn on the body to detect health condition by physiological monitoring, e.g. electrocardiogram, temperature, breathing detecting, measuring or recording for diagnostic purposes A61B5/00
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

The present embodiments harness a wide variety of capabilities of modern smartphones, and combine these capabilities with information from a continuous glucose monitor to provide diabetics and related people with more information than the continuous glucose monitor can provide by itself. The increased information provides the diabetic with an increased likelihood of good diabetes management for better health.

Claims

1. A machine-executed method of continuous analyte monitoring for a host to facilitate management of the host'"'"'s blood glucose level, the method comprising:

receiving a first input from a timekeeping/scheduling module executed by an electronic device, the first input including information about an upcoming event;

receiving a second input from a continuous analyte monitoring (CAM) device including analyte concentration data of the host;

processing the first and second inputs by analyzing an event or an operational mode associated with either of the timekeeping/scheduling module or the CAM device; and

producing an output by synchronizing the event or the operational mode of at least one of the timekeeping/scheduling module and the CAM device with the other of the timekeeping/scheduling module and the CAM device.

2. The method of claim 1, wherein the output is to the timekeeping/scheduling module to schedule an event.

3. The method of claim 1, wherein the event is to eat, to obtain a reference glucose value, or to inject insulin.

4. The method of claim 1, wherein the wherein the output is sent to a user, a caretaker, a parent, a guardian, or a healthcare professional.

5. The method of claim 1, wherein the output is a recommendation provided via screen prompt, text message, e-mail message, or a post to a social network.

6. The method of claim 1, wherein the output is a change in the operating mode of the electronic device.

7. The method of claim 6, wherein the operating mode is a vibrate mode or a silent mode.

8. The method of claim 1, wherein the processing comprises analyzing a user'"'"'s blood glucose data.

9. The method of claim 1, wherein the output comprises instructions to schedule an event on the timekeeping/scheduling module.

10. The method of claim 1, wherein the event is insertion of a new continuous analyte sensor, to eat, or to exercise.

11. The method of claim 1, wherein the output is a recommendation.

12. The method claim 11, wherein the recommendation is a therapy, to schedule a doctor'"'"'s appointment, to call a caretaker, to send data to a caretaker, to send data to a doctor, to eat a meal, to exercise, to replace a sensor, to calibrate a sensor, to check blood glucose, to upload or sync data to a cloud computing system.

13. The method of claim 1, wherein the recommendation is provided via screen prompt, text message, email message, or social network posting.

14. A machine-executed method of continuous analyte monitoring for a host to facilitate management of the host'"'"'s blood glucose level, the method comprising:

receiving a first input from an activity monitor executed by an electronic device, wherein the activity monitor provides information regarding the activity;

receiving a second input from a continuous analyte monitoring (CAM) device, wherein the CAM device measures a concentration of an analyte within the host and outputs a value that represents the host'"'"'s blood glucose level;

processing the first and second inputs, wherein correlations or impacts of the activity on the host'"'"'s blood glucose level are determined to associate the host'"'"'s blood glucose level with the activity; and

producing an output associated with the activity responsive to the determined associations.

15. The method of claim 14, wherein processing the first and second inputs comprises applying one or more algorithms to two streams of input, including algorithms useful for correlating data and/or recognizing patterns.

16. The method of claim 14, wherein the output is data that is stored locally or remotely for retrospective analysis.

17. The method claim 14, wherein the output is a warning of a low blood glucose level while the user is engaged in certain activities that might amplify a level of danger associated with the low blood glucose level, wherein the warning is distinct from a standard alert or alarm typically issued when the user is not engaged one of the certain activities.

18. The method of claim 14, wherein the output is a warning of a low blood glucose level while the user is engaged in certain activities that might amplify a level of danger associated with the low blood glucose level, wherein the warning is provided at a different blood glucose threshold than a threshold that would trigger an alert when the user is not engaged one of the certain activities.

19. A machine-executed method of continuous analyte monitoring for a host to facilitate management of the host'"'"'s blood glucose level, the method comprising:

receiving a first input from an image capture module executed by an electronic device, the first input providing information about at least one of a location, an activity, or a food;

receiving a second input from a continuous analyte monitoring (CAM) device including analyte concentration data of the host;

processing the first and second inputs by correlating information associated with the first input with the analyte concentration data of the host; and

outputting information associated with the first input.

20. The method claim 19, wherein the second input is an estimated glucose value at a time substantially corresponding to a time when the photograph was taken.