Systems, devices, and methods for meal information collection, meal assessment, and analyte data correlation

• US 10,888,272 B2
• Filed: 07/08/2016
• Issued: 01/12/2021
• Est. Priority Date: 07/10/2015
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Hayter, Gary A., Dunn, Timothy C., Crouther, Nathan
• Primary Examiner(s): Sorey, Robert A
• Assistant Examiner(s): Rapillo, Kristine K
• Application Number:
  US15/206,095
• Publication Number:
  US 20170128007A1
• Time in Patent Office: 1,649 Days
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• 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 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/6833 Adhesive patches
• CPC Class Codes: A61B 5/6849 in combination with a needle set
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G09B 19/0092 Nutrition
• CPC Class Codes: G09B 5/02 with visual presentation of the material to be studied, e.g. using film strip

Abstract

Systems, devices, and methods for detecting, measuring and classifying meals for an individual based on analyte measurements. These results and related information can be presented to the individual to show the individual which meals are causing the most severe analyte response. These results can be organized and categorized based on preselected criteria or previous meals and results so as to organize and present the results in a format with reference to glucose as the monitored analyte. Various embodiments disclosed herein relate to methods, systems, and software applications intended to engage an individual by providing direct and timely feedback regarding the individual'"'"'s meal-related glycemic response.

Claims

1. A method of processing analyte data using an in vivo analyte monitoring system comprising a sensor control device and a reader device, the method comprising:

detecting a meal event with the reader device by processing the analyte data received from the sensor control device having an in vivo analyte sensor, wherein the reader device has an adjustable sensitivity for detecting the meal event;

associating, by the reader device, meal information with a range of analyte data received from the sensor control device, the range of analyte data reflecting an analyte response of the individual to the meal;

displaying, by the reader device, information about the analyte response;

automatically determining, by the reader device, whether a sensitivity setting for detecting the meal event is either too sensitive or not sensitive enough for detecting the meal event; and

if it is determined by the reader device that the sensitivity setting is either too sensitive or not sensitive enough for detecting the meal event, then automatically adjusting, by the reader device, the sensitivity setting.

2. The method of claim 1, further comprising receiving, at the reader device, meal information from the individual.

3. The method of claim 2, further comprising determining whether the meal information received from the individual corresponds to the detected event.

4. The method of claim 2, further comprising:

prompting the individual to enter meal information about the detected event when the meal information received from the individual does not correspond to the detected event.

5. The method of claim 4, wherein prompting the individual to enter meal information about the detected event comprises prompting the individual to take the photograph of the meal with a camera application of the reader device, wherein the reader device is a smart phone.

6. The method of claim 4, wherein the meal information received from the individual further comprises a textual description of the meal.

7. The method of claim 4, wherein prompting the individual to enter meal information comprises prompting the individual to select meal information from a list of meal information options.

8. The method of claim 7, wherein the list of meal information options includes information about meals previously consumed by the individual.

9. The method of claim 8, wherein a notification that prior consumption of the selected meal resulted in an analyte excursion is immediately outputted when the individual or another user selects a meal information option that is a previously consumed meal that resulted in an analyte excursion.

10. The method of claim 1, further comprising:

detecting, with the reader device, a plurality of meal events in temporal proximity with each other;

associating, by the reader device, the plurality of meal events together as one meal cluster; and

displaying information, on the reader device, about an analyte response to the meal cluster.

11. The method of claim 10, further comprising determining if each meal event of the plurality of meal events is within a predetermined time range of another meal event of the plurality of meal events prior to associating the plurality of meal events together as one meal cluster.

12. The method of claim 11, wherein displaying information, on the reader device, about the analyte response to the meal cluster includes displaying a peak analyte value for the meal cluster.

13. The method of claim 12, further comprising determining the peak analyte value for the meal cluster by identifying the highest value in the received analyte data occurring at a time between a first meal event of the plurality of meal events to have occurred and the expiration of a predetermined time range after the last meal event of the plurality of meal events to have occurred.

18. The method of claim 1, wherein automatically determining whether a sensitivity setting for detecting the meal event is either too sensitive or not sensitive enough for detecting the meal event comprises comparing a total number of meal events with a baseline number of meal events in a day.

19. The method of claim 1, wherein the sensitivity setting is automatically adjusted with a scaling factor.

20. The method of claim 1, wherein the sensitivity setting is automatically adjusted to a next set of predetermined sensitivity settings.

14. An in vivo analyte monitoring system, comprising:

a sensor control device comprising an in vivo analyte sensor; and

a reader device comprising;

wireless communication circuitry adapted to wirelessly communicate with the sensor control device having an in vivo analyte sensor;

graphical user interface circuitry comprising a display;

processing circuitry communicatively coupled with the wireless communication circuitry; and

non-transitory memory comprising instructions stored thereon that, when executed, cause the processing circuitry to;

detect a meal event in the analyte data by analysis of the analyte data received from the sensor control device, wherein the sensitivity for the detection of the meal event is adjustable by the processor;

associate meal information with a range of analyte data received from the sensor control device, wherein the range of analyte data reflects an analyte response of the individual to the meal;

display information about the analyte response with the reader device;

automatically determine whether a sensitivity setting for detecting the meal event is either too sensitive or not sensitive enough for detecting the meal event; and

if it is determined by the reader device that the sensitivity setting is either too sensitive or not sensitive enough for detecting the meal event, then adjust the sensitivity setting.

15. The system of claim 14, wherein the non-transitory memory comprises instructions that, when executed, cause the processing circuitry to read meal information received from the individual.

16. The system of claim 15, wherein the non-transitory memory comprises instructions that, when executed, cause the processing circuitry to determine whether the meal information received from the individual corresponds to the detected event.

17. The system of claim 15, wherein the non-transitory memory comprises instructions that, when executed, cause the processing circuitry to prompt the individual to enter meal information about the detected event if the meal information received from the individual does not correspond to the detected event.