Software applications residing on handheld analyte determining devices

• US 9,913,599 B2
• Filed: 12/21/2011
• Issued: 03/13/2018
• Est. Priority Date: 02/11/2011
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Bernstein, Daniel M., Bradrick, Brittany K., Budiman, Erwin S., Davis, Eric, Dunn, Timothy C., Gopal, Mani, Harper, Wesley S., Hayter, Gary A., Scott, Steve, Winkler, Todd, Wolpert, Howard
• Primary Examiner(s): Riggs, II, Larry D
• Application Number:
  US13/984,815
• Publication Number:
  US 20140088393A1
• Time in Patent Office: 2,274 Days
• Field of Search: None
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

Presented herein is a handheld analyte measurement device. The analyte measurement device includes one or more software applications to help the user manager their diabetes. Embodiments and descriptions of the various applications are provided below in conjunction with the handheld analyte measurement device.

Claims

1. A diabetes management system for optimizing the amount of recoverable historical information and minimizing the amount of data stored therein, the system comprising:

an analyte measurement device having one or more computer-readable storage medium having instructions executable by at least one processing device that, when executed, cause the processing device to determine a data storage schedule based on instantaneous glucose information and glucose rate of change information, wherein the instructions to determine the data storage schedule comprise instructions to;

receive and store a first glucose measurement;

determine a glucose rate of change based in part upon the first glucose measurement;

determine an estimated time interval based, at least, on when a glucose concentration will change by a predetermined amount from the first glucose measurement; and

after waiting the estimated time interval, receive and store a second glucose measurement.

2. The diabetes management system of claim 1, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to place at least one of an upper limit and a lower limit on the estimated time interval.

3. The diabetes management system of claim 1, wherein the estimated time interval is further determined based on historical patient glucose data.

4. The diabetes management system of claim 3, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to utilize an AutoRegressive (AR) model.

5. The diabetes management system of claim 3, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to utilize polynomial fitting.

6. The diabetes management system of claim 1, wherein the estimated time interval is further determined based on historical patient glucose data and additional information selected from insulin, exercise or other diabetes relevant parameters.

7. The diabetes management system of claim 6, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to utilize an AutoRegressive with exogenous input (ARX) model.

8. The diabetes management system of claim 6, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to utilize a physiology-based glucoregulatory model.

9. The diabetes management system of claim 8, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to utilize a Kalman Filter.

10. The diabetes management system of claim 1, wherein the instructions executable by the at least one processing device, when executed, cause the processing device to shorten the estimated time interval when an erroneous glucose measurement is detected.