Diagnostic methods and devices for monitoring chronic glycemia

• US 9,465,910 B2
• Filed: 05/15/2013
• Issued: 10/11/2016
• Est. Priority Date: 05/15/2012
• Status: Active Grant

• Current Assignee: Diabetes Care By Design, LLC
• Original Assignee: Alan W. Cannon, James Minor
• Inventors: Minor, James M.
• Primary Examiner(s): Lin, Jerry
• Application Number:
  US13/895,054
• Publication Number:
  US 20130311102A1
• Time in Patent Office: 1,245 Days
• Field of Search: 702/19
• US Class Current: 1/1
• CPC Class Codes: G16B 99/00 Subject matter not provided for in other groups of this subclass
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Computer apparatus, non-transitory computer readable media and methods for receiving daily vectors of measured blood glucose level values ordered by daily-defined time points over multiple days distributed over a predefined time period; calculating a vector average; calculating a chronic glycemia value based on the vector average modified by a universal term based on the centroid of an attractor basin; receiving subsequent daily vectors of blood glucose level values measured at subsequent defined time points after the predefined time period; calculating an updated vector average; calculating a subsequent chronic glycemia value based on the updated vector average modified by the universal term based on the centroid of the attractor basin estimated from the orbit; and outputting the chronic glycemia value and subsequent chronic glycemia value.

Claims

1. A computer apparatus for performing at least one of diagnosing or monitoring chronic glycemia, said apparatus comprising:

at least one processor; and

programming which, when executed by said at least one processor, performs a process including;

receiving daily vectors of measured blood glucose level values ordered by daily-defined time points over multiple days distributed over a predefined time period;

calculating a vector average from the daily vectors;

calculating a chronic glycemia value based on the vector average modified by a universal term based on the centroid of an attractor basin estimated by an orbit established by the daily vectors calculated from the blood glucose levels measured at the defined time points over multiple days distributed over the predefined time period;

receiving subsequent daily vectors of blood glucose level values measured at subsequent defined time points after the predefined time period;

calculating an updated vector average from the daily vectors and subsequent daily vectors;

calculating a subsequent chronic glycemia value based on the updated vector average modified by the universal term based on the centroid of the attractor basin estimated from the orbit; and

outputting the chronic glycemia value and subsequent chronic glycemia value to show a trend over time of chronic glycemia status.

2. The computer apparatus of claim 1, wherein said programming, when executed by said at least one processor, outputs the chronic glycemia value after said calculating a chronic glycemia value.

3. The computer apparatus of claim 1, wherein said calculating a chronic glycemia value comprises calculating the chronic glycemia value using the formula:

AG_S=offset_S+vector a*vector BG mean±

expected error;

where “

AG_S”

refers to the chronic glycemia value, * indicates a vector dot product operation, offset_S is a patient-specific constant , “

vector a”

is a vector that refers to said universal term,”

vector BG mean”

is a vector that refers to said vector average, “

S”

indexes each subject, and said expected error results from both statistical uncertainty and dynamic uncertainty of chaos theory.

4. The computer apparatus of claim 3, wherein said vector “

a”

is a two-dimensional vector comprising components “

a[1]” and

“

a[2]”

, and wherein 0<

a[1]<

0.5 and 0<

a[2]≦

0.5.

5. The computer apparatus of claim 3, wherein said vector “

a”

is a two-dimensional vector comprising components “

a[1]” and

“

a[2]”

, and wherein 0<

a[1]≦

1.0 and 0<

a[2]≦

1.0.

6. The computer apparatus of claim 3, wherein a[1]=a[2]=0.475, and expected error=±

2.910 mg/dL.

7. The computer apparatus of claim 3, wherein said expected error is less than ±

10 mg/dL (glucose/blood).

8. The computer apparatus of claim 3, wherein said expected error is about ±

2.91 mg/dL (glucose/blood).

9. The computer apparatus of claim 1, wherein said calculating a chronic glycemia value comprises calculating a relative chronic glycemia value using the formula:

AGs =vector a* vector BG mean ±

expected error;

where “

AG_S”

refers to the chronic glycemia value, * is a vector dot product, “

vector a”

is a vector that refers to said universal term, “

vector BG mean”

is a vector that refers to said vector average, “

S”

indexes each subject, and said expected error results from both statistical uncertainty and dynamic uncertainty of chaos theory.

10. The computer apparatus of claim 1 incorporated in a personal blood glucose monitor.

11. The computer apparatus of claim 1, wherein said programming, when executed by said at least one processor, calculates at least one scatter value based on a diameter of said orbit, and outputs said at least one scatter value, wherein each said at least one scatter value is calculated by averaging diameter values of said orbit over multiple adjacent time periods.

12. A chronic glycemia monitoring apparatus comprising:

a blood glucose monitoring device configured to take and output blood glucose measurements, including at least one processor;

said apparatus further comprising programming which, when executed by said at least one processor, performs a process including;

receiving daily blood glucose level values measured by said blood glucose monitoring device at daily-defined time points over multiple days distributed over a predefined time period;

calculating a daily vector of the measured blood glucose level values received for each day, respectively;

calculating a vector average from the daily vectors having been calculated;

calculating a chronic glycemia value based on the vector average modified by a universal term based on a centroid of an attractor basin defined by a vector orbit established by the blood glucose levels measured at the defined time points over multiple days distributed over the predefined time period;

receiving subsequent blood glucose level values measured by said blood glucose monitoring device on one or more days after the predefined time period;

calculating a subsequent daily vector of measured additional blood glucose level values received for each day, respectively, after the predefined time period;

calculating an updated vector average from the daily vectors and subsequent daily vectors;

calculating a subsequent chronic glycemia value based on the updated vector average modified by the universal term based on the centroid of the attractor basin estimated from the vector orbit; and

outputting the chronic glycemia value and subsequent chronic glycemia value to show a trend over time of chronic glycemia status.

13. A non-transitory computer readable medium including one or more sequences of instructions for performing chronic glycemia trending, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform a process comprising:

receiving a daily vector of measured blood glucose level values ordered by daily defined time points over multiple days distributed over a predefined time period;

calculating a vector average from the daily vectors of blood glucose levels received;

calculating a chronic glycemia value based on the vector average modified by a universal term based on a centroid of an attractor basin estimated by an orbit established by the daily vectors of the blood glucose levels measured at the defined time points over multiple days distributed over the predefined time period;

receiving at least one additional daily vector of blood glucose level values measured at additional defined time points after the predefined time period;

calculating an updated average vector blood glucose level from the daily vectors and said at least one additional daily vector;

calculating a subsequent chronic glycemia value based on the updated vector average modified by the universal term based on the centroid of the attractor basin estimated from the orbit; and

outputting the chronic glycemia value and subsequent chronic glycemia value to show a trend over time of chronic glycemia status.

14. The non-transitory computer readable medium of claim 13, further including instructions which, when executed by the one or more processors, cause the one or more processors to output the chronic glycemia value after said calculating a chronic glycemia value.

15. The non-transitory computer readable medium of claim 13, wherein said calculating a chronic glycemia value comprises calculating the chronic glycemia value using the formula:

AG_S=offset_S+a*BG mean±

expected error;

where “

AG_S”

refers to the chronic glycemia value, * indicates a vector dot product operation, offset_S is a patient-specific constant “

a”

is a vector that refers to said universal term, “

BG mean”

is a vector that refers to said vector average, “

S”

indexes each subject, and said expected error results from both statistical uncertainty and dynamic uncertainty of chaos theory.

16. The non-transitory computer readable medium of claim 15, wherein said vector “

a”

is a two-dimensional vector comprising components “

a[1]” and

“

a[2]”

, and wherein 0<

a[1]≦

0.5 and 0<

a[2]≦

0.5.

17. The non-transitory computer readable medium of claim 15, wherein said expected error is less than ±

8 mg/dL (glucose/blood).

18. The non-transitory computer readable medium of claim 15, wherein said expected error is about ±

2.910 mg/dL (glucose/blood).

19. The non-transitory computer readable medium of claim 13, further including instructions which, when executed by the one or more processors, cause the one or more processors to calculate at least one scatter value based on a diameter variation of said orbit over time, and output said at least one scatter value.

20. A method for tracking chronic glycemia, said method comprising:

receiving a daily vector of measured blood glucose level values ordered by daily defined time points over multiple days distributed over a predefined time period;

calculating a vector average from the blood glucose levels received over multiple days;

calculating a chronic glycemia value based on the vector average modified by a universal term based on a centroid of an attractor basin estimated by an orbit established by the vectors of the blood glucose levels measured at the defined time points over multiple days distributed over the predefined time period;

receiving at least one additional daily vector of blood glucose level values measured at additional defined time points after the predefined time period;

calculating an updated vector average from the blood glucose levels and the additional blood glucose levels received;

calculating a subsequent chronic glycemia value based on the updated vector average modified by the universal term based on the centroid of the attractor basin estimated by the orbit; and

outputting the chronic glycemia value and subsequent chronic glycemia value to show a trend over time of chronic glycemia status.

21. The method of claim 20, wherein said calculating a chronic glycemia value comprises calculating the chronic glycemia value using the formula:

AG_S=offset_S+vector a*vector BG mean±

expected error;

where “

AG_S”

refers to the chronic glycemia value, * indicates a vector dot product operation, offset_S is a patient-specific constant “

vector a”

is a vector that refers to said universal term, “

vector BG mean”

is a vector that refers to said vector average, “

S”

indexes each subject, and said expected error results from both statistical uncertainty and dynamic uncertainty of chaos theory.

22. The method of claim 21, wherein said expected error is less than ±

10 mg/dL (glucose/blood).

23. The method of claim 20, further comprising calculating at least one scatter value based on a diameter change of said orbit.