Micropressors, devices and methods for use in analyte monitoring systems

• US 20060074564A1
• Filed: 11/09/2005
• Published: 04/06/2006
• Est. Priority Date: 03/22/2002
• Status: Active Grant

• Current Assignee: LifeScan IP Holdings, LLC
• Original Assignee: Animas Technologies LLC (Johnson & Johnson)
• Inventors: Tamada, Janet A., Bartkowiak, Miroslaw, Kulcu, Eray, Harper, Wesley S., Lesho, Matthew J.
• Granted Patent: US 7,711,493 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7242 using integration
• CPC Class Codes: G01N 27/3271 Amperometric enzyme electrodes for analytes in body fluids, e.g. glucose in blood amperometry per se G01N27/49; aspects concerning the enzyme reagent C12Q1/001
• CPC Class Codes: Y10T 436/144444 Glucose

Abstract

The present invention comprises one or more microprocessors programmed to execute methods for improving the performance of an analyte monitoring device including prediction of glucose levels in a subject by utilizing a predicted slower-time constant (1/k₂). In another aspect of the invention, pre-exponential terms (1/c₂) can be used to provide a correction for signal decay (e.g., a Gain Factor). In other aspects, the present invention relates to one or more microprocessors comprising programming to control execution of (i) methods for conditional screening of data points to reduce skipped measurements, (ii) methods for qualifying interpolated/extrapolated analyte measurement values, (iii) various integration methods to obtain maximum integrals of analyte-related signals, as well as analyte monitoring devices comprising such microprocessors. Further, the present invention relates to algorithms for improved optimization of parameters for use in prediction models that require optimization of adjustable parameters.

Claims

1. One or more micropressors, comprising programming to control:

providing a measurement value related to glucose amount or concentration in a subject, and two or more data integrity screens associated with said glucose measurement value; and

(A) accepting said measurement value when either (i) said two or more data integrity screens fall within predetermined acceptable ranges or within predetermined threshold values, or (ii) a first data integrity screen of said two or more data integrity screens falls outside of predetermined acceptable range or beyond predetermined threshold value and at least a second data integrity screen of said two or more data integrity screens falls within predetermined acceptable ranges or within predetermined threshold values, or

(B) skipping said measurement value when two or more of said two or more data integrity screens falls outside of predetermined acceptable ranges or beyond predetermined threshold values.

2. The one or more micropressors of claim 1, wherein at lease one or said two or more data integrity screens are selected from the group consisting of peak sensor current, skin conductivity, sensor current, iontophoretic voltage, subject temperature, analyte monitoring device operating temperature, and background current.

3. An analyte monitoring system comprising, said one or more microprocessors of claim 1;

and

a sensing device used to provide said measurement value related to glucose amount or concentration.

4. The one or more microprocessors of claim 1, wherein said measurement value comprises one or more data points related to a measurement value at a given time point.

5. The one or more microprocessors of claim 4, wherein said measurement value comprises an electrochemical signal from a biosensor.

6. The one or more microprocessors of claim 5, wherein one of said two or more data integrity screens relates to non-monotonicity of the electrochemical signal from the biosensor.

7. The one or more microprocessors of claim 1, wherein said first data integrity screen is a skin conductance value associated in time with said glucose measurement value.

8. The one or more microprocessors of claim 7, wherein said skin conductance value is represented as an absolute value.

9. The one or more microprocessors of claim 1, further comprising equal weighting of all of said two or more data integrity screens for determination of said accepting or skipping.

10. The one or more microprocessors of claim 1, further comprising different weighting of one or more of said two or more data integrity screens for determination of said accepting or skipping.

11. The one or more microprocessors of claim 1, wherein providing the measurement value related to glucose amount or concentration in a subject comprises employing iontophoretic extraction of glucose from the subject followed by electrochemical detection of the glucose amount or concentration.

12. The one or more microprocessors of claim 1, wherein providing the measurement value related to glucose amount or concentration in a subject comprises use of a subcutaneous sensor.

13. The one or more microprocessors of claim 12, wherein at least one of said two or more data integrity screens are selected from the group consisting of temperature of the subject, peak sensor signal, and trend analysis of data.

14. The analyte monitoring system of claim 3, wherein said sensing device uses electrochemical detection.

15. The analyte monitoring system of claim 3, further comprising a sampling device.

16. The analyte monitoring system of claim 15, wherein said sampling device uses a sampling method selected from the group consisting of iontophoresis, sonophoresis, microdialysis, suction, and passive diffusion.