Micropressors, devices and methods for use in analyte monitoring systems

• US 20060085137A1
• Filed: 11/09/2005
• Published: 04/20/2006
• 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 7,523,004 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 signal, comprising data points, related to glucose amount or concentration in a subject, wherein said data points typically have a monotonic trend; and

evaluating said data points for one or more non-monotonic events, wherein

(i) if the data points have an acceptable monotonic trend the measurement signal is accepted for further processing, or

(ii) if the data points comprise one or more non-monotonic events then a percent contribution of said one or more non-monotonic events relative to total measurement signal is further evaluated, wherein if the percent contribution is less than a predetermined threshold value or falls within a predetermined range relative to total measurement signal then the measurement signal is accepted for further processing;

however, if the percent contribution is greater than a predetermined threshold value or falls outside a predetermined range relative to total measurement signal then the measurement signal is not accepted for further processing and the measurement signal is skipped.

2. The one or more microprocessors of claim 1, wherein said measurement signal comprising data points that typically have a monotonic trend is either a current measurement or a charge measurement.

3. An analyte monitoring system, comprising:

said one or more microprocessors of claim 1;

and

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

4. The one or more microprocessors of claim 1, wherein said data points are obtained from an electrochemical sensor.

5. The one or more microprocessors of claim 1, wherein the percent contribution of said one or more non-monotonic events relative to total measurement signal is evaluated by a method comprising using an area under an entire curve created by the data points of an overall signal and comparing a percent contribution of an area under the curve that corresponds to the contribution by said one or more non-monotonic events.

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

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

8. The analyte monitoring system of claim 7, wherein said sampling device uses a sampling method selected from the group consisting of iontophoresis, sonophoresis, microdialysis, suction, and passive diffusion.