Micropressors, devices and methods for use in analyte monitoring systems

• US 7,523,004 B2
• Filed: 11/09/2005
• Issued: 04/21/2009
• 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.
• Primary Examiner(s): Brusca; John S
• Application Number:
  US11/270,857
• Publication Number:
  US 20060085137A1
• Time in Patent Office: 1,259 Days
• Field of Search: None
• 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. A method of obtaining an analyte value in biological fluid of a user with an analyte sensor having two electrode sets coupled to a microprocessor, the method comprising:

providing a plurality of data points via the microprocessor by;

contacting the two electrode sets with biological fluid of a user, in which each electrode set includes an iontophoretic electrode and an electrochemical sensor element in contact with the biological fluid and each of the two iontophoretic electrodes function as either a cathode or anode while in contact with the fluid;

measuring a total signal from the sensor element associated with the iontophoretic electrodes;

extracting a signal from the total signal related to the analyte from the sensor element associated with the iontophoretic electrodes to provide the plurality of data points;

evaluating said data points, via the microprocessor for one or more non-monotonic events and (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, and 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 unless 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 skipped;

integrating, via the microprocessor, the signal related to the analyte over time to obtain a charge signal as being proportional to a value of the analyte; and

displaying, via the microprocessor, the analyte value of the biological fluid of the user for diagnostic purposes.

2. The method of claim 1, in which the data points that have a monotonic trend comprises one of a current measurement or a charge measurement.

3. The method of claim 1, in which 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.

4. The method of claim 1, in which said measurement signal comprises a one of either a current measurement or a charge measurement and the analyte comprises glucose.

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