Method and device for predicting physiological values

• US 6,272,364 B1
• Filed: 05/11/1999
• Issued: 08/07/2001
• Est. Priority Date: 05/13/1998
• Status: Expired due to Term

• Current Assignee: LifeScan IP Holdings, LLC
• Original Assignee: Cygnus, Inc. (Johnson & Johnson)
• Inventors: Kurnik, Ronald T.
• Primary Examiner(s): Lacyk, John P.
• Assistant Examiner(s): CARTER, RYAN CHRISTOPHER
• Application Number:
  US09/309,720
• Time in Patent Office: 819 Days
• Field of Search: 600/300, 600/309, 600/310, 600/322, 600/345, 600/347, 600/365, 600/573, 600/575, 600/549, 600/395-396, 600/372, 600/393, 600/386, 607/115, 607/148-149
• US Class Current: 600/345
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement

Abstract

A method and device are provided for measuring the concentration of target chemical analytes present in a biological system, and then predicting a future or past concentration of an analyte using a series of such measurements. One important application of the invention involves predicting future or past blood glucose concentrations using a series of measured blood glucose values.

Claims

1. A method for measuring an analyte present in a biological system, said method comprising:

(a) transdermally extracting the analyte from the biological system using a sampling system that is in operative contact with a skin or mucosal surface of said biological system;

(b) obtaining a raw signal from the extracted analyte, wherein said raw signal is specifically related to the analyte;

(c) performing a calibration step which correlates the raw signal obtained in step (b) with a measurement value indicative of the concentration of analyte present in the biological system at the time of extraction;

(d) repeating steps (a)-(b) to obtain a series of measurement values at selected time intervals, wherein the sampling system is maintained in operative contact with the skin or mucosal surface of said biological system to provide for analyte measurement; and

(e) predicting a measurement value at a further time interval which occurs either one time interval before or one time interval after the series of measurement values is obtained in step (d).

2. The method of claim 1, wherein the selected time intervals are evenly spaced.

3. The method of claim 1, wherein the series of measurement values obtained in step (d) is comprised of three or more discrete values.

4. The method of claim 3, wherein the further time interval occurs one time interval after the series of measurement values is obtained in step (d).

5. The method of claim 3, wherein the further time interval occurs one time interval before the series of measurement values is obtained in step (d).

6. The method of claim 3, wherein the prediction of step (e) is carried out using said series of three or more measurement values in a series function represented by:

$\begin{array}{cc}{y}_{n+1}=y_n+\mathrm{\alpha <br><br>}<br><br>\left(y_n-y_{n-1}\right)+\frac{{\mathrm{\alpha <br><br>}}^2}{2}<br><br>\left(y_n-2<br><br>y_{n-1}+y_{n-2}\right)& \left(7\right)\end{array}$

wherein y is the measurement value of the analyte, n is the time interval between measurement values, and α

is a real number between 0 and 1.

7. The method of claim 6, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval after the series of measurement values is obtained.

8. The method of claim 6, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval before the series of measurement values is obtained.

9. The method of claim 8, further comprising the step of taking a reference analyte measurement at the time interval n+1.

10. The method of claim 1, wherein the analyte is extracted from the biological system in step (a) into a collection reservoir to obtain a concentration of the analyte in said reservoir.

11. The method of claim 10, wherein the collection reservoir is in contact with the skin or mucosal surface of the biological system and the analyte is extracted using an iontophoretic current applied to said skin or mucosal surface.

12. The method of claim 11, wherein the collection reservoir contains an enzyme that reacts with the extracted analyte to produce an electrochemically detectable signal.

13. The method of claim 12, wherein the analyte is glucose and the enzyme is glucose oxidase.

14. The method of claim 13, wherein the series of measurement values obtained in step (d) is comprised of three or more discrete blood glucose values.

15. The method of claim 14, wherein the further time interval occurs one time interval after the series of measurement values is obtained in step (d).

16. The method of claim 14, wherein the further time interval occurs one time interval before the series of measurement values is obtained in step (d).

17. The method of claim 14, wherein the prediction of step (e) is carried out using said series of three or more measurement values in a series function represented by:

$\begin{array}{cc}{y}_{n+1}=y_n+\mathrm{\alpha <br><br>}<br><br>\left(y_n-y_{n-1}\right)+\frac{{\mathrm{\alpha <br><br>}}^2}{2}<br><br>\left(y_n-2<br><br>y_{n-1}+y_{n-2}\right)& \left(7\right)\end{array}$

wherein y is the measurement value of blood glucose, n is the time interval between measurement values, and a is a real number between 0 and 1.

18. The method of claim 17, wherein the series function is used to predict the value of y_n+1, and the time interval n+1 occurs one time interval after the series of measurement values is obtained.

19. The method of claim 18, wherein the predicted value of y_n+1 is used to control administration of insulin to the biological system from an associated insulin pump.

20. The method of claim 17, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval before the series of measurement values is obtained.

21. The method of claim 20, further comprising the step of taking a reference blood glucose measurement from the biological system at the time interval n+1.

22. The method of claim 21, wherein the reference blood glucose measurement is compared against the predicted value of y_n+1 and used to calibrate the sampling device.

23. A method for measuring blood glucose in a subject, said method comprising:

(a) operatively contacting a glucose sensing apparatus with the subject to detect blood glucose;

(b) obtaining a raw signal from the sensing apparatus, wherein said raw signal is specifically related to the glucose detected by the sensing apparatus;

(c) performing a calibration step which correlates the raw signal obtained in step (b) with a measurement value indicative of the subject'"'"'s blood glucose concentration;

(d) repeating steps (a)-(b) to obtain a series of measurement values at selected time intervals; and

(e) predicting a measurement value at a further time interval which occurs either one time interval before or one time interval after the series of measurement values is obtained in step (d).

24. The method of claim 23, wherein the sensing means comprises an enzyme that reacts with the glucose to produce an electrochemically detectable signal.

25. The method of claim 24, wherein the enzyme is glucose oxidase.

26. The method of claim 23, wherein the sensing apparatus is a near-IR spectrometer.

27. The method of claim 23, wherein the selected time intervals are evenly spaced.

28. The method of claim 23, wherein the series of measurement values obtained in step (d) is comprised of three or more discrete values.

29. The method of claim 28, wherein the further time interval occurs one time interval after the series of measurement values is obtained in step (d).

30. The method of claim 28, wherein the further time interval occurs one time interval before the series of measurement values is obtained in step (d).

31. The method of claim 28, wherein the prediction of step (e) is carried out using said series of three or more measurement values in a series function represented by:

$\begin{array}{cc}{y}_{n+1}=y_n+\mathrm{\alpha <br><br>}<br><br>\left(y_n-y_{n-1}\right)+\frac{{\mathrm{\alpha <br><br>}}^2}{2}<br><br>\left(y_n-2<br><br>y_{n-1}+y_{n-2}\right)& \left(7\right)\end{array}$

wherein y is the measurement value of the analyte, n is the time interval between measurement values, and α

is a real number between 0 and 1.

32. The method of claim 31, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval after the series of measurement values is obtained.

33. The method of claim 31, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval before the series of measurement values is obtained.

34. The method of claim 33, further comprising the step of taking a reference analyte measurement at the time interval n+1.

35. A monitoring system for measuring an analyte present in a biological system, said system comprising, in operative combination:

(a) sampling means for extracting the analyte from the biological system, wherein said sampling means is adapted for extracting the analyte across a skin or mucosal surface of said biological system;

(b) sensing means in operative contact with the analyte extracted by the sampling means, wherein said sensing means obtains a raw signal from the extracted analyte and said raw signal is specifically related to the analyte; and

(c) microprocessor means in operative communication with the sampling means and the sensing means, wherein said microprocessor means (i) is used to control the sampling means and the sensing means to obtain a series of raw signals at selected time intervals during a measurement period, (ii) correlate the raw signals with measurement values indicative of the concentration of analyte present in the biological system, and (iii) predict a measurement value at a further time interval which occurs either one time interval before or one time interval after the series of measurement values is obtained.

36. The monitoring system of claim 35, wherein the sensing means comprises a near-IR spectrometer.

37. The monitoring system of claim 35, wherein the measurement values comprise a series of measurement values comprising three or more discrete values.

38. The monitoring system of claim 37, wherein the further time interval occurs one time interval after the series of measurement values.

39. The monitoring system of claim 37, wherein the further time interval occurs one time interval before the series of measurement values.

40. The monitoring system of claim 37, wherein the prediction of (c)(iii) is carried out using said series of three or more measurement values in a series function represented by:

$\begin{array}{cc}{y}_{n+1}=y_n+\mathrm{\alpha <br><br>}<br><br>\left(y_n-y_{n-1}\right)+\frac{{\mathrm{\alpha <br><br>}}^2}{2}<br><br>\left(y_n-2<br><br>y_{n-1}+y_{n-2}\right)& \left(7\right)\end{array}$

wherein y is the measurement value of the analyte, n is the time interval between measurement values, and α

is a real number between 0 and 1.

41. The monitoring system of claim 40, wherein the series function is used to predict the value of y_n+1, and the time interval n+1 occurs one time interval after the series of measurement values is obtained.

42. The monitoring system of claim 40, wherein the series function is used to predict the value of y_n+1 and the time interval n+1 occurs one time interval before the series of measurement values is obtained.

43. The monitoring system of claim 35, wherein the sampling means includes one or more collection reservoirs for containing the extracted analyte.

44. The monitoring system of claim 35, wherein the sampling means uses an iontophoretic current to extract the analyte from the biological system.

45. The monitoring system of claim 44, wherein the collection reservoir contains an enzyme that reacts with the extracted analyte to produce an electrochemically detectable signal.

46. The monitoring system of claim 45, wherein the analyte is glucose and the enzyme is glucose oxidase.