Methods for improving the performance of an analyte monitoring system

• US 20030050546A1
• Filed: 06/21/2002
• Published: 03/13/2003
• Est. Priority Date: 06/22/2001
• Status: Active Grant

• Current Assignee: LifeScan IP Holdings, LLC
• Original Assignee: Animas Technologies LLC (Johnson & Johnson)
• Inventors: Potts, Russell O., Tamada, Janet A., Dunn, Timothy C., Desai, Shashi P., Lesho, Matthew J., Wei, Charles W.
• Granted Patent: US 7,011,630 B2
• Time in Patent Office: Days
• US Class Current: 600/347
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1477 non-invasive
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61N 1/30 Apparatus for iontophoresis, i.e. transfer of media in ionic state by an electromotoric force into the body, or cataphoresis

Abstract

The present invention relates to methods to increase the number of analyte-related signals used to provide analyte measurement values, e.g., when two or more analyte-related signals are used to obtain a single analyte measurement value a “rolling” value based on the two or more signals can be employed. In another aspect, interpolation and/or extrapolation methods are used to estimate unusable, missing or error-associated analyte-related signals. Further, interpolation and extrapolation of values are employed in another aspect of the invention that reduces the incident of failed calibrations. Further, the invention relates to methods, which employ gradients and/or predictive algorithms, to provide an alert related to analyte values exceeding predetermined thresholds. The invention includes the above-described methods, one or more microprocessors programmed to execute the methods, one or more microprocessors programmed to execute the methods and control at least one sensing and/or sampling device, and monitoring systems employing the methods described herein.

Claims

1. A method of increasing the number of analyte measurement values related to the amount or concentration of an analyte in a subject as measured using an analyte monitoring device, said method comprising

providing a series of analyte-related signals obtained from the analyte monitoring device over time, wherein (i) two or more contiguous analyte-related signals are used to obtain a single analyte measurement value (M), (ii) analyte-related signals are not used to calculate more than one analyte measurement value, and (iii) said two or more contiguous analyte-related signals, used to obtain the single analyte measurement value, comprise first and last analyte-related signals of the series;

mathematically computing rolling analyte measurement values, wherein (i) each rolling analyte measurement value is calculated based on two or more contiguous analyte-related signals from the series of analyte-related signals obtained from the analyte monitoring device, (ii) a subsequent rolling analyte measurement value is mathematically computed by dropping said first analyte-related signal and including an analyte-related signal contiguous and subsequent to the last analyte-related signal, (iii) further rolling analyte measurement values are obtained by repeating the dropping of the first analyte-related signal used to calculate the previous rolling analyte measurement and including an analyte-related signal contiguous and subsequent to the last analyte-related signal used to calculate the previous rolling analyte measurement, and (iv) each rolling analyte measurement value provides a measurement related to the amount or concentration of analyte in the subject; and

increasing the number of analyte measurement values derived from the analyte-related signals in the series of analyte-related signals obtained from the analyte monitoring device by serially calculating rolling analyte measurement values, thereby increasing the number of analyte measurement values.

2. The method of claim 1, wherein said rolling analyte measurement value is an average of two or more analyte-related signals.

3. The method of claim 1, wherein said rolling analyte measurement value is a sum of two or more analyte-related signals.

4. The method of claim 1, wherein each analyte-related signal is represented by an integral over time, and said rolling analyte measurement value is obtained by integral splitting.

5. The method of claim 1, wherein said monitoring device comprises a sampling device and a sensing device, and wherein said providing the series of analyte-related signals obtained from an analyte monitoring device comprises

extracting a sample from the subject alternately into a first collection reservoir and then into a second collection reservoir using the sampling device, wherein (i) each sample comprises the analyte, and (ii) said sampling device comprises said first and second collection reservoirs;

and

sensing the analyte in each extracted sample to obtain a signal from each sample that is related to the analyte amount or concentration in the subject, thus providing a series of analyte-related signals, said sensing device comprising first and second sensors, wherein said first sensor is in operative contact with said first collection reservoir and said sensing provides signal S^A_J (where S^A is the signal from sensor A, j is the time interval), the second sensor is in operative contact with the second collection reservoir and said sensing provides signal S^B_J+1 (where S^B is the signal from sensor B, j+1 is the time interval), and an analyte measurement value is obtained using analyte-related signal from sensor A and sensor B.

6. The method of claim 5, wherein said rolling analyte measurement values are calculated as follows:

(average signal)_J=(S^B<sub>J−

1</sub>+S^A_j)/2,  

 

Eqn. 1 (average signal)_J+1=(S^A_j+S^B_j+1)/2;

 

 

Eqn. 2 (average signal)_J+2=(S^B_J+1+S^A_J+2)/2;

etc.,  

 

Eqn. 3

wherein (i) (j−

1) is the measurement half-cycle previous to j, and (j+2) is two measurement half-cycles after j, and (ii) each average signal corresponds to a rolling analyte measurement value.

7. The method of claim 5, wherein said rolling analyte measurement values are calculated as follows:

(summed signal)_J=(S^B<sub>j−

1</sub>+S^A_j);

 

 

Eqn. 4 (summed signal)_j+1=(S^A_j+S^B_j+1); and

 

 

Eqn. 5 (summed signal)_j+2=(S^B_j+1+S^A_j+2);

etc.  

 

Eqn. 6

where (j−

1) is the measurement half-cycle previous to j, and (j+2) is two measurement half-cycles after j; and

(ii) each summed signal corresponds to a rolling analyte measurement value.

8. The method of claim 1, wherein a missing or error-associated signal in the series of analyte-related signals obtained from the analyte monitoring device is estimated using interpolation before mathematically computing rolling analyte measurement values.

9. The method of claim 1, wherein a missing or error-associated signal in the series of analyte-related signals obtained from the analyte monitoring device is estimated using extrapolation before mathematically computing rolling analyte measurement values.

10. The method of claim 1, wherein said analyte is glucose.

11. The method of claim 10, wherein said analyte monitoring device comprises (i) an iontophoretic sampling device, and (ii) an electrochemical sensing device.

12. The method of claim 11, wherein said analyte-related signal is a current or a charge related to amount or concentration of analyte in the subject.

13. The method of claim 1, wherein one or more microprocessors are utilized to mathematically compute rolling analyte measurement values.

14. The method of claim 13, wherein said one or more microprocessors further control components of the analyte monitoring system.

15. The method of claim 14, wherein said analyte monitoring system comprises at least one sampling device and at least one sensing device.

16. The method of claim 15, wherein said one or more microprocessors control obtaining samples from the subject and sensing analyte concentration in each obtained sample to provide the series of analyte-related signals.

17. One or more microprocessors programmed to control:

mathematical computations of rolling analyte measurement values, wherein (i) each rolling analyte measurement value is calculated based on two or more contiguous analyte-related signals from a series of analyte-related signals obtained from an analyte monitoring device, (ii) said series of analyte-related signals is obtained from the analyte monitoring device over time, wherein (a) two or more contiguous analyte-related signals are used to obtain a single analyte measurement value (M), (b) analyte-related signals are not used to calculate more than one analyte measurement value, and (c) said two or more contiguous analyte-related signals, used to obtain the single analyte measurement value, comprise first and last analyte-related signals of the series, (iii) a subsequent rolling analyte measurement value is mathematically computed by dropping said first analyte-related signal and including an analyte-related signal contiguous and subsequent to the last analyte-related signal, (iv) further rolling analyte measurement values are obtained by repeating the dropping of the first analyte-related signal used to calculate the previous rolling analyte measurement and including an analyte-related signal contiguous and subsequent to the last analyte-related signal used to calculate the previous rolling analyte measurement, and (v) each rolling analyte measurement value provides a measurement related to the amount or concentration of analyte in the subject; and

increases of the number of analyte measurement values derived from the analyte-related signals in the series of analyte-related signals obtained from the analyte monitoring device by serially calculating rolling analyte measurement values.

18. The one or more microprocessors of claim 17, wherein said analyte monitoring device comprises at least one sensing device and said one or more microprocessors are further programmed to control operation of said sensing devices.

19. The one or more microprocessors of claim 18, wherein said analyte monitoring device further comprises at least one sampling device and said one or more microprocessors are further programmed to control operation of said sampling devices.

20. An analyte monitoring device comprising:

a sensing device; and

one or more microprocessor programmed to control operation of said sensing device and said one or more microprocessor programmed to control mathematical computations of rolling analyte measurement values, wherein (i) each rolling analyte measurement value is calculated based on two or more contiguous analyte-related signals from a series of analyte-related signals obtained from an analyte monitoring device, (ii) said series of analyte-related signals is obtained from the analyte monitoring device over time, wherein (a) two or more contiguous analyte-related signals are used to obtain a single analyte measurement value (M), (b) analyte-related signals are not used to calculate more than one analyte measurement value, and (c) said two or more contiguous analyte-related signals, used to obtain the single analyte measurement value, comprise first and last analyte-related signals of the series, (iii) a subsequent rolling analyte measurement value is mathematically computed by dropping said first analyte-related signal and including an analyte-related signal contiguous and subsequent to the last analyte-related signal, (iv) further rolling analyte measurement values are obtained by repeating the dropping of the first analyte-related signal used to calculate the previous rolling analyte measurement and including an analyte-related signal contiguous and subsequent to the last analyte-related signal used to calculate the previous rolling analyte measurement, and (v) each rolling analyte measurement value provides a measurement related to the amount or concentration of analyte in the subject; and

increase of the number of analyte measurement values derived from the analyte-related signals in the series of analyte-related signals obtained from the analyte monitoring device by serially calculating rolling analyte measurement values.

21. The analyte monitoring device of claim 20, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control the operation of said sampling device.

22. A method of replacing unusable analyte-related signals when employing an analyte monitoring device to measure an analyte amount or concentration in a subject, said method comprising

providing a series of analyte-related signals obtained from the analyte monitoring device over time, wherein each analyte-related signal is related to the amount or concentration of analyte in the subject;

and

replacing an unusable analyte-related signal with an estimated signal by either;

(A) if one or more analyte-related signals previous to the unusable analyte-related signal and one or more analyte-related signals subsequent to the unusable analyte related signal are available, then interpolation is used to estimate the unusable, intervening analyte-related signal;

or

(B) if two or more analyte-related signals previous to the unusable analyte-related signal are available, then extrapolation is used to estimate the unusable, subsequent analyte-related signal.

23. The method of claim 22, wherein said analyte monitoring device comprises one or more sensor devices and a relationship between the signals obtained from the different sensor devices is used in interpolation and/or extrapolation calculation of estimated values.

24. The method of claim 23, wherein said sensor device comprises two sensor elements and a ratio of signals obtained from a first sensor relative to a second sensor is employed in interpolation and/or extrapolation calculation of estimated signal values.

25. The method of claim 22, said analyte monitoring device comprising a sampling device and a sensing device, said providing the series of analyte-related signals obtained from an analyte monitoring device comprising

extracting a sample from the subject alternately into a first collection reservoir and then into a second collection reservoir using the sampling device, wherein (i) each sample comprises the analyte, and (ii) said sampling device comprises said first and second collection reservoirs;

and

sensing the analyte in each extracted sample to obtain a signal from each sample that is related to the analyte amount or concentration in the subject, thus providing a series of analyte-related signals, said sensing device comprising first and second sensors, wherein said first sensor is in operative contact with said first collection reservoir and said sensing provides signal S^A_J (where S^A is the signal from sensor A, j is the time interval), the second sensor is in operative contact with the second collection reservoir and said sensing provides signal S^B_j+1 (where S^B is the signal from sensor B, j+1 is the time interval), and an analyte measurement value is obtained using analyte-related signal from sensor A and sensor B.

26. The method of claim 25, wherein said analyte monitoring device comprises two sensors and a relationship between the signals obtained from the different sensors is used in interpolation and/or extrapolation calculation of estimated values.

27. The method of claim 26, wherein said relationship between the signals from the different sensors is a smoothed ratio of the form:

R^S₁=wR₁+(1-−

w)R^S<sub>l−

1</sub>  

 

Eqn. 10

wherein, R₁ is the A/B or B/A signal ratio for a i^th measurement cycle, R^S_i is smoothed R for a i^th measurement cycle, and w is a smoothing factor and is represented by a fraction between and inclusive of 0 through 1, and R^S<sub>i−

1</sub> is a smoothed ratio for the (i−

1)^th measurement cycle, wherein the i^th measurement cycle is composed of first and second half-cycles and the second half-cycle value of the i^th measurement cycle precedes S_j.

28. The method of claim 27, wherein a smoothed A/B ratio and a smoothed B/A ratio are employed, and said ratios are as follows:

29. The method of claim 28, wherein said analyte is glucose.

30. The method of claim 28, for interpolation in the situation where both S_j and S_J+2 are signals from the B sensor (S^B_j and S^B_J+2), and S_J+1 is being estimated for the A sensor signal (S^AE_j+1), interpolation Eqn. 7A is employed as follows:

31. The method of claim 28, for interpolation in the situation where both S_J and S_J+2 are signals from the A sensor (S^A_J and S^A_j+2), and S_J+1 is being estimated for the B sensor signal (S^BE_J+1), interpolation Eqn. 7C is employed as follows:

32. The method of claim 28, for extrapolation in the situation where S_J is signal from sensor A (S^A_J) and S_J+1 is signal from B sensor (S^B_J+1), and S_j+2 is being estimated for the A sensor signal (S^AE_j+2), extrapolation Eqn. 8A is employed as follows:

33. The method of claim 28, for extrapolation in the situation where S_J is signal from the B sensor (S^B_J) and S_j+1 is signal from the A sensor (S^A_j+1), and S_j+2 is being estimated for the B sensor signal (S^BE_j+2), extrapolation Eqn. 8C is employed as follows:

34. The method of claim 22, wherein said analyte is glucose.

35. The method of claim 34, wherein said analyte monitoring device comprises (i) an iontophoretic sampling device, and (ii) an electrochemical sensing device.

36. The method of claim 35, wherein said analyte-related signal is a current or a charge related to analyte amount or concentration of analyte in the subject.

37. The method of claim 22, wherein one or more microprocessors are utilized to mathematically compute said estimated signal.

38. The method of claim 37, wherein said one or more microprocessors further control components of the analyte monitoring system.

39. The method of claim 38, wherein said analyte monitoring system comprises a sampling device and a sensing device.

40. The method of claim 39, wherein said one or more microprocessors control obtaining samples from the subject and sensing analyte concentration in each obtained sample to provide the series of analyte-related signals.

41. One or more microprocessors programmed to control:

replacement, in a series of analyte-related signals, of an unusable analyte-related signal with an estimated signal by either;

(A) if one or more analyte-related signals previous to the unusable analyte-related signal and one or more analyte-related signals subsequent to the unusable analyte related signal are available, then interpolation is used to estimate the unusable, intervening analyte-related signal;

or

(B) if two or more analyte-related signals previous to the unusable analyte-related signal are available, then extrapolation is used to estimate the unusable, subsequent analyte-related signal;

wherein said series of analyte-related signals is obtained from an analyte monitoring device over time, and each analyte-related signal is related to an amount or concentration of analyte in a subject being monitored with the analyte monitoring device.

42. The one or more microprocessors of claim 41, wherein said analyte monitoring device comprises a sensing device and said one or more microprocessors are further programmed to control operation of said sensing device.

43. The one or more microprocessors of claim 42, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control operation of said sampling device.

44. An analyte monitoring device comprising:

a sensing device; and

one or more microprocessor programmed to control operation of said sensing device and said one or more microprocessor programmed to control replacement, in a series of analyte-related signals, of an unusable analyte-related signal with an estimated signal by either;

(A) if one or more analyte-related signals previous to the unusable analyte-related signal and one or more analyte-related signals subsequent to the unusable analyte related signal are available, then interpolation is used to estimate the unusable, intervening analyte-related signal;

or

(B) if two or more analyte-related signals previous to the unusable analyte-related signal are available, then extrapolation is used to estimate the unusable, subsequent analyte-related signal;

wherein said series of analyte-related signals is obtained from an analyte monitoring device over time, and each analyte-related signal is related to an amount or concentration of analyte in a subject being monitored with the analyte monitoring device.

45. The analyte monitoring device of claim 44, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control the operation of said sampling device.

46. A method for reducing the incidence of failed calibration for an analyte monitoring system that is used to monitor an amount or concentration of analyte present in a subject, wherein the analyte monitoring system provides a series of signals or measurement values, said method comprising:

sensing the analyte in each of a series of samples to obtain an analyte-related signal from each sample that is related to the analyte amount or concentration in the subject, thus providing a series of analyte-related signals, said sensing device comprising a first sensor (A) and second sensor (B), wherein (1) said first sensor (A) is in operative contact with a first collection reservoir and said second sensor (B) is in operative contact with a second collection reservoir, and (2) two consecutive analyte-related signals comprise a measurement cycle, and each of the two consecutive analyte-related signals is half-cycle analyte-related signal; and

performing a calibration method to relate analyte amount or concentration in the subject to analyte-related signals obtained from the sensors, said calibration method comprising;

(i) obtaining a first half-cycle analyte-related signal S_j, wherein a second half-cycle analyte-related signal S_j+1, or an estimate thereof, and a third half-cycle analyte-related signal S_j+2, or an estimate thereof, are both used in the calibration method so that the sensor analyte-related signals correlate to the analyte amount or concentration in the subject, wherein the calibration method also employs an analyte calibration value that is independently determined;

(ii) providing the analyte calibration value;

(iii) selecting a conditional statement selected from the group consisting of;

(a) if neither the second half-cycle signal S_J+1 nor the third half-cycle signal S_j+2 comprise errors, then S_j+1 and S_j+2 are used in the calibration method;

(b) if only the second half-cycle signal S_j+1 comprises an error, then an estimated signal S^E_J+1 is obtained by determining an interpolated value using signal S_J and S_j+2, wherein said interpolated value is S^E_J+1, and S^E_J+1 and S_J+2 are used in the calibration method;

(c) if only the third half-cycle signal S_j+2 comprises an error, then an estimated signal S^E_J+2 is obtained by determining an extrapolated value using signal S_J and S_J+1, wherein said extrapolated value is S^E_j+2, and S_j+1 and S^E_j+2 are used in the calibration method; and

(d) if both the second half-cycle signal S_J+1 and the third half-cycle signal S_J+2 comprise errors, then return to (i) to obtain a new half-cycle signal S_j from a later measurement half-cycle than the first half-cycle signal,

wherein said calibration method reduces the incidence of failed calibration for the analyte monitoring system.

47. The method of claim 46, wherein said analyte monitoring device comprises two sensors and a relationship between the signals obtained from the different sensors is used in interpolation and/or extrapolation calculation of estimated values.

48. The method of claim 47, wherein said relationship between the signals from the different sensors is a smoothed ratio of the form:

R^S_i=wR_i+(1−

w)R^s<sub>l−

1</sub>  

 

Eqn. 10

wherein, R_i is the A/B or B/A signal ratio for a i^th measurement cycle, R^S₁ is smoothed R for a i^th measurement cycle, and w is a smoothing factor and is represented by a fraction between and inclusive of 0 through 1, and R^S<sub>i−

1</sub> is a smoothed ratio for the (i−

1)^th measurement cycle, wherein the i^th measurement cycle is composed of first and second half-cycles and the second half-cycle value of the i^th measurement cycle precedes S_J.

49. The method of claim 48, wherein a smoothed A/B ratio and a smoothed B/A ratio are employed, and said ratios are as follows:

50. The method of claim 49, wherein said analyte is glucose.

51. The method of claim 49, for interpolation in the situation where both S_J and S_j+2 are signals from the B sensor (S^B_j and S^B_j+2), and S_j+1 is being estimated for the A sensor signal (S^AE_j+1), interpolation Eqn. 7A is employed as follows:

52. The method of claim 49, for interpolation in the situation where both S_j and S_J+2 are signals from the A sensor (S^A_J and S^A_J+2), and S_J+1 is being estimated for the B sensor signal (S^BE_j+1), interpolation Eqn. 7C is employed as follows:

53. The method of claim 49, for extrapolation in the situation where S_J is signal from sensor A (S^A_J) and S_j+1 is signal from B sensor (S^B_j+1), and S_J+2 is being estimated for the A sensor signal (S^AE_J+2), extrapolation Eqn. 8A is employed as follows:

54. The method of claim 49, for extrapolation in the situation where S_j is signal from the B sensor (S^B_j) and S_j+1 is signal from the A sensor (S^A_j+1), and S_j+2 is being estimated for the B sensor signal (S^BE_J+2), extrapolation Eqn. 8C is employed as follows:

55. The method of claim 46, wherein said analyte is glucose.

56. The method of claim 55, wherein said analyte monitoring device comprises (i) an iontophoretic sampling device, and (ii) an electrochemical sensing device.

57. The method of claim 56, wherein said analyte-related signal is a current or a charge related to analyte amount or concentration of analyte in the subject.

58. The method of claim 46, wherein one or more microprocessors are utilized to perform said calibration method.

59. The method of claim 58, wherein said one or more microprocessors further control components of the analyte monitoring system.

60. The method of claim 59, wherein said analyte monitoring system comprises a sampling device and a sensing device.

61. The method of claim 60, wherein said one or more microprocessors control obtaining samples from the subject and sensing analyte concentration in each obtained sample to provide the series of analyte-related signals.

62. The method of claim 46, further comprising waiting for an un-skipped half-cycle signal (S_j) before initiating said calibration method.

63. One or more microprocessors programmed to control:

operation of a sensing device for sensing an analyte in each of a series of samples to obtain an analyte-related signal from each sample that is related to analyte amount or concentration in a subject, thus providing a series of analyte-related signals, said sensing device comprising a first sensor (A) and second sensor (B), wherein (1) said first sensor (A) is in operative contact with a first collection reservoir and said second sensor (B) is in operative contact with a second collection reservoir, and (2) two consecutive analyte-related signals comprise a measurement cycle, and each of the two consecutive analyte-related signals is half-cycle analyte-related signal; and

performance of a calibration method to relate analyte amount or concentration in the subject to analyte-related signals obtained from the sensors, said calibration method comprising;

(i) obtaining a first half-cycle analyte-related signal S_j, wherein a second half-cycle analyte-related signal S_J+1, or an estimate thereof, and a third half-cycle analyte-related signal S_J+2, or an estimate thereof, are both used in the calibration method so that the sensor analyte-related signals correlate to the analyte amount or concentration in the subject, wherein the calibration method also employs an analyte calibration value that is independently determined;

(ii) providing the analyte calibration value;

(iii) selecting a conditional statement selected from the group consisting of;

(a) if neither the second half-cycle signal S_j+1 nor the third half-cycle signal S_J+2 comprise errors, then S_J+1 and S_J+2 are used in the calibration method;

(b) if only the second half-cycle signal S_J+1 comprises an error, then an estimated signal S^E_J+1 is obtained by determining an interpolated value using signal S_j and S_j+2, wherein said interpolated value is S^E_J+1, and S^E_j+1 and S_j+2 are used in the calibration method;

(c) if only the third half-cycle signal S_j+2 comprises an error, then an estimated signal S^E_J+2 is obtained by determining an extrapolated value using signal S_j and S_j+1, wherein said extrapolated value is S^E_J+2, and S_j+1 and S^E_j+2 are used in the calibration method; and

(d) if both the second half-cycle signal S_j+1 and the third half-cycle signal S_J+2 comprise errors, then return to (i) to obtain a new half-cycle signal S_J from a later measurement half-cycle than the first half-cycle signal.

64. The one or more microprocessors of claim 63, wherein said analyte monitoring device comprises a sensing device and said one or more microprocessors are further programmed to control operation of said sensing device.

65. The one or more microprocessors of claim 64, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control operation of said sampling device.

66. An analyte monitoring device comprising:

a sensing device; and

one or more microprocessor programmed to control operation of said sensing device and said one or more microprocessor programmed to control performance of a calibration method to relate analyte amount or concentration in the subject to analyte-related signals obtained from the sensors, said calibration method comprising;

(i) obtaining a first half-cycle analyte-related signal S,, wherein a second half-cycle analyte-related signal S_J+1, or an estimate thereof, and a third half-cycle analyte-related signal S_j+2, or an estimate thereof, are both used in the calibration method so that the sensor analyte-related signals correlate to the analyte amount or concentration in the subject, wherein the calibration method also employs an analyte calibration value that is independently determined;

(ii) providing the analyte calibration value;

(iii) selecting a conditional statement selected from the group consisting of;

(a) if neither the second half-cycle signal S_J+1 nor the third half-cycle signal S_j+2 comprise errors, then S_J+1 and S_J+2 are used in the calibration method;

(b) if only the second half-cycle signal S_j+1 comprises an error, then an estimated signal S^E_j+1 is obtained by determining an interpolated value using signal S_J and S_J+2, wherein said interpolated value is S^E_J+1, and S^E_J+1 and S_j+2 are used in the calibration method;

(c) if only the third half-cycle signal S_j+2 comprises an error, then an estimated signal S^E_j+2 is obtained by determining an extrapolated value using signal S_J and S_J+1, wherein said extrapolated value is S^E_J+2, and S_j+1 and S^E_J+2 are used in the calibration method; and

(d) if both the second half-cycle signal S_J+1 and the third half-cycle signal S_J+2 comprise errors, then return to (i) to obtain a new half-cycle signal S_j from a later measurement half-cycle than the first half-cycle signal.

67. The analyte monitoring device of claim 66, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control the operation of said sampling device.

68. A method for predicting an analyte concentration-related event in a subject being monitored for levels of a selected analyte using an analyte monitoring device, said method comprising

providing (A) a series of analyte-related signals obtained from the analyte monitoring device over time, wherein each analyte-related signal is related to the amount or concentration of analyte in the subject, (B) a predetermined threshold value indicative of an analyte concentration-related event in the subject, and (C) a predetermined threshold rate of change of analyte concentration indicative of an analyte concentration-related event in the subject;

calculating (A) a predicted analyte-related signal at a future time interval, which occurs after the series of analyte-related signals is obtained, using one or more predictive algorithms, and (B) a rate of change of analyte concentration in the subject;

comparing (A) the predicted analyte-related signal to the threshold value, then (i) if the predicted value is within the threshold value, then the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the predicted value is beyond the threshold value, then an analyte concentration-related event is indicated, and the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal;

(B) the rate of change of analyte concentration in the subject to the predetermined threshold rate of change, then (i) if the rate of change is beyond the predetermined threshold rate of change then an analyte concentration-related event is indicated and the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the rate of change is within the predetermined threshold rate of change, then the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal; and

predicting an analyte concentration-related event in a subject if both the predicted value indicates an analyte concentration-related event and the rate of change indicates an analyte concentration-related event.

69. The method of claim 68, wherein when an analyte concentration-related event is predicted an alert is provided to the subject to indicate an analyte-concentration related event.

70. The method of claim 68, wherein said one or more predictive algorithms are selected from the group consisting of:

71. The method of claim 68, wherein said rate of change of analyte concentration in the subject is determined using one or more gradient models selected from the group consisting of:

72. The method of claim 68, wherein said predictive algorithm is

73. The method of claim 68, wherein said analyte is glucose.

74. The method of claim 73, wherein (i) said predicted glucose-related signal, at a further time interval, is lower than the predetermined threshold said predicted glucose-related signal is designated to be hypoglycemic, and (ii) said predicted rate of change is negative and less than a predetermined threshold rate of change is indicative of a hypoglycemic event;

and (iii) a hypoglycemic event in the subject is predicted when both (a) comparing the predicted measurement value to the predetermined threshold indicates a hypoglycemic event, and (b) comparing the rate of change with the threshold rate of change indicates a hypoglycemic event.

75. The method of claim 73, wherein said predictive algorithm is

76. The method of claim 73, wherein said analyte-concentration related event in the subject is hypoglycemia.

77. The method of claim 73, wherein said analyte-concentration related event in the subject is hyperglycemia.

78. The method of claim 73, wherein said analyte monitoring device comprises (i) an iontophoretic sampling device, and (ii) an electrochemical sensing device.

79. The method of claim 78, wherein said analyte-related signal is a current or a charge related to analyte amount or concentration of glucose in the subject.

80. The method of claim 68, wherein one or more microprocessors are utilized to perform said calculating and comparing.

81. The method of claim 80, wherein when an analyte concentration-related event is predicted said one or more microprocessors triggers the analyte monitoring system to provide an alert to the subject to indicate an analyte-concentration related event.

82. The method of claim 80, wherein said one or more microprocessors further control components of the analyte monitoring system.

83. The method of claim 82, wherein said analyte monitoring system comprises a sampling device and a sensing device.

84. The method of claim 83, wherein said one or more microprocessors control obtaining samples from the subject and sensing analyte concentration in each obtained sample to provide the series of analyte-related signals.

85. The method of claim 76, wherein further parameters are used to confirm a prediction of the hypoglycemic event, such further parameters selected from the group consisting of current glucose readings in the subject, one or more predicted glucose reading, time intervals, trends, skin conductance, and skin temperature.

86. One or more microprocessors programmed to control:

provision of (A) a series of analyte-related signals obtained from the analyte monitoring device over time, wherein each analyte-related signal is related to the amount or concentration of analyte in the subject, (B) a predetermined threshold value indicative of an analyte concentration-related event in the subject, and (C) a predetermined threshold rate of change of analyte concentration indicative of an analyte concentration-related event in the subject;

calculation of (A) a predicted analyte-related signal at a future time interval, which occurs after the series of analyte-related signals is obtained, using one or more predictive algorithms, wherein and (B) a rate of change of analyte concentration in a subject;

comparison of (A) the predicted analyte-related signal to the threshold value, then (i) if the predicted value is within the threshold value, then the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the predicted value is beyond the threshold value, then an analyte concentration-related event is indicated, and the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal;

(B) the rate of change of analyte concentration in the subject to the predetermined threshold rate of change, then (i) if the rate of change is beyond the predetermined threshold rate of change then an analyte concentration-related event is indicated and the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the rate of change is within the predetermined threshold rate of change, then the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal; and

prediction of an analyte concentration-related event in a subject if both the predicted value indicates an analyte concentration-related event and the rate of change indicates an analyte concentration-related event.

87. The one or more microprocessors of claim 86, wherein said analyte monitoring device comprises a sensing device and said one or more microprocessors are further programmed to control operation of said sensing device.

88. The one or more microprocessors of claim 87, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control operation of said sampling device.

89. An analyte monitoring device comprising:

a sensing device; and

one or more microprocessor programmed to control operation of said sensing device and said one or more microprocessor programmed to control

provision of (A) a series of analyte-related signals obtained from the analyte monitoring device over time, wherein each analyte-related signal is related to the amount or concentration of analyte in the subject, (B) a predetermined threshold value indicative of an analyte concentration-related event in the subject, and (C) a predetermined threshold rate of change of analyte concentration indicative of an analyte concentration-related event in the subject;

calculation of (A) a predicted analyte-related signal at a future time interval, which occurs after the series of analyte-related signals is obtained, using one or more predictive algorithms, wherein and (B) a rate of change of analyte concentration in a subject;

comparison of (A) the predicted analyte-related signal to the threshold value, then (i) if the predicted value is within the threshold value, then the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the predicted value is beyond the threshold value, then an analyte concentration-related event is indicated, and the analyte monitoring device continues to provide a series of analyte-related signals and repeats said calculating and comparing of a predicted analyte-related signal based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal;

(B) the rate of change of analyte concentration in the subject to the predetermined threshold rate of change, then (i) if the rate of change is beyond the predetermined threshold rate of change then an analyte concentration-related event is indicated and the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal, or (ii) if the rate of change is within the predetermined threshold rate of change, then the analyte monitoring system continues to provide a series of analyte-related signals and repeats said calculating of a rate of change based on the series of analyte-related signals comprising new analyte-related signal obtained subsequent to the previous predicted analyte-related signal; and

prediction of an analyte concentration-related event in a subject if both the predicted value indicates an analyte concentration-related event and the rate of change indicates an analyte concentration-related event.

90. The analyte monitoring device of claim 89, wherein said analyte monitoring device further comprises a sampling device and said one or more microprocessors are further programmed to control the operation of said sampling device.