SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA

• US 20080021666A1
• Filed: 10/01/2007
• Published: 01/24/2008
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Brauker, James, Goode, Paul, Kamath, Apurv
• Granted Patent: US 8,394,021 B2
• Time in Patent Office: Days
• US Class Current: 702/85
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/04 Constructional details of apparatus
• CPC Class Codes: A61B 2562/085 combined with means for recording calibration data
• CPC Class Codes: A61B 3/10 Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/1433 provided with locking means details of syringes A61M5/315
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1468 using chemical or electrochemical methods, e.g. by polarographic means A61B5/1486 takes precedence
• CPC Class Codes: A61B 5/1473 invasive, e.g. introduced into the body by a catheter A61B5/1482 takes precedence
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/150022 for capillary blood or interstitial fluid
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G01N 33/48707 by electrical means G01N33/49, G01N33/493 take precedence
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.

Claims

1. A method for matching continuous glucose sensor data with reference data, the method comprising:

receiving sensor data from a continuous glucose sensor, the sensor data comprising one or more sensor data points;

receiving reference data from a reference glucose monitor, the reference data comprising one or more reference data points;

forming a matched pair by pairing a sensor value with a reference value, wherein the sensor value comprises a sensor data point or an averaged sensor data point, and wherein the reference value comprises a reference data point or an averaged reference data point; and

calibrating the sensor data in real-time, wherein the sensor data is calibrated using at least the matched pair.

2. The method of claim 1, wherein the step of forming the matched pair comprises averaging a plurality of reference data points to obtain the reference value.

3. The method of claim 2, wherein the step of averaging comprises at least one of equally weighted averaging, non-equally weighted averaging, calculating a mean, and calculating a median.

4. The method of claim 1, wherein the step of forming the matched pair comprises averaging a plurality of time corresponding sensor data points to obtain the sensor value.

5. The method of claim 4, wherein the step of averaging comprises at least one of equally weighted averaging, non-equally weighted averaging, calculating a mean, and calculating a median.

6. The method of claim 1, wherein the step of forming the matched pair comprises averaging a plurality of reference data points to obtain the reference value and averaging a plurality of sensor data points to obtain the sensor value.

7. The method of claim 1, wherein the one or more sensor data points are obtained at a time that is at least about 10 minutes after a time at which the one or more reference data points are obtained.

8. The method of claim 1, wherein the one or more sensor data points are obtained at a time after the one or more reference data points are obtained, wherein the time is configured to compensate for a time lag caused by at least one of a data smoothing filter and a physiological time lag.

9. The method of claim 1, wherein the step of forming the matched pair comprises evaluating a plurality of matched pairs, wherein the plurality of matched pairs are obtained by matching a reference data point against a plurality of time-spaced sensor data points.

10. The method of claim 9, wherein the step of forming the matched pair comprises choosing from the plurality of matched pairs a matched pair with a best correlation.

11. A system for matching continuous glucose sensor data with reference data, the system comprising:

a sensor data module configured to receive a data stream from a continuous glucose sensor, the sensor data comprising one or more sensor data points;

a reference data module configured to receive reference data from a reference glucose monitor, the reference data comprising one or more reference data points; and

a processor module configured to form a matched pair by pairing a sensor data point with a reference data point, wherein the processor module is further configured to calibrate sensor data in real-time, wherein the sensor data is calibrated using at least said matched data pair.

12. The system of claim 11, wherein the processor module is configured to average a plurality of reference data points to obtain a reference value.

13. The system of claim 12, wherein the processor module is configured to average the plurality of reference data points using at least one of an equally weighted average, a non-equally weighted average, a mean-value, and a median.

14. The system of claim 11, wherein the processor module is configured to average a plurality of time corresponding sensor data points to obtain a sensor value.

15. The system of claim 14, wherein the processor module is configured to average the plurality of sensor data points using at least one of an equally weighted average, a non-equally weighted average, a mean-value, and a median.

16. The system of claim 11, wherein the processor module configured to average a plurality of reference data points to obtain a reference value and to average a plurality of sensor data points to obtain a sensor value.

17. The system of claim 16, wherein the sensor value is measured at a time that is at least about 10 minutes after a time at which the reference value is measured.

18. The system of claim 16, wherein the sensor value is measured at a time after the reference value is measured, wherein the time is configured to compensate for a time lag caused by at least one of a data smoothing filter and a physiological time lag.

19. The system of claim 11, wherein the processor module is further configured to evaluate a plurality of matched pairs, wherein the plurality of matched pairs are obtained by matching a reference data point against a plurality of time-spaced sensor data points.

20. The system of claim 19, wherein the processor module is further configured to choose from the plurality of matched pairs, a matched pair with the best correlation.

21. A method for calibrating a continuous glucose sensor data, the method comprising:

receiving a data stream from a continuous glucose sensor, the data stream comprising one or more sensor data points;

receiving reference data from a reference glucose monitor, the reference data comprising one or more reference data points;

forming at least one matched pair by pairing one or more sensor data points with one or more reference data points;

forming a first calibration line and a second calibration line that have different slopes; and

calibrating the one or more sensor data points in real-time, wherein the first calibration line is applied when a blood glucose concentration is at or below a predetermined threshold, and wherein the second calibration line is applied when a blood glucose concentration is at or above the predetermined threshold

22. The method of claim 21, wherein the predetermined threshold is 150 mg/dl.

23. The method of claim 21, wherein the first calibration line is a first regression line based, at least in part, on a matched pair, and wherein the second calibration line is a second regression line obtained by applying a predetermined pivot about a point to the first regression line.

24. The method of claim 23, wherein the pivot is determined from a retrospective analysis of glucose sensor data.

25. The method of claim 23, wherein the pivot is selected such that at least one of the first calibration line and the second calibration line complies with a clinical acceptability standard.

26. The method of claim 25, wherein the clinical acceptability standard is a standard selected from group consisting of Clarke Error Grid, Consensus Grid, mean absolute relative difference, and other clinical cost function.

31. The system of claim 23, wherein the pivot is selected such that at least one of the first calibration line and the second calibration line complies with a clinical acceptability standard.

32. The system of claim 25, wherein the clinical acceptability standard is a standard selected from group consisting of Clarke Error Grid, Consensus Grid, mean absolute relative difference, and other clinical cost function.

27. A system for calibrating continuous glucose sensor data, the system comprising:

a sensor data module configured to receive a data stream from a continuous glucose sensor, the data stream comprising one or more sensor data points;

a reference input module configured to receive reference data from a reference glucose monitor, the reference data comprising one or more reference data points;

a processor module configured to form at least one matched pair by pairing one or more sensor data points with one or more reference data points;

wherein the processor module is further configured to form a first calibration line and a second calibration line that have different slopes, and wherein at least one of the two calibration lines is based at least in part on the at least one matched pair; and

calibrating the one or more sensor data points in real-time, wherein the first calibration line is applied when a blood glucose concentration is at or below a predetermined threshold, and wherein the second calibration line is applied when a blood glucose concentration is at or above the predetermined threshold

28. The system of claim 27, wherein the predetermined threshold is 150 mg/dl.

29. The system of claim 27, wherein the first calibration line is a first regression line based, at least in part, on a matched pair, and the second calibration line is a second regression line obtained by applying a predetermined pivot about a point to the first regression line.

30. The system of claim 29, wherein the pivot is determined from a retrospective analysis of glucose sensor data.

33. An integrated system, comprising:

a continuous glucose sensor configured to measure a glucose concentration in a host and to provide sensor data associated therewith; and

an insulin delivery device configured to administer insulin, wherein the insulin delivery device comprises a processor module configured to receive and store, at least temporarily, sensor data obtained from the continuous glucose sensor, and wherein the processor module is further configured to analyze sensor data to predict a future glucose concentration in the host, whereby insulin is administered at least in part responsive to the predicted future glucose concentration.

34. The integrated system of claim 33, wherein the processor module is configured to administer insulin, via the delivery device, responsive to a predicted future glucose concentration below a predetermined threshold.

35. The system of claim 33, wherein the processor module is configured to determine an amount and time of insulin administration based, at least in part, on the predicted future glucose concentration.

36. The system of claim 33 wherein the insulin delivery device comprises an insulin pump.

38. The integrated system of claim 33, wherein the processor module is configured to administer insulin, via the delivery device, responsive to a rate of change glucose concentration above a predetermined threshold.

39. The system of claim 33, wherein the processor module is configured to determine an amount and time of insulin administration based, at least in part, on the rate of change.

40. The system of claim 33 wherein the insulin delivery device comprises an insulin pump.

42. The system of claim 33, wherein the processor module is configured to determine an amount and time of insulin administration based, at least in part, on the glucose trend.

43. The system of claim 33 wherein the insulin delivery device comprises an insulin pump.

37. An integrated system, comprising:

a continuous glucose sensor configured to measure a glucose concentration in a host and to provide sensor data associated therewith; and

an insulin delivery device configured to administer insulin, wherein the insulin delivery device comprises a processor module configured to receive and store, at least temporarily, sensor data obtained from the continuous glucose sensor, wherein the processor module is further configured to analyze sensor data to determine a rate of change of glucose concentration in the host, whereby insulin is administered at least in part responsive to the rate of change.

41. An integrated system, comprising:

a continuous glucose sensor configured to measure a glucose concentration in a host and provide sensor data associated therewith; and

an insulin delivery device configured to administer insulin, wherein the insulin delivery device comprises a processor module configured to receive and store, at least temporarily, sensor data obtained from the continuous glucose sensor, wherein the processor module is further configured to analyze sensor data to determine a glucose trend in the host, whereby insulin is administered at least in part responsive to the glucose trend.

44. A method for determining at least one of an amount of insulin to be administered or a duration of time of insulin administration, the method comprising:

receiving continuous glucose sensor data, the sensor data comprising one or more sensor data points;

processing said glucose sensor data to determine at least one of an amount of insulin to be administered or a duration of time of insulin administration by analyzing a glucose trend in the sensor data; and

instructing an insulin delivery device to deliver insulin, the instruction comprising at least one of the amount of insulin to be administered or the duration of time of insulin administration, responsive to the glucose trend.

45. The method of claim 44, wherein the step of analyzing the glucose trend comprises predicting a future glucose concentration.

46. The method of claim 44, wherein the step of analyzing the glucose trend comprises determining a rate of change.

47. A glucose sensor system, comprising:

a glucose sensor; and

sensor electronics configured to receive and retain glucose data from the glucose sensor;

wherein the sensor electronics are configured to process the glucose data to predict a glucose-related trend.

48. The system of claim 47, wherein the glucose-related trend comprises a rate of glucose increase or a rate of glucose decrease.

49. The system of claim 47, wherein the glucose related trend comprises an acceleration of glucose increase or an acceleration of glucose decrease.

50. The system of claim 47, wherein the sensor electronics comprises a readable/writable memory device that retains the glucose data

51. The system of claim 47, further comprising a receiver configured to display the glucose-related trend.

52. A glucose monitoring device, comprising:

a sensor data module configured to receive glucose data from a continuous glucose sensor;

a data storage module coupled to the sensor data module and configured to store glucose data; and

a processor configured to process the stored glucose data to predict a glucose-related trend.

53. The device of claim 52, wherein the glucose-related trend comprises a rate of glucose level increase or a rate of glucose level decrease.

54. The device of claim 52, wherein the glucose related trend comprises an acceleration of glucose level increase or an acceleration of glucose level decrease.

55. The device of claim 52, wherein the data storage unit comprises a readable/writable memory device.

56. The device of claim 52, further comprising a user interface configured to display the glucose-related trend.

57. The device of claim 52, further comprising a communication unit operatively coupled to the processor, the communication unit configured to transmit one or more of the glucose data or the glucose-related trend.

58. The device of claim 57, wherein the communication unit comprises a wireless communication unit.

59. The device of claim 57, wherein the communication unit comprises an RF transmitter.

60. The device of claim 59, wherein the communication unit comprises an RF transceiver.

61. A method of processing glucose data, comprising:

positioning at least a portion of a glucose sensor in contact with a bodily fluid of a host;

obtaining glucose-related information using the sensor;

storing the glucose-related information; and

processing the stored glucose-related information and predicting glucose-related trend.

62. The method of claim 61, further comprising displaying the glucose-related trend.

63. A method for calibrating a continuous glucose sensor, comprising:

positioning at least a portion of an electrochemical sensor in a body of a host;

obtaining one or more sensor data points from the electrochemical sensor;

determining a rate of change from the one or more sensor data points; and

determining whether calibration is appropriate based on the determined rate of change.

64. The method of claim 63, wherein determining whether calibration is appropriate comprises comparing the determined the rate of change to a predetermined rate of change threshold.

65. The method of claim 64, wherein when the determined rate of change is above the predetermined rate of change threshold, calibration is determined to be not appropriate.

66. The method of claim 63, further comprising waiting a predetermined time period before performing calibration.

67. The method of claim 66 wherein when the determined rate of change is below the predetermined value, calibration is determined to be appropriate.

68. The method of claim 63 further comprising performing calibration using a blood sample to calibrate the electrochemical sensor signal.

69. A method of glucose determination, comprising:

positioning at least a portion of an electrochemical sensor in a body of a host;

obtaining one or more sensor data points from the electrochemical sensor; and

performing a rate of change analysis based on the one or more sensor data points.

70. The method of claim 69, wherein the rate of change analysis comprises determining whether calibration is appropriate.

71. A glucose sensor system, comprising:

an electrochemical glucose sensor; and

a receiver configured to receive one or more sensor data points from an electrochemical sensor, the receiver further configured to determine a rate of change of the one or more sensor data points and to determine whether calibration is appropriate based on the determined rate of change.

72. The device of claim 71, further comprising a user interface operatively coupled to the receiver configured to display one or more data associated with at least one of the one or more sensor data points, the rate of change, and the determination whether calibration is appropriate.

73. A method for processing sensor data from a continuous glucose sensor, the method comprising:

receiving sensor data from a continuous glucose sensor;

filtering or data smoothing the received sensor data to form first filtered sensor data; and

filtering or data smoothing the first filtered sensor data to obtained second filtered sensor data.

74. The method of claim 73, wherein the step of filtering or data smoothing the received sensor data and the step of filtering or data smoothing the first filtered sensor data are performed in separate electronics units.

75. The method of claim 73, wherein the step of filtering or data smoothing the received sensor data and the step of filtering or data smoothing the first filtered sensor data are performed in a single or integral electronics unit

76. The method of claim 73, wherein the step of filtering or data smoothing the received sensor data is performed in a sensor electronics, wherein the sensor electronics are integral with the continuous glucose sensor, and wherein the step of filtering or data smoothing the first filtered sensor data is performed in a receiver electronics, wherein the receiver electronics are separate from the sensor electronics, and wherein the sensor electronics are operatively connected to the receiver electronics by a wired or wireless connection.

77. A system for processing sensor data from a continuous glucose sensor, the system comprising:

a sensor data module configured to receive sensor data from a continuous glucose sensor; and

a processor module configured to filter or smooth the received sensor data to form first filtered sensor data, wherein the processor module is further configured to filter or smooth the first filtered sensor data to obtain second filtered sensor data.

78. The system of claim 77, wherein filtering or smoothing the received sensor data to form first filtered sensor data and filtering or smoothing the first filtered sensor data to obtain second filtered sensor data are performed in separate electronics units.

79. The system of claim 77, wherein filtering or smoothing the received sensor data to form first filtered sensor data and filtering or smoothing the first filtered sensor data to obtain second filtered sensor data are performed in a single or integral electronics unit

80. The system of claim 77, wherein the system further comprises sensor electronics directly connected to the continuous glucose sensor, wherein the first filtered sensor data is obtained from the sensor electronics, and wherein the system further comprises receiver electronics operative connected to the sensor electronics, wherein the second filtered sensor data is obtained from the receiver electronics, wherein the receiver electronics are separate from the sensor electronics, and wherein the sensor electronics are operatively connected to the receiver electronics by a wired or wireless connection.

81. A method for predicting future data from real-time continuous glucose sensor data, the method comprising:

receiving sensor data from a continuous glucose sensor, the sensor data comprising one or more sensor data points; and

predicting one or more glucose values for a future time, based at least in part on the sensor data.

82. The method of claim 81, further comprising:

receiving reference data from a reference glucose monitor, the reference data comprising one or more reference data points;

forming at least one matched pair by pairing one or more sensor data points with one or more reference data points; and

forming a conversion function based, at least in part, on said at least one matched pair, wherein the step of predicting one or more glucose values comprises calculating the one or more future glucose values based, at least in part, on the conversion function

83. The method of claim 81, further comprising a step of alerting a user when one or more predicted glucose values indicates an upcoming hypoglycemic event or an upcoming hyperglycemic event.

84. The method of claim 81, further comprising a step of compensating for a time lag associated with the sensor by estimating one or more glucose values for a future time, such that an estimate of a glucose value at an instant time can be displayed without a time lag.

85. The method of claim 84, further comprising displaying the time-compensated glucose value estimate on a user interface.

86. The method of claim 81, further comprising a step of processing sensor data and compensating for a time lag associated with the processing step by estimating one or more glucose values for a future time, such that an estimate of a glucose value at an instant time can be displayed without a time lag.

87. The method of claim 86, further comprising displaying the time-compensated glucose value estimate on a user interface.

88. A system for predicting future data from real-time continuous glucose sensor data, the system comprising:

a sensor data module configured to receive sensor data from a continuous glucose sensor, the sensor data comprising one or more sensor data points; and

a processor module configured to predict one or more glucose values for a future time, based at least in part on the sensor data.

89. The system of claim 88, further comprising:

a reference input module configured to receive reference data from a reference glucose monitor, the reference data comprising one or more reference data points, and wherein the processor module is further configured to form at least one matched pair by pairing a one or more sensor data points with one or more reference data points and form a conversion function based, at least in part, on said at least one matched pair, wherein one or more glucose values is predicted by calculating one or more future glucose values based, at least in part, on the conversion function

90. The system of claim 88, further comprising an output module configured to alert a user when one or more predicted glucose values indicates an upcoming hypoglycemic event or an upcoming hyperglycemic event.

91. The system of claim 88, wherein the processor module is configured to compensate for a time lag associated with the sensor by estimating one or more glucose values for a future time, such that an estimate of a glucose value at an instant time can be displayed without a time lag.

92. The system of claim 91, further comprising an output module configured to display the time-compensated glucose value estimate on a user interface.

93. The system of claim 88, wherein the processor module is configured to process the sensor data and compensate for a time lag associated with the sensor data processing by estimating one or more glucose values for a future time, such that an estimate of a glucose value at an instant time can be displayed without a time lag.

94. The system of claim 88, further comprising an output module configured to display the time-compensated glucose value estimate on a user interface.

95. A continuous glucose sensing system, the system comprising:

a continuous glucose sensor device comprising a first sensor configured to continuously measuring a glucose concentration in a host, wherein at least a portion of the first sensor is positioned in or under a host'"'"'s tissue;

a glucose monitor comprising a second sensor configured to determine a glucose concentration of the host at a point in time; and

a processor module configured to calibrate data from said first sensor using data from said second sensor, and wherein the second sensor is integral with at least a portion of the continuous glucose sensor device.

96. The system of claim 95, wherein the continuous glucose sensor device comprises a receiver configured to receive and display continuous glucose data from the first sensor.

97. The system of claim 96, wherein the glucose monitor further comprises a blood glucose meter, and wherein the meter is integral with the receiver.

98. A method of calibrating, the method comprising:

inserting at least a portion of a first sensor in a host'"'"'s tissue; and

calibrating the first sensor unit after a predetermined time period has lapsed from the inserting step.

99. The method of claim 98, wherein the calibrating step further comprises a step of performing a blood glucose measurement after the predetermined time period has lapsed from the inserting step.

100. An analyte monitoring system, comprising:

a sensor device including a sensor, the sensor device configured to receive a data stream corresponding to a glucose concentration in a host, the data stream comprising one or more sensor data points; and

a display unit operatively coupled to the sensor, the display unit configured to output data based on signals received from the sensor device.

101. The system of claim 100, wherein the data output comprises at least one output selected from the group consisting of a series of audio alerts, a series of vibratory alerts, a series of visual alerts, and a series of a combination of one or more of audio, visual or vibratory alerts.

102. An analyte monitoring device, comprising:

a receiver unit for receiving one or more signals related to an analyte level in a host detected by an electrochemical sensor, the receiver unit comprising a display to display an indication of the analyte level wherein the receiver unit comprises a calibrator.

103. The device of claim 102, wherein the receiver unit comprises an RF receiver.

104. The device of claim 102, wherein the receiver unit comprises an analyzer coupled to the display and the RF receiver to analyze data from the RF receiver and provide analyzed data to the display.

105. The device of claim 102, wherein the calibrator is a blood glucose calibrator.

106. The device of claim 102, wherein the receiver unit comprises an alarm configured to indicate when the analyte level is at or near a threshold level.

107. The device of claim 106, wherein the threshold level comprises at least one level selected from the group consisting of hypoglycemia, predicted future hypoglycemia, hyperglycemia, or predicted future hyperglycemia.

108. The device of claim 106, wherein the alarm comprises at least one alarm selected from the group consisting of an audible signal, a visual display, or a vibratory signal.

109. The device of claim 102 wherein the receiver unit is a portable handheld unit.

110. The device of claim 102 wherein the receiver unit is configured for wearing on or under an article of clothing.

111. The device of claim 102, wherein the receiver unit includes an RF transceiver configured to receive or transmit the one or more signals related to an analyte level.

112. The device of claim 102, wherein the analyte is glucose.

113. The device of claim 102, wherein the receiver unit is further configured to communicate with a drug administration system.

114. The device of claim 113, wherein the receiver unit is configured to wirelessly communicate with the drug administration system.

115. The device of claim 114, wherein the receiver unit is configured to communicate with the drug administration system by rf communication.

116. The device of claim 102, wherein the receiver unit is configured to display one or more indicators associated with the analyte level on the display.

117. The device of claim 116, wherein the one or more indicators comprises one or more of an arrow or a color representative of analyte level trend information.

118. The device of claim 116, wherein the displayed one or more indicators comprises a historical analyte level or a predicted analyte level of the host.

119. The device of claim 116, wherein the displayed one or more indicators corresponds to a rate of change in the analyte level detected by the electrochemical sensor.

120. A system for calibrating a glucose sensor, the system comprising:

a continuous glucose sensor configured to substantially continuously measure a glucose concentration in a host and to provide sensor data associated therewith;

a reference glucose monitor configured to measure the host'"'"'s blood glucose concentration at a time point and provide reference data associated therewith; and

a processor module, configured to form at least one matched data pair by matching reference analyte data to substantially time corresponding sensor data, wherein the processor module is further configured determine a rate of change of the glucose concentration at time substantially corresponding to the at least one matched data pair and to determine whether to calibrate the continuous glucose sensor responsive thereto.

121. The system of claim 120, further comprising a receiver unit operatively connected to the continuous glucose sensor and configured to receive and process the sensor data, wherein the processor module and reference glucose monitor are integral with the receiver unit.

122. The system of claim 120, wherein the processor module is further configured to instruct administration of insulin at least in part responsive to the rate of change.

123. The system of claim 122, wherein the processor module is further configured to predict a future glucose concentration.

124. The system of claim 120, wherein the processor module is configured to wait a predetermined time period before performing calibration.

127. The system of claim 122, wherein the processor module is further configured to predict a future glucose concentration.

128. The system of claim 127, wherein the processor module is further configured to instruct administration of insulin at least in part responsive to the predicted future glucose concentration.

129. The system of claim 120, wherein the processor module is configured to wait a predetermined time period before performing calibration.

131. The system of claim 120, further comprising a receiver unit operatively connected to the continuous glucose sensor and configured to receive and process the sensor data, wherein the processor module and reference glucose monitor are integral with the receiver unit.

132. The system of claim 120, wherein the processor module is further configured to instruct administration of insulin at least in part responsive to the physiological changes.

125. A system for calibrating a glucose sensor, the system comprising:

a continuous glucose sensor configured to substantially continuously measure a glucose concentration in a host and to provide sensor data associated therewith;

a reference glucose monitor configured to measure a host'"'"'s blood glucose concentration at a time point and provide reference data associated therewith; and

a processor module configured to form at least one matched data pair by matching reference analyte data to substantially time corresponding sensor data, wherein the processor module is further configured evaluate a congruence of at least one matched data pair and to determine whether to calibrate the sensor responsive thereto.

126. The system of claim 125, further comprising a receiver unit operatively connected to the continuous glucose sensor and configured to receive and process the sensor data, wherein the processor module and reference glucose monitor are integral with the receiver unit.

130. A system for calibrating a glucose sensor, the system comprising:

a continuous glucose sensor configured to substantially continuously measure a glucose concentration in a host and to provide sensor data associated therewith;

a reference glucose monitor configured to measure the host'"'"'s blood glucose concentration at a time point and to provide reference data associated therewith; and

a processor module, configured to form at least one matched data pair by matching reference analyte data to substantially time corresponding sensor data, wherein the processor module is further configured evaluate physiological changes of the host at time substantially corresponding to the at least one matched data pair and to determine whether to calibrate the continuous glucose sensor responsive thereto.