Closed loop control and signal attenuation detection

• US 9,392,969 B2
• Filed: 08/31/2008
• Issued: 07/19/2016
• Est. Priority Date: 08/31/2008
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories)
• Inventors: Hayter, Gary, Budiman, Erwin S.
• Primary Examiner(s): Mehta, Bhisma
• Assistant Examiner(s): LEE, BRANDY SCOTT
• Application Number:
  US12/202,304
• Publication Number:
  US 20100057057A1
• Time in Patent Office: 2,879 Days
• Field of Search: 604/131, 604/65, 604/66
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• 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 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 2205/3507 with implanted devices, e.g. external control
• CPC Class Codes: A61M 2205/50 with microprocessors or computers
• CPC Class Codes: A61M 2205/581 by audible feedback
• CPC Class Codes: A61M 2205/582 by tactile feedback
• CPC Class Codes: A61M 2205/583 by visual feedback
• CPC Class Codes: A61M 2205/702 automatically during use
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/142 Pressure infusion, e.g. using pumps
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 20/17 delivered via infusion or injection

Abstract

Methods, system and devices for monitoring a plurality of parameters associated with a closed loop control operation including continuously monitoring a physiological condition and automatic administration of a medication, detecting a signal level associated with the monitored physiological condition deviating from a predetermined threshold level, retrieving the medication level administered associated with a time period of the detected signal level, applying the retrieved medication level to the detected signal based on a predefined predictive model to generate a predictive signal, and comparing the detected signal to the predictive signal to determine whether a condition associated with the detected signal level is present are provided.

Claims

1. A method, comprising:

continuously monitoring a physiological condition and an automatic administration of a medication in a closed loop control operation, wherein monitoring the physiological condition comprises monitoring a signal level associated with the physiological condition;

detecting a deviation of the monitored signal level from a predetermined threshold level;

retrieving an administered medication level associated with a time period where the deviation of the monitored signal level occurred;

generating a predictive signal level with a predefined predictive model by using, at least, the retrieved administered medication level and the monitored signal level;

comparing the monitored signal level to the predictive signal level; and

using the comparison to determine whether a condition associated with the deviation of the monitored signal level is present.

2. The method of claim 1, wherein the monitored signal level is associated with an analyte level and the condition associated with the deviation of the monitored signal level is an early signal attenuation condition.

3. The method of claim 1, wherein the condition is a signal attenuation level that is below a predetermined level.

4. The method of claim 1, wherein the condition associated with the deviation of the monitored signal level is an adverse signal condition, the method comprising executing a corrective procedure if the adverse signal condition is determined to be present.

5. The method of claim 4, wherein the adverse signal condition is associated with an impending hypoglycemic condition.

6. The method of claim 4, further comprising asserting a notification associated with the adverse signal condition.

7. The method of claim 4, wherein the corrective procedure includes calibration of an analyte sensor.

8. The method of claim 4, wherein executing the corrective procedure includes waiting a predetermined time period to confirm a presence of the adverse signal condition prior to executing the corrective procedure.

9. The method of claim 4, wherein the predictive model includes a predictive algorithm that describes a glucose response or behavior based at least in part on meal intake or exercise events.

10. The method of claim 1, wherein the physiological condition is continuously monitored using an analyte sensor comprising a plurality of electrodes including a working electrode, wherein the working electrode comprises an analyte-responsive enzyme and a mediator, wherein at least one of the analyte-responsive enzyme and the mediator is chemically bonded to a polymer disposed on the working electrode, and wherein at least one of the analyte-responsive enzyme and the mediator is crosslinked with the polymer.

11. A device, comprising:

one or more processors; and

a memory operatively coupled to the one or more processors, the memory storing instructions which, when executed by the one or more processors, cause the one or more processors to;

continuously monitor a physiological condition and an automatic administration of a medication in a closed loop control operation, wherein the continuous monitoring of the physiological condition comprises monitoring a signal level associated with the physiological condition;

detect a deviation of the monitored signal level from a predetermined threshold level;

retrieve an administered medication level associated with a time period where the deviation of the monitored signal level occurred;

generate a predictive signal level with a predefined predictive model that uses, at least, the retrieved administered medication level and the monitored signal level;

compare the monitored signal level to the predictive signal level; and

use the comparison to determine whether a condition associated with the deviation of the monitored signal level is present.

12. The device of claim 11, wherein the condition associated with the deviation of the monitored signal level is a signal attenuation level below a predetermined level.

13. The device of claim 11, wherein the instructions, when executed by the one or more processors, cause the one or more processors to execute a corrective procedure if the condition associated with the deviation of the monitored signal level is determined to be present.

14. The device of claim 13, wherein the corrective procedure includes calibration of an analyte sensor.

15. The device of claim 13, wherein the instructions, when executed by the one or more processors, cause the one or more processors to wait a predetermined time period to confirm a presence of the condition associated with the deviation of the monitored signal level prior to executing the corrective procedure.

16. The device of claim 11, wherein the condition associated with the deviation of the monitored signal level is an impending hypoglycemic condition.

17. The device of claim 11, wherein the predictive model includes a predictive algorithm that describes a glucose response or behavior based at least in part on meal intake or exercise events.

18. The device of claim 11, wherein the physiological condition is continuously monitored using an analyte sensor comprising a plurality of electrodes including a working electrode, wherein the working electrode comprises an analyte-responsive enzyme and a mediator, wherein at least one of the analyte-responsive enzyme and the mediator is chemically bonded to a polymer disposed on the working electrode, and wherein at least one of the analyte-responsive enzyme and the mediator is crosslinked with the polymer.