Adaptive zone model predictive control with a glucose and velocity dependent dynamic cost function for an artificial pancreas
US-12128212-B2 · Oct 29, 2024 · US
US9392969B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9392969-B2 |
| Application number | US-20230408-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 31, 2008 |
| Priority date | Aug 31, 2008 |
| Publication date | Jul 19, 2016 |
| Grant date | Jul 19, 2016 |
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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.
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What is claimed is: 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.
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