Control model for artificial pancreas
AssigneePresident and Fellows of Harvard College
InventorsEyal DASSAU, Dawei SHI, Francis J. DOYLE III
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Abstract
A multivariate parameter adaptation approach is disclosed for long-term use of an artificial pancreas using a dual-layer control scheme. The adaptation problem, which can be treated as an optimization problem with an unknown objective function and constraints, may be solved by the proposed BO-assisted multivariate optimization approach. Results showed that the algorithm was able to identify the improperly tuned parameters and smoothly adjust them for improved glucose regulation, despite lifestyle disturbances.
Claims17
A system for managing the glucose of a patient, the system comprising:
- an artificial pancreas comprising a pump configured to deliver insulin into a patient;
- a memory containing machine readable medium comprising machine executable code having stored thereon;
- a glucose sensor configured to output glucose readings based on the blood glucose level of the patient;
- a memory containing machine readable medium comprising machine executable code having stored thereon;
- a control system coupled to the memory comprising one or more processors, the control system configured to execute the machine executable code to cause the control system to:
- periodically update a carbohydrate parameter of a control model based on a set of postprandial glucose readings previously output from the glucose sensor over a first time period;
- periodically update a basal rate parameter of the control model based on a set of fasting glucose readings previously output from the glucose sensor over a second time period;
- receive a set of glucose readings output from the glucose sensor;
- periodically process the set of glucose readings with the control model to determine an amount of insulin to deliver;
- and
- send a command to the artificial pancreas to deliver the amount of insulin using the pump.
A method of managing the glucose of a patient, the method comprising:
- updating a carbohydrate parameter of a control model based on a set of postprandial glucose readings previously output from the glucose sensor over a first time period;
- updating a basal rate parameter of the control model based on a set of fasting glucose readings previously output from the glucose sensor over a second time period;
- receiving a set of glucose readings output from the glucose sensor;
- processing the set of glucose readings with the control model to determine an amount of insulin to deliver;
- and
- sending a command to the artificial pancreas to deliver the amount of insulin using the pump.
The method of claim 15, wherein updating a carbohydrate parameter and a basal rate parameter is performed weekly.
The method of claim 15, wherein processing the set of glucose readings with the control model to determine an amount of insulin to deliver is performed at least two times a day.
A non-transitory machine readable medium having stored thereon instructions for performing a method comprising machine executable code which when executed by at least one machine, causes the machine to:
- periodically update a carbohydrate parameter of a control model based on a set of postprandial glucose readings previously output from the glucose sensor over a first time period;
- periodically update a basal rate parameter of the control model based on a set of fasting glucose readings previously output from the glucose sensor over a second time period;
- receive a set of glucose readings output from the glucose sensor;
- periodically process the set of glucose readings with the control model to determine an amount of insulin to deliver;
- and
- send a command to the artificial pancreas to deliver the amount of insulin using the pump.
Dependencies are inferred from the claim text.