Fully automated control system for type 1 diabetes
First Claim
1. A system for automatic control of blood glucose level of a subject, comprising:
- a glucose sensor operative to continually sense a glucose level of the subject and generate a corresponding glucose level signal;
a delivery device operative to deliver doses of insulin to the subject in response to an insulin dose control signal; and
a controller operative to generate the insulin dose control signal as a function of the weight of the subject and time-varying glucose levels of the subject as represented by the glucose level signal over time, the controller employing a control algorithm including;
generating the insulin dose control signal based on (a) the glucose level signal, and (b) accumulation of insulin in the subject due to finite rate of utilization,wherein the controller employs a model-predictive control algorithm by which the insulin dose control signal is generated as a value optimizing an objective function with objectives of (a) a weighted integration of a difference between a predicted glucose level signal and a setpoint signal over a time horizon, and (b) a weighted integration of the insulin dose control signal over the time horizon.
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Abstract
An augmented, adaptive algorithm utilizing model predictive control (MPC) is developed for closed-loop glucose control in type 1 diabetes. A linear empirical input-output subject model is used with an MPC algorithm to regulate blood glucose online, where the subject model is recursively adapted, and the control signal for delivery of insulin and a counter-regulatory agent such as glucagon is based solely on online glucose concentration measurements. The MPC signal is synthesized by optimizing an augmented objective function that minimizes local insulin accumulation in the subcutaneous depot and control signal aggressiveness, while simultaneously regulating glucose concentration to a preset reference set point. The mathematical formulation governing the subcutaneous accumulation of administered insulin is derived based on nominal temporal values pertaining to the pharmacokinetics (timecourse of activity) of insulin in human, in terms of its absorption rate, peak absorption time, and overall time of action.
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Citations
45 Claims
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1. A system for automatic control of blood glucose level of a subject, comprising:
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a glucose sensor operative to continually sense a glucose level of the subject and generate a corresponding glucose level signal; a delivery device operative to deliver doses of insulin to the subject in response to an insulin dose control signal; and a controller operative to generate the insulin dose control signal as a function of the weight of the subject and time-varying glucose levels of the subject as represented by the glucose level signal over time, the controller employing a control algorithm including; generating the insulin dose control signal based on (a) the glucose level signal, and (b) accumulation of insulin in the subject due to finite rate of utilization, wherein the controller employs a model-predictive control algorithm by which the insulin dose control signal is generated as a value optimizing an objective function with objectives of (a) a weighted integration of a difference between a predicted glucose level signal and a setpoint signal over a time horizon, and (b) a weighted integration of the insulin dose control signal over the time horizon. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A method for automatic control of the blood glucose level of a subject, comprising:
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continually sensing a glucose level of the subject and generating a corresponding glucose level signal; operating a delivery device to deliver doses of insulin to the subject in response to an insulin dose control signal; and generating the insulin dose control signal as a function of the weight of the subject and time-varying glucose levels of the subject as represented by the glucose level signal over time, by a control algorithm including; generating the insulin dose control signal based on (a) the glucose level signal, and (b) accumulation of insulin in the subject due to finite rate of utilization, wherein the control algorithm includes a model-predictive control algorithm by which the insulin dose control signal is generated as a value optimizing an objective function with objectives of (a) a weighted integration of a difference between a predicted glucose level signal and a setpoint signal over a time horizon, and (b) a weighted integration of the insulin dose control signal over the time horizon. - View Dependent Claims (24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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43. A controller for use in a system for automatic control of blood glucose level of a subject, the controller being operative to generate an insulin dose control signal as a function of the weight of the subject and time-varying glucose levels of the subject as represented by an glucose level signal over time, the glucose level signal being generated by a glucose sensor operative to continually sense a glucose level of the subject, the insulin dose control signal controlling the delivery of doses of insulin to the subject by a delivery device, the controller employing a control algorithm including:
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generating the insulin dose control signal based on (a) the glucose level signal, and (b) accumulation of insulin in the subject due to finite rate of utilization, wherein the control algorithm includes a model-predictive control algorithm by which the insulin dose control signal is generated as a value optimizing an objective function with objectives of (a) a weighted integration of a difference between a predicted glucose level signal and a setpoint signal over a time horizon, and (b) a weighted integration of the insulin dose control signal over the time horizon. - View Dependent Claims (44, 45)
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Specification