Unified Insulin Control System for Hypoglycemia Prevention
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Solution Overview
Problem
Current diabetes management systems with automatic basal insulin control using MPC algorithms fail to account for manual bolus doses, leading to potential hypoglycemic excursions due to independent operation of both control processes.
Innovation Solution
A diabetes management system that integrates automatic basal insulin control with manual bolus insulin control by using physiological data to modify or cancel manual bolus doses, ensuring consistent glycemic control by correlating both processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic basal insulin control and manual bolus insulin control operate independently, then each control process can function autonomously, but the risk of excessive insulin delivery and hypoglycemic events increases
Solution Approach 1:
The patent merges automatic basal insulin control and manual bolus insulin control into a unified control system. The controller integrates both control processes, allowing them to operate autonomously while maintaining coordination through shared physiological data and centralized decision-making logic, thereby preventing excessive insulin delivery.
Solution Approach 2:
The system implements feedback mechanisms where the controller continuously monitors physiological data and adjusts both basal and bolus insulin delivery based on real-time glucose levels and predicted future glucose trends. This feedback loop ensures that automatic and manual control processes remain coordinated and prevent hypoglycemic events.
2Speed
If manual bolus insulin dose is administered without considering automatic basal control, then patient can quickly respond to glucose changes, but total insulin dose may exceed requirements causing hypoglycemia
Solution Approach 1:
The controller performs preliminary calculations of predicted future glucose levels before administering bolus insulin. By anticipating future glucose trends and the impact of basal insulin delivery, the system adjusts bolus dosing in advance to prevent hypoglycemia while maintaining rapid response capability.
Solution Approach 2:
The system applies preliminary anti-action by calculating the expected effect of automatic basal control and adjusting the manual bolus dose accordingly before administration. This preemptive adjustment prevents the harmful effect of excessive total insulin delivery while preserving the speed benefit of manual bolus response.
3Measurement precision
If automatic control algorithm adjusts insulin delivery based on glucose trends, then glycemic control precision improves, but complexity of control system increases
Solution Approach 1:
The control algorithm is segmented into distinct functional modules: a model predictive control component for calculating predicted future glucose levels, a basal control component for automatic baseline insulin delivery, and a bolus control component for meal-time insulin adjustment. This segmentation maintains high precision while managing system complexity through modular design.
Data Source
AI summary
Systems and methods for diabetes management with automatic basal and manual bolus insulin control are presented. An exemplary system includes a delivery device, a glucose sensor, and a controller. The delivery device delivers insulin and the glucose sensor measures glucose levels of the subject. A basal insulin dose is calculated using a model predictive control algorithm and physiological data of the subject including desired glucose levels, amounts of the delivered insulin and the measured glucose levels. A manual bolus insulin dose is initiated by the subject. The manual bolus insulin dose is modified based on one or both of the model predictive control algorithm and the physiological data of the subject. A total insulin dose is determined based on the modified manual bolus insulin dose and the calculated basal insulin dose, and delivered to the subject.