Closed-Loop Insulin Delivery Without Recent Behavioral Input
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Solution Overview
Problem
People with diabetes face a significant cognitive and emotional burden in managing their intensive medicine therapy, particularly in delivering the correct amount of insulin at the right time, which requires frequent dosing determinations and recalibration of therapeutic parameters based on various individual factors.
Innovation Solution
A method that involves receiving previous insulin delivery data from an insulin pump and estimated glucose data from a continuous glucose monitor, determining an insulin delivery amount based on this data to bring the estimated glucose closer to a target value without using user-specific behavioral data entered through a user interface within the previous 6 hours, and communicating this amount to the insulin pump.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual insulin dosing is used with frequent user input of behavioral data, then glycemic control can be achieved, but cognitive burden and error risk increase significantly
Solution Approach 1:
The system automatically determines insulin dosing without requiring user input of behavioral data. The insulin pump and glucose monitor work together to self-adjust insulin delivery based on glucose readings, eliminating the need for users to manually track and input meal, exercise, and stress information while maintaining effective glycemic control
Solution Approach 2:
The system continuously monitors glucose levels and uses this feedback to automatically adjust insulin dosing. The closed-loop control system processes glucose data and insulin delivery data to determine optimal dosing, creating a self-regulating system that responds to changing physiological conditions without user intervention
2Ease of operation
If automated insulin delivery is implemented without requiring user-specific behavioral data, then ease of operation improves, but the system must rely solely on historical data and glucose readings
Solution Approach 1:
The system extracts and eliminates the requirement for user input of behavioral data from the insulin dosing process. By removing this input requirement, the system simplifies operation for users while the automated data processing handles the complexity of determining appropriate insulin doses based solely on glucose and insulin delivery history
Solution Approach 2:
The system creates a universal insulin dosing algorithm that works across different users without requiring user-specific behavioral inputs. The same automated process handles all users by processing their individual glucose and insulin delivery data, making the system broadly applicable while maintaining personalized dosing through automated analysis
Data Source
AI summary
Some embodiments include burden-free insulin delivery systems and methods. In some embodiments, a method may include receiving previous insulin delivery data at a user device from an insulin pump; receiving estimated glucose data at the user device from a continuous glucose monitor; determining an insulin delivery amount based on the previous insulin delivery data and the estimated glucose data to bring the estimated glucose data closer to a target glucose value without using any user-specific behavioral data physically entered by a user through a user interface of the user device within a previous period of time, the previous period of time being less than six hours; and communicating the insulin delivery amount to the insulin pump.