Dynamic Insulin Sensitivity Segmentation for Glycemic Control
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Solution Overview
Problem
Conventional insulin pumps rely on a single, constant insulin sensitivity value, which fails to accurately adjust basal and bolus dosages in response to varying blood glucose levels and trends, leading to suboptimal glycemic control in diabetic patients.
Innovation Solution
The system adjusts insulin dosages based on blood glucose levels and trends, correlating specific glucose ranges and trends with corresponding insulin sensitivity values, using a processor to calculate bolus and basal doses, and allowing for dynamic adjustment of insulin delivery to maintain normoglycemia.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single constant insulin sensitivity value is used, then the device complexity is reduced, but the glycemic control precision deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from a static, constant insulin sensitivity value to a dynamic, time-varying sensitivity profile. The system divides the day into multiple time periods (e.g., morning, afternoon, evening, night) and assigns different insulin sensitivity values to each period, allowing the sensitivity parameter to change dynamically according to circadian rhythms and daily activities. This resolves the contradiction by introducing temporal variability without significantly complicating the overall device architecture.
Solution Approach 2:
The patent segments the daily insulin sensitivity profile into distinct time periods, each with its own sensitivity characteristics. By dividing the 24-hour cycle into multiple segments (e.g., 4-6 time periods), the system can independently optimize sensitivity values for each segment. This segmentation approach maintains manageable complexity while substantially improving glycemic control precision across different parts of the day.
2Reliability
If insulin sensitivity varies with blood glucose levels and time, then the glycemic control is improved, but the device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing insulin sensitivity values for different time periods before actual insulin dosing occurs. The system allows users to input or automatically determines sensitivity values for each time period in advance, and these pre-calculated values are then used during routine dosing calculations. This eliminates the need for real-time complex calculations while maintaining adaptive sensitivity adjustment, thereby improving reliability without significantly increasing operational complexity.
Solution Approach 2:
The patent changes the parameter of insulin sensitivity from a fixed value to a time-dependent variable. By introducing temporal dimension to sensitivity parameter, the system can accurately reflect physiological variations throughout the day. The dosage calculation algorithm is updated to retrieve the appropriate sensitivity value based on the current time period, enabling dynamic adaptation without requiring complex real-time modeling or calculation.
3Measurement precision
If basal and bolus dosages are dynamically adjusted, then the glycemic control precision is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent applies self-service by enabling the insulin pump to automatically adjust basal and bolus dosages based on pre-programmed sensitivity profiles and real-time glucose measurements, without requiring manual intervention for each adjustment. The system autonomously calculates appropriate dosages by retrieving the correct sensitivity values for the current time period and applying them to the dosing algorithm, reducing the operational burden on users while maintaining high precision in dosage control.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors blood glucose levels and compares them against target ranges, then automatically adjusts insulin delivery accordingly. The feedback loop operates by: (1) measuring current glucose, (2) determining the appropriate sensitivity value for the current time period, (3) calculating the required insulin dosage, and (4) delivering the insulin. This automated feedback process maintains precision while simplifying user interaction compared to manual adjustment methods.
Data Source
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AI summary
Systems, devices and methods are presented in the subject disclosure for recommending an insulin dose adapted for use with an insulin delivery device. In some embodiments, the method may include receiving blood glucose (BG) data, determining one or more insulin sensitivity (IS) values associated with the BG data, and determining an insulin dose based on the determined one or more IS values. A system for carrying out such a method is also presented.