Dynamic Glucose Display for Insulin Therapy Management
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Solution Overview
Problem
Current analyte monitoring and infusion systems for diabetes management face challenges in efficiently processing and adapting to real-time glucose data, leading to suboptimal insulin therapy adjustments and increased complexity in user interface management.
Innovation Solution
A system that includes real-time monitoring of analyte levels, dynamic modification of therapy profiles, and contextual-based dosage determination, utilizing a network of sensors, processors, and user interfaces to provide continuous data processing and adaptive insulin delivery recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and dynamic modification of therapy profiles is implemented, then insulin therapy management is enhanced and glucose control is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system segments therapy management into distinct components: basal profile management, bolus dosage calculation, and real-time monitoring. Each component processes specific aspects of glucose control independently, allowing the system to handle complex therapy requirements through modular, manageable segments rather than monolithic processing.
Solution Approach 2:
The system performs preliminary calculations and predictions of glucose levels before actual therapy administration. By anticipating future glucose trends based on current data and pre-calculating appropriate therapy adjustments, the system reduces the complexity of real-time decision-making while maintaining reliable glucose control.
2Adaptability or versatility
If continuous data processing and adaptive insulin delivery recommendations are provided, then therapy responsiveness is improved, but processing time and computational load increase
Solution Approach 1:
The system implements periodic data processing at strategically determined intervals rather than continuous processing. Therapy recommendations are updated at optimal moments based on glucose trend analysis and physiological patterns, maintaining high adaptability while reducing overall computational time and processing load.
Solution Approach 2:
The system processes only the critical subset of data necessary for accurate therapy recommendations rather than analyzing all available data points continuously. By focusing on key parameters and trends that most significantly impact insulin delivery decisions, the system achieves high adaptability with reduced processing time.
3Ease of operation
If graphical and visual feedback mechanisms are implemented, then user interaction complexity is reduced, but display requirements and interface complexity increase
Solution Approach 1:
The system employs color-coded visual feedback to represent different glucose states and therapy recommendations. Graphical displays use color variations to intuitively communicate glucose levels, trends, and alert conditions, allowing users to quickly comprehend complex therapy information without requiring sophisticated interface interactions.
Solution Approach 2:
The system creates simplified graphical representations and visual copies of complex physiological data and therapy parameters. By translating raw numerical data into intuitive visual formats such as graphs, icons, and visual trends, the system enhances ease of operation while managing interface complexity through effective data visualization rather than complex controls.
Data Source
AI summary
Method and system including displaying a first representation of a medication treatment parameter profile, displaying a first representation of a physiological profile associated with the medication treatment parameter profile, detecting a modification to a segment of the medication treatment parameter profile, displaying a modified representation of the medication treatment parameter profile and the physiological profile based on the detected modification to the segment of the medication treatment parameter profile, modifying an attribute of the first representation of the medication treatment parameter profile, and modifying an attribute of the first representation of the physiological profile are provided.