Modular Diabetes Control Architecture for Glycemic Adaptation
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Solution Overview
Problem
People with diabetes face the challenge of maintaining strict glycemic control without increasing the risk of hypoglycemia, which requires efficient algorithms for automated insulin delivery in closed-loop control systems.
Innovation Solution
A modular architecture for diabetes control systems that includes biosystem observers providing glycemic state information and control modules responsible for basal rate, pre-meal, and correction insulin boluses, as well as hypoglycemia prevention, facilitated by a System Coordinator for integration and interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a modular architecture with multiple control modules is implemented, then system adaptability and ease of operation are improved, but device complexity increases
Solution Approach 1:
The control system is divided into separate modular components including a biosystem observer module, a system coordinator module, and multiple control modules (basal rate control, pre-meal bolus, correction bolus, hypoglycemia prevention). Each module operates independently with well-defined interfaces, allowing the system to handle complex diabetes management tasks through coordinated simple units rather than a single complex unit.
Solution Approach 2:
The modular architecture enables a single system to perform multiple diabetes control functions through different modules that can be activated as needed. The system can adapt to different patient needs and clinical scenarios by selecting appropriate module combinations, making the system universally applicable to various diabetes management requirements without requiring separate systems for each function.
2Ease of manufacture
If incremental testing and deployment of system features is enabled, then ease of manufacture and deployment are improved, but loss of time for system development increases
Solution Approach 1:
The system is structured as independent, testable modules that can be developed, tested, and deployed separately. Each module can be incrementally added to the system and tested in isolation or in combination with other modules, enabling staged deployment strategies where new features are introduced gradually rather than requiring complete system redesigns.
Solution Approach 2:
The modular design allows for preliminary testing and validation of individual modules before integration into the full system. Control modules can be developed and tested in advance using simulation environments and clinical data, with results evaluated before actual deployment, enabling proactive identification and resolution of issues rather than reactive fixes.
3Ease of operation
If separate control modules for different diabetes management functions are implemented, then ease of operation and user flexibility are improved, but device complexity increases
Solution Approach 1:
The system separates diabetes management functions into distinct control modules including basal rate control, pre-meal bolus calculation, correction bolus calculation, and hypoglycemia prevention. Each module handles a specific aspect of glucose control independently, allowing users to interact with and configure individual modules based on their specific needs without being overwhelmed by a monolithic complex system.
Solution Approach 2:
The system coordinator module serves as an intermediary that manages communication and coordination between the biosystem observer and various control modules. It handles the complexity of integrating multiple modules and presenting unified control decisions to the user, shielding users from the underlying system complexity while enabling flexible configuration of individual control strategies.
Data Source
AI summary
A structure, method, and computer program product for a diabetes control system provides, but is not limited thereto, the following: open-loop or closed-loop control of diabetes that adapts to individual physiologic characteristics and to the behavioral profile of each person. An exemplary aspect to this adaptation is biosystem (patient or subject) observation and modular control. Consequently, established is the fundamental architecture and the principal components for a modular system, which may include algorithmic observers of patients' behavior and metabolic state, as well as interacting control modules responsible for basal rate, insulin boluses, and hypoglycemia prevention.