Wearable Insulin Pump Onboarding via Subjective Coefficient Mapping
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Solution Overview
Problem
The complexity of insulin pump parameter settings for automatic insulin delivery algorithms can lead to user error and inconvenience, as they require technical knowledge and may not provide optimal outcomes for individuals with varying insulin sensitivities.
Innovation Solution
A computing apparatus and method that allows users to input subjective insulin need parameters through a graphical user interface, which modifies a subjective coefficient value to set specific factors for the automatic insulin delivery algorithm, enabling more personalized and intuitive insulin dosage determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are required to provide complex technical parameters for AID algorithm initialization, then the insulin delivery accuracy may be improved, but the ease of operation deteriorates and user error risk increases
Solution Approach 1:
The patent introduces an intermediary mapping relationship between simple user inputs (demographic parameters like weight, age, gender) and complex technical parameters (insulin sensitivity factors, basal rates). The system acts as a mediator that automatically calculates and sets appropriate technical parameters based on user-provided demographic information, eliminating the need for users to directly input complex medical parameters while maintaining delivery accuracy
Solution Approach 2:
The system transforms the parameter input paradigm by changing from direct technical parameter input to demographic parameter input. By using demographic parameters as proxies, the system achieves parameter simplification while maintaining the ability to derive accurate insulin delivery settings through automated calculations based on population-based relationships
2Ease of operation
If demographic parameters are used for simplifying the onboarding process, then the ease of operation is improved, but the reliability deteriorates due to insufficient personalization
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing population-based relationships between demographic parameters and insulin sensitivity factors. During onboarding, it leverages these pre-computed relationships to quickly derive personalized parameters from simple demographic inputs, providing both simplicity and reliability through advance preparation of reference data
Solution Approach 2:
The system incorporates feedback mechanisms that allow users to provide subjective insulin need assessments and physiological responses. This feedback loop enables continuous refinement and personalization of the initial demographic-based settings, ensuring reliability by adapting to individual user responses and adjusting parameters accordingly
3Adaptability or versatility
If multiple technical parameters are required for AID algorithm configuration, then the adaptability to individual user needs may be improved, but the device complexity increases
Solution Approach 1:
The patent extracts and separates the complexity from the user interface by removing the need for users to directly configure complex technical parameters. The system extracts only the essential demographic information needed for personalization and handles all complex parameter derivation internally, achieving adaptability without exposing device complexity to the user
Data Source
AI summary
Disclosed are a computing apparatus, a computer-readable medium and a method that enable a user to use subjective inputs to alter settings of a wearable automatic drug delivery system. A user input device is presented on a graphical user interface that enables input of a subjective insulin need parameter. In response to receiving the input, the processor may modify a subjective coefficient value. A specific factor useable by an automatic insulin delivery algorithm is set based on the subjective coefficient value. Physiological condition data related to the user and the set specific factor may be used to determine a dosage of insulin to be delivered to the user based on the collected physiological condition data of the user. The processor may cause the determined dosage of insulin to be delivered to the user based on an output of the automatic insulin delivery algorithm.