Control Algorithm Validation Using Real Glucose Reference Actions
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Solution Overview
Problem
Existing methods for validating control algorithms in diabetes treatment, such as clinical trials and simulators, are risky and time-consuming, potentially leading to incorrect insulin dosages that can cause hypoglycemia or hyperglycemia.
Innovation Solution
A method using real data from continuous glucose monitoring sensors to validate control algorithms by comparing action differences between the control algorithm and a reference algorithm, with an evaluation score based on predetermined targets, ensuring accuracy and safety without the need for simulators or clinical trials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If clinical trials are used to validate control algorithms, then the validation can be performed with real patient data, but the process is time-consuming and potentially dangerous for patients
Solution Approach 1:
The patent creates a virtual patient simulator that copies the essential characteristics of real patients through mathematical models. This virtual replica allows validation of control algorithms using synthetic patient data that mirrors real clinical scenarios, eliminating the need for actual human subjects while maintaining validation reliability. The simulator generates virtual patient states, insulin actions, and glucose responses that can be used for algorithm validation without exposing real patients to risk.
Solution Approach 2:
The patent performs preliminary validation of control algorithms using the virtual patient simulator before conducting actual clinical trials. By pre-validating algorithms on virtual patients with diverse characteristics and clinical scenarios, the system can identify and correct potential issues beforehand, ensuring safety and effectiveness before deployment to real patients. This preliminary validation phase significantly reduces the time required for subsequent clinical trials.
2Reliability
If clinical trials are used to validate control algorithms, then real patient data can be obtained, but the process is dangerous and requires patient monitoring
Solution Approach 1:
The patent creates a virtual patient simulator that copies the essential characteristics of real patients through mathematical models. This virtual replica allows validation of control algorithms using synthetic patient data that mirrors real clinical scenarios, eliminating the need for actual human subjects while maintaining validation reliability. The simulator generates virtual patient states, insulin actions, and glucose responses that can be used for algorithm validation without exposing real patients to risk.
Solution Approach 2:
The virtual patient simulator acts as an intermediary between the control algorithm validation process and real patients. Instead of directly testing algorithms on human subjects, the system uses the virtual simulator as a middle layer that provides realistic patient data and scenarios without the inherent safety risks of human experimentation. The simulator translates algorithm performance predictions into virtual patient outcomes, allowing safe preliminary validation.
3Loss of time
If simulators are used to validate control algorithms, then validation can be performed quickly, but the simulators contain modeling biases and are computationally expensive
Solution Approach 1:
The patent creates a virtual patient simulator that copies the essential characteristics of real patients through mathematical models. This virtual replica allows validation of control algorithms using synthetic patient data that mirrors real clinical scenarios, eliminating the need for actual human subjects while maintaining validation reliability. The simulator generates virtual patient states, insulin actions, and glucose responses that can be used for algorithm validation without exposing real patients to risk.
Solution Approach 2:
The patent employs parameter changes by adjusting model complexity and computational parameters to optimize the balance between validation speed and accuracy. The virtual patient simulator uses mathematical models with carefully selected parameters that capture essential physiological relationships while maintaining computational efficiency. By tuning model parameters and simulation resolution, the system achieves fast validation without sacrificing measurement precision, avoiding the computational expenses associated with more complex simulation approaches.
Data Source
Figure 1~2
AI summary
A method for validating a control algorithm, the method being implemented by a computer and comprising the steps of receiving a plurality of states (50); receiving a plurality of reference actions (52); receiving a plurality of reference outputs (54); processing the plurality of states (56); computing at least an action difference (58) consisting of computing at least a difference between at least one control action and at least one reference action; evaluating the at least an action difference (60) by computing at least an evaluation score; and validating the control algorithm (62), the control algorithm being validated if at least the evaluation score satisfies an evaluation score criteria.