Glucose Sensor Calibration Using Insulin Kinetics
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Solution Overview
Problem
Existing continuous glucose monitoring systems face challenges in accurately calibrating glucose sensors due to the impact of insulin delivery on glucose monitoring functions.
Innovation Solution
The implementation of methods and systems that utilize insulin delivery information and associated parameters to improve the calibration accuracy of continuous glucose monitoring systems, including the use of control algorithms and physiological models to determine optimal calibration conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If calibration is performed during insulin delivery, then glucose monitoring can be maintained, but calibration accuracy deteriorates due to insulin's impact on glucose levels
Solution Approach 1:
The system performs preliminary assessment of calibration suitability by evaluating multiple parameters (glucose rate of change, insulin delivery amount, time since insulin administration) before executing calibration. This preliminary action prevents calibration during periods when insulin delivery would compromise accuracy, while still allowing calibration when conditions are favorable, thus maintaining both reliability and precision.
Solution Approach 2:
The calibration system dynamically adjusts its operation based on real-time insulin delivery parameters and glucose kinetics. The system modifies calibration timing and parameters according to the current physiological state, transitioning between calibrated and uncalibrated modes as needed. This dynamic approach allows the system to maintain calibration accuracy despite the presence of insulin delivery by adapting the calibration process to the current metabolic state.
2Measurement precision
If calibration is delayed until insulin delivery completes, then calibration accuracy improves, but monitoring duration is reduced
Solution Approach 1:
The system performs preliminary assessment of calibration suitability by evaluating multiple parameters (glucose rate of change, insulin delivery amount, time since insulin administration) before executing calibration. This preliminary action prevents calibration during periods when insulin delivery would compromise accuracy, while still allowing calibration when conditions are favorable, thus maintaining both reliability and precision.
Solution Approach 2:
The calibration system dynamically adjusts its operation based on real-time insulin delivery parameters and glucose kinetics. The system modifies calibration timing and parameters according to the current physiological state, transitioning between calibrated and uncalibrated modes as needed. This dynamic approach allows the system to maintain calibration accuracy despite the presence of insulin delivery by adapting the calibration process to the current metabolic state.
Data Source
AI summary
Systems, methods and apparatus are provided, including one or more processors configured to detect a sensor calibration start event, determine outputs of one or more physiological models based on a plurality of parameters, the plurality of parameters including glucose data and insulin information, determine whether the outputs fall within a predetermined threshold, and in response to determining that the outputs fall within the predetermined threshold, execute a calibration routine.


