Analyte Sensor Calibration Timing Optimization
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Solution Overview
Problem
Existing analyte monitoring systems require frequent calibration of analyte sensors, which often involves painful blood glucose measurements, necessitating a more efficient calibration method to minimize the number of such measurements while maintaining sensor accuracy.
Innovation Solution
The system optimizes analyte sensor calibration by receiving current blood glucose measurements, determining temporal proximity to scheduled calibration events, and initiating a calibration routine when proximity is within a predetermined time period, thereby reducing the need for additional blood glucose measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If analyte sensors are calibrated according to a fixed schedule, then sensor accuracy is maintained, but the frequency of painful blood glucose measurements increases
Solution Approach 1:
The calibration schedule is made dynamic by adjusting the timing of calibration events based on real-time sensor performance monitoring. The system evaluates sensor drift and accuracy in between scheduled calibrations, then modifies the calibration schedule accordingly, allowing flexibility to reduce unnecessary calibrations while maintaining accuracy.
Solution Approach 2:
The system implements continuous feedback by monitoring sensor performance between calibrations and using this information to determine when actual calibration is needed. This feedback loop replaces the rigid fixed schedule with an adaptive approach that responds to real-time sensor conditions, reducing the frequency of blood glucose measurements while preserving accuracy.
2Reliability
If frequent calibration routines are performed, then sensor accuracy is maintained, but user comfort decreases due to frequent blood glucose measurements
Solution Approach 1:
The system dynamically adjusts calibration timing based on actual sensor performance rather than following a rigid schedule. By monitoring sensor drift and accuracy in real-time, the system can extend the time between calibrations when sensor performance remains stable, thereby improving user comfort while maintaining accuracy through performance-based decision making.
Solution Approach 2:
The system performs self-evaluation of sensor performance between calibrations, automatically determining when calibration is needed based on monitored accuracy and drift. This self-service capability eliminates the need for users to blindly follow fixed schedules, allowing the system to optimize calibration timing for both accuracy and user comfort.
3Device complexity
If a fixed calibration schedule is used, then calibration timing is simple to manage, but the number of required blood glucose measurements increases unnecessarily
Solution Approach 1:
The system uses feedback from continuous sensor monitoring to determine actual calibration needs. By evaluating sensor performance in between scheduled calibrations, the system can identify when calibrations can be safely delayed or cancelled, reducing the total number of blood glucose measurements while maintaining manageable calibration processes through automated decision making.
Solution Approach 2:
The system changes the parameter of calibration timing from a fixed schedule to a performance-based dynamic schedule. By monitoring sensor drift and accuracy parameters in real-time, the system adjusts calibration timing to minimize blood glucose measurements while maintaining accuracy, transforming a quantity-driven approach to a quality-driven approach.
Data Source
AI summary
Method and apparatus for optimizing analyte sensor calibration including receiving a current blood glucose measurement, retrieving a time information for an upcoming scheduled calibration event for calibrating an analyte sensor, determining temporal proximity between the current blood glucose measurement and the retrieved time information for the upcoming calibration event, initiating a calibration routine to calibrate the analyte sensor when the determined temporal proximity is within a predetermined time period, and overriding the upcoming scheduled calibration event using the current blood glucose measurement are provided.