Transmitter Unit Calibration for Analyte Sensor Sensitivity
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Solution Overview
Problem
Existing analyte monitoring systems face challenges in accommodating a range of sensor sensitivities and ensuring data processing and control for medical telemetry systems, particularly in continuous glucose monitoring, where flexibility and accuracy are crucial for reliable patient data analysis.
Innovation Solution
A method and apparatus for performing calibration routines, retrieving prior calibration parameters, comparing current and prior parameters, and determining stability status for in vivo analyte sensors, which includes features like ambient temperature compensation, digital anti-aliasing filtering, and outlier data point verification to ensure accurate glucose monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed calibration parameter is used for the analyte sensor, then the manufacturing process is simple, but the system cannot accommodate a range of sensor sensitivities
Solution Approach 1:
The system transitions from a static, fixed calibration parameter to a dynamic calibration process that automatically adjusts based on sensor characteristics. The transmitter unit performs iterative calibration routines, comparing current sensor responses against stored prior responses to dynamically determine optimal calibration parameters for each sensor's unique sensitivity range.
Solution Approach 2:
The calibration process incorporates feedback mechanisms where the transmitter unit receives sensor responses, compares them against expected values, and adjusts calibration parameters accordingly. The system uses feedback from multiple sensor readings to refine the calibration parameter selection, ensuring optimal performance across varying sensor sensitivities.
2Measurement precision
If calibration parameters are updated frequently to maintain accuracy, then measurement precision improves, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary calibration during the manufacturing process, establishing baseline sensor characteristics before deployment. This preliminary action reduces the need for extensive real-time calibration adjustments, allowing the system to achieve accurate measurements more quickly after sensor insertion while maintaining precision through periodic updates.
Solution Approach 2:
Instead of continuous calibration updates, the system employs periodic calibration routines that occur at predetermined intervals or when specific conditions are detected. This periodic approach maintains measurement precision while significantly reducing computational load and processing time compared to continuous adjustment methods.
3Reliability
If the system processes all sensor data without filtering, then data completeness is maintained, but data quality and reliability decrease due to outliers and errors
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor data quality metrics and adjust processing parameters accordingly. When outliers or errors are detected in sensor readings, the feedback system triggers recalibration routines or adjusts the threshold for data acceptance, maintaining high data quality while preserving as much valid information as possible through intelligent filtering rather than blanket exclusion.
Data Source
AI summary
Methods and apparatus for providing data processing and control for use in a medical communication system are provided.