Analyte Sensor Mismatch Correction via Signal Transformation
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Solution Overview
Problem
Implantable glucose sensors face accuracy issues due to temporal mismatch between electrodes, leading to systematic errors in blood glucose measurement, which can be caused by differences in temporal response characteristics, material properties, and membrane structures, affecting the reliability of continuous glucose monitoring systems.
Innovation Solution
The implementation of a method and apparatus that utilize computerized logic to correct for temporal mismatch between sensors by applying mathematical transformations to align the responses of differential sensor pairs, allowing for more accurate blood glucose concentration determination through dynamic compensation during operation within a living subject.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If differential sensor pairs are used to measure analyte concentration, then measurement capability is improved, but temporal mismatch between electrodes introduces systematic errors that worsen measurement precision
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the time constant of one electrode signal to match the other electrode's time constant. This involves calculating a scaling factor based on the ratio of the two time constants and applying this factor to rescale the transformed signal, thereby aligning the temporal responses and eliminating systematic errors caused by temporal mismatch.
Solution Approach 2:
The patent implements feedback by continuously monitoring the temporal response characteristics of both electrodes and dynamically adjusting the transformation parameters accordingly. The system calculates the time constants from the sensor signals, determines the mismatch, applies the appropriate mathematical transformation, and iteratively refines the correction to maintain accurate measurements despite changing conditions.
2Measurement precision
If mathematical transformations are applied to correct temporal mismatch, then measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent replaces complex mechanical or hardware synchronization mechanisms with mathematical transformations. Instead of physically adjusting electrode responses through hardware modifications, the system uses software-based signal processing including filtering, transformation, and time constant scaling to achieve temporal alignment, thereby reducing device complexity while maintaining measurement accuracy.
3Duration of action of stationary object
If dynamic compensation is applied during operation, then reliability of extended monitoring is improved, but processing requirements and energy consumption increase
Solution Approach 1:
The patent applies dynamics by implementing real-time adaptive compensation that continuously adjusts to changing sensor characteristics during operation. The system dynamically calculates time constants from incoming signals, determines appropriate transformation parameters, and applies corrections on-the-fly, allowing the sensor to maintain accuracy over extended periods despite drift or environmental changes.
Data Source
AI summary
Apparatus and methods for response modeling and correction of signals associated with a parameter sensor. In one exemplary embodiment, the parameter sensor is configured to measure a physiologic analyte of a living being (e.g., blood glucose), and the apparatus and methods employ a mathematical transformation of two or more sensing elements (electrodes) of the sensor in order to compensate for temporal response differences or “mismatch.” This compensation enables the calculated blood analyte level, which results from processing of the signals of the two or more sensing electrodes, to be more accurate than calculations made without such compensation. In one variant, the parameter signals are generated, and compensation processing conducted, autonomously via a common implanted sensor platform.