Adaptive Glucose Sensor Initialization for Faster Equilibration
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Solution Overview
Problem
Existing glucose sensors use a fixed initialization sequence that does not account for manufacturing variations and environmental conditions, leading to performance variability and reduced longevity, with inaccurate readings during the stabilization period.
Innovation Solution
Adjust the initialization sequence of glucose sensors based on parameters related to manufacturing and environmental conditions, such as platinum surface area ratio, glucose oxidase activity, and interstitial fluid glucose levels, to optimize sensor equilibration and stabilize current flow more quickly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed initialization sequence is used for all glucose sensors, then the device complexity is reduced and ease of manufacture is improved, but performance variability increases and reliability deteriorates due to manufacturing variations
Solution Approach 1:
The patent adjusts initialization parameters (voltage levels, pulse durations, timing intervals) based on manufacturing parameters (platinum surface area ratio, glucose oxidase activity) to optimize sensor performance. This resolves the contradiction by allowing parameter customization that maintains reliability while accounting for manufacturing variations.
Solution Approach 2:
The initialization sequence is made dynamic and adjustable rather than fixed. The system can modify initialization parameters based on measured manufacturing variations and environmental conditions, transforming a static process into an adaptive one that maintains performance across different sensor units.
2Device complexity
If a fixed initialization sequence is used for all glucose sensors, then the device complexity is reduced, but the initialization time increases due to lack of optimization for individual sensors
Solution Approach 1:
By adjusting initialization parameters based on manufacturing data, the system optimizes equilibration speed for each sensor type, reducing initialization time without requiring complex real-time adaptation mechanisms.
Solution Approach 2:
Manufacturing parameters are measured and stored in advance, allowing the initialization sequence to be pre-optimized for each sensor batch or unit. This preliminary characterization enables faster initialization without adding complexity during the actual initialization process.
3Ease of operation
If a fixed initialization sequence is used, then ease of operation is improved, but accuracy deteriorates during the stabilization period due to environmental conditions
Solution Approach 1:
Initialization parameters are adjusted based on environmental conditions (temperature, pH, glucose concentration) to optimize equilibration speed and accuracy. This maintains ease of operation while improving measurement precision during the critical stabilization period.
Solution Approach 2:
The system measures environmental conditions and manufacturing parameters, then uses this feedback to adjust initialization parameters. This closed-loop approach ensures accurate readings while maintaining simple operation for the end user.
4Reliability
If the initialization sequence is extended to account for manufacturing variations, then reliability is improved, but the loss of time increases due to longer equilibration periods
Solution Approach 1:
Rather than extending initialization time, the system changes initialization parameters (voltage, pulse structure) to achieve faster equilibration while maintaining performance consistency across different manufacturing variations.
Solution Approach 2:
The initialization sequence adapts its duration and parameters based on sensor characteristics, allowing some sensors to complete initialization faster while others take longer, optimizing the overall process without compromising reliability.
5Device complexity
If manufacturing variations are not accounted for, then device complexity is reduced, but productivity decreases due to slower overall initialization across sensor batches
Solution Approach 1:
By adjusting initialization parameters based on manufacturing data, the system optimizes equilibration speed for each sensor type, increasing overall batch throughput without requiring complex individualized initialization routines.
Solution Approach 2:
The system uses universal initialization procedures for groups of sensors with similar manufacturing characteristics, achieving high throughput while accounting for variations through parameter adjustment rather than individual customization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the time to accurate glucose readings, improves sensor longevity, and enhances user satisfaction by ensuring quicker and more reliable glucose monitoring.
Implementation Method 1
the electrical current (iSig) flowing through the sensing (e.g., working) electrode of a glucose sensor is indicative of the blood glucose level in the patient's interstitial fluid
Implementation Method 2
the current (iSig) behavior of the glucose sensor is not stable until the chemistry stack has reached equilibrium
Data Source
AI summary
An example method for initializing a glucose sensor includes executing an initialization sequence for the glucose sensor, wherein the initialization sequence is based on one or more of parameters related to manufacturing the glucose sensor or environmental conditions of the glucose sensor that are present in vivo, and reporting glucose levels in a patient after the initialization sequence.