Analyte Sensor Impedance Detection for Calibration Drift
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Solution Overview
Problem
Existing analyte sensors, particularly glucose monitors, face challenges in maintaining accuracy and detecting damage or faults without relying on frequent in vivo calibration, which is inconvenient and costly.
Innovation Solution
Utilizing impedance measurements to calibrate and compensate for sensor drift, detect damage, and reduce the need for in vivo calibration by determining impedance values through electronic measurements, allowing for factory calibration and real-time sensitivity estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in vivo calibration is performed frequently to maintain sensor accuracy, then measurement precision is improved, but loss of time and patient convenience deteriorate
Solution Approach 1:
The sensor is calibrated during manufacturing with reference electrodes before being implanted or used by the patient. This preliminary calibration establishes baseline sensitivity values that eliminate the need for frequent in vivo calibration procedures, allowing the sensor to maintain accuracy without requiring repeated time-consuming calibration events during patient use
Solution Approach 2:
The system continuously monitors impedance values and sensitivity changes over time, using this feedback to detect when calibration drift occurs. By monitoring the relationship between impedance and sensitivity, the system can identify when factory calibration values need adjustment without requiring full recalibration, thus reducing the frequency of time-consuming calibration events while maintaining measurement precision
2Reliability
If in vivo calibration is performed frequently to detect sensor damage, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system continuously monitors impedance values and compares them against expected ranges to detect sensor damage or malfunction. This automated feedback mechanism provides reliable damage detection without requiring user intervention or calibration procedures, maintaining ease of operation while improving reliability through continuous monitoring
Solution Approach 2:
The sensor system performs self-diagnosis by monitoring its own impedance characteristics and sensitivity responses. The system automatically detects when damage occurs and can alert the user or system, eliminating the need for users to perform manual calibration or assessment procedures to check for sensor damage, thus improving reliability without compromising ease of operation
3Loss of time
If impedance measurements are used to reduce calibration frequency, then loss of time is reduced, but measurement precision may deteriorate
Solution Approach 1:
The system uses impedance measurements as feedback to track sensitivity changes over time. By continuously monitoring impedance and comparing it to factory calibration values, the system can detect when drift occurs and adjust measurements accordingly, maintaining precision without requiring frequent full calibration events
Solution Approach 2:
The system changes from fixed factory calibration to dynamic calibration that adapts based on measured impedance values. By using impedance as a parameter to track sensor state and adjust sensitivity calculations in real-time, the system maintains measurement precision while reducing the need for frequent manual calibration events
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
Improves sensor accuracy and reduces the frequency of in vivo calibration events by using impedance to estimate sensor sensitivity and detect damage, enhancing performance and efficiency.
Implementation Method 1
determining an impedance of the analyte sensor based on the measured current or charge count and the applied transient excursion bias voltage
Data Source
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Figure 3A~3C
AI summary
Various examples are directed to systems and methods of and using analyte sensors. An example analyte sensor system comprises an analyte sensor and a hardware device in communication with the analyte sensor. The hardware device may be configured to perform operations comprising applying a first bias voltage to the analyte sensor, the first bias voltage less than an operational bias voltage of the analyte sensor, measuring a first current at the analyte sensor when the first bias voltage is applied, and applying a second bias voltage to the analyte sensor. The operations may further comprise measuring a second current at the analyte sensor when the second bias voltage is applied, detecting a plateau bias voltage using the first current and the second current, determining that the plateau bias voltage is less than a plateau bias voltage threshold, and executing a responsive action at the analyte sensor.