Glucose Meter Signal Processing Outlier Removal
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Solution Overview
Problem
Conventional methods for measuring blood glucose levels using electronic meters face challenges in filtering out noise from environmental sources like electrostatic discharge and switching power supplies, leading to inaccurate readings due to the dominance of extreme values over true signal characteristics.
Innovation Solution
A method that ranks and discards the highest and lowest magnitude A/D conversions before calculating the average, thereby filtering out noise disturbances and improving the accuracy of blood glucose measurements by reducing the impact of outliers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional software averaging is used to reduce noise, then noise reduction is achieved, but measurement time increases significantly and phase delay occurs
Solution Approach 1:
The patent extracts and removes outlier values from the signal before averaging. By identifying and discarding extreme values that represent noise disturbances rather than true signal characteristics, the method achieves effective noise reduction without requiring excessive sampling, thus reducing measurement time and phase delay while maintaining reliability
Solution Approach 2:
The patent applies preliminary filtering by ranking and removing outliers before the averaging calculation is performed. This preliminary action eliminates the need for excessive sampling to achieve noise reduction, allowing the system to reach accurate results faster and reduce measurement time
2Measurement precision
If more A/D readings are averaged to reduce noise, then measurement accuracy improves, but measurement time increases significantly
Solution Approach 1:
The patent extracts outlier values from the dataset before averaging. By removing these extreme values that contribute to noise, the method achieves high measurement accuracy with fewer samples, eliminating the need to increase sampling time to compensate for noise contamination
Solution Approach 2:
The patent changes the approach from increasing sample count to improving sample quality. By applying a ranking-based outlier removal parameter to the dataset, the system achieves high measurement precision with reduced sampling time, as the focus shifts from quantity to quality of measurements
3Reliability
If conventional averaging is used, then noise reduction is achieved, but phase delay increases due to the time required to collect sufficient samples
Solution Approach 1:
The patent extracts and removes outlier values before averaging, achieving effective noise filtering with a fixed, small number of samples. This eliminates the need to collect extensive samples over time, thereby reducing phase delay while maintaining reliable noise filtering
Solution Approach 2:
The patent performs preliminary outlier removal before the averaging calculation. This preliminary filtering action achieves noise reduction with minimal sampling time, preventing the phase delay that would otherwise occur while waiting to collect sufficient samples for conventional averaging
Data Source
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AI summary
A system and method of processing a test current for an analyte measurement in a fluid using a test strip and a test meter are disclosed. The method comprises sampling the test current at a pre-determined sampling rate to acquire a plurality of A/D conversions. The method also comprises filtering out at least a highest magnitude A/D conversion and a lowest magnitude A/D conversion leaving a plurality of accepted A/D conversions. Further, the method comprises calculating an average or a summation of the plurality of accepted A/D conversions and converting the average or the summation into a glucose concentration.