Mobile Device Analyte Bias Correction for Critical Threshold Detection
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Solution Overview
Problem
Existing methods for determining analyte concentrations in bodily fluids using mobile devices face challenges in evaluating color changes from color formation reactions, leading to potential misses in critical analyte concentrations due to measurement errors.
Innovation Solution
The method involves using a mobile device with a processing device and camera to determine an initial analyte result value from a color formation image, and then adjusting this value by comparing it to threshold values and applying biases to ensure accurate representation of analyte concentrations, thereby reducing the likelihood of missing critical states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If color formation reactions are used to determine analyte concentration, then the measurement can be performed using generally available mobile devices, but measurement errors may lead to missing critical analyte concentrations
Solution Approach 1:
The system applies preliminary anti-action by introducing bias values before the final result is displayed. When an initial analyte result value approaches a threshold value, the system proactively adds or subtracts a bias value to shift the result away from the threshold, preventing false critical state notifications. This anticipatory correction addresses measurement errors before they can lead to missed critical detections.
Solution Approach 2:
The system performs preliminary action by evaluating the initial analyte result value against threshold values and applying corrections in advance. The processing device calculates whether a bias should be applied based on the proximity to threshold values, and this correction is performed before presenting the final result to the user, ensuring more reliable critical state detection.
2Measurement precision
If threshold comparison is used to determine critical states, then critical analyte concentrations can be identified, but measurement errors may cause false negatives near threshold values
Solution Approach 1:
The system applies preliminary anti-action by introducing bias values before the final result is displayed. When an initial analyte result value approaches a threshold value, the system proactively adds or subtracts a bias value to shift the result away from the threshold, preventing false critical state notifications. This anticipatory correction addresses measurement errors before they can lead to missed critical detections.
Solution Approach 2:
The system implements beforehand cushioning by adding or subtracting bias values to create a buffer zone around threshold values. This cushioning effect absorbs measurement errors and prevents the final result from landing exactly at or near critical thresholds, reducing the likelihood of false negatives while maintaining reliable critical state detection.
3Reliability
If bias values are added or subtracted from initial analyte result values, then the likelihood of detecting critical states increases, but the final result may differ from the initial measurement
Solution Approach 1:
The system applies parameter changes by modifying the analyte result value through the addition or subtraction of bias values. This transformation changes the final presented parameter (analyte concentration) to account for measurement uncertainties near threshold values, prioritizing reliable critical state detection over exact numerical precision in borderline cases.
Solution Approach 2:
The system converts the potential harm of measurement errors into a benefit by deliberately applying bias values that compensate for these errors. The apparent inaccuracy of adding or subtracting bias values is transformed into a protective mechanism that ensures critical states are not missed, turning a source of error into a source of reliability.
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 enhances the reliability and safety of analyte concentration measurements by increasing the likelihood of detecting critically high or low analyte concentrations, thus improving user safety and health monitoring.
Implementation Method 1
determining by the processing device an initial numerical analyte result value from an image of a color formation of a reagent test region
Implementation Method 2
which comprise at least one test chemical, also referred to as a test reagent, which undergo a coloration reaction in the presence of the at least one Analyte to be detected
Data Source
AI summary
A method of determining an analyte concentration in a body fluid using a mobile device with a camera is disclosed. A corresponding computer program, a non-transitory computer-readable storage medium, a corresponding mobile device, and a corresponding kit are also disclosed. In step a of the method, a numerical analyte result value from an image of a color formation of a reagent test region is determined. In step b, the numerical analyte result value and/or a corresponding analyte value range and/or a corresponding message is displayed. In step c), after step a) and before step b), an upper bias is added to the numerical analyte result value if it exceeds an upper threshold value, or a lower bias is subtracted if it falls below a lower threshold value, or it is kept unchanged it neither threshold value is passed.