Analyte Detection Using Differential Measurement Locations
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Solution Overview
Problem
Current methods for detecting analytes in body fluids, particularly those with particulate compounds, face inaccuracies due to deviations in measured values caused by the concentration of particulate compounds, such as hematocrit, which are influenced by various parameters beyond just blood cells.
Innovation Solution
A method involving a test element with a capillary element guiding the sample across a test field with multiple measurement locations, using an evaluation algorithm that considers the difference between measurement values from these locations and analyte-induced changes to correct for the concentration of particulate compounds, thereby improving the accuracy of analyte detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single measurement location is used in the test field, then the device complexity is reduced, but the measurement precision deteriorates due to inaccuracies caused by particulate compound concentration variations
Solution Approach 1:
The test field is divided into multiple measurement locations (at least two) to enable differential measurements. This segmentation allows the system to capture spatial variations in particulate compound concentration and use algorithmic processing to correct analyte concentration measurements, thereby improving measurement precision without requiring complex hardware modifications at each location
Solution Approach 2:
An evaluation algorithm acts as an intermediary between the raw measurement values from multiple locations and the final analyte concentration result. This algorithm processes the difference between measurements from different locations to compensate for particulate compound interference, achieving high measurement precision through software-based correction rather than complex physical measurement systems
2Measurement precision
If multiple measurement locations are used to correct for particulate compounds, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The test field is divided into multiple measurement locations (at least two) to enable differential measurements. This segmentation allows the system to capture spatial variations in particulate compound concentration and use algorithmic processing to correct analyte concentration measurements, thereby improving measurement precision without requiring complex hardware modifications at each location
Solution Approach 2:
An evaluation algorithm acts as an intermediary between the raw measurement values from multiple locations and the final analyte concentration result. This algorithm processes the difference between measurements from different locations to compensate for particulate compound interference, achieving high measurement precision through software-based correction rather than complex physical measurement systems
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 of analyte concentration measurements by accounting for the effects of particulate compounds, reducing errors and providing more accurate results, especially in blood glucose level determination.
Implementation Method 1
a capillary element adapted to guide the sample across said test field in a flow direction
Implementation Method 2
at least one test material adapted to change at least one measurable property in the presence of the analyte
Data Source
AI summary
Methods, devices and systems for detecting an analyte in a body fluid are described. A sample of body fluid is applied to a test element having a test field including a test material adapted to change a measurable property in the presence of the analyte. The test element includes a capillary to guide the sample across said test field. The measurable property is measured in a first measurement location providing a first measurement value, and in a second measurement location providing a second measurement value. The analyte is detected by using an evaluation algorithm having at least a first input variable including a difference between the first measurement value and the second measurement value, and at least a second input variable including information relating to an analyte-induced change of the measurable property of the test material in at least part of the test field.