Analyte Detection Image Correction for Positional Drift
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Solution Overview
Problem
Current methods for detecting analytes in body fluids face challenges in precision, particularly with small sample volumes, mechanical disturbances, and inaccuracies due to structured sample application and mechanical tolerances, which affect the determination of blank values and spatial resolution of detector arrays.
Innovation Solution
A method and device that corrects for relative position changes between the image detector and test field using characteristic features, allowing for high-precision detection of analytes in small sample volumes by acquiring and processing image sequences to normalize optical properties and account for mechanical distortions, thereby improving the accuracy of analyte concentration measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detector arrays are used to monitor optical changes in test fields, then measurement precision is improved, but device complexity increases due to the need for correction algorithms and image processing
Solution Approach 1:
The patent applies preliminary action by acquiring images of the test field before sample application to establish baseline characteristics. This allows the system to pre-determine optical properties and create reference data that simplifies subsequent measurement processing and correction algorithms.
Solution Approach 2:
The system implements feedback by continuously monitoring optical changes in the test field during sample application and using this information to dynamically adjust measurement parameters. The feedback loop enables real-time correction of artifacts and optimization of analyte concentration calculations.
2Ease of operation
If small sample volumes are used to reduce discomfort, then ease of operation is improved, but measurement precision deteriorates due to insufficient sample coverage on the test field
Solution Approach 1:
The patent applies dimensionality change by transitioning from single-point detection to distributed pixel array detection across the test field. This allows the system to capture spatial distribution of the small sample volume and derive accurate analyte concentration through integrated optical measurement across multiple pixels.
Solution Approach 2:
The system creates optical copies of the test field at multiple time points and spatial locations. By acquiring sequential images and creating a composite representation of the sample distribution, the system can accurately measure analyte concentration even from small sample volumes without requiring large physical quantities.
3Manufacturing precision
If structured sample application is used to improve measurement consistency, then manufacturing precision is improved, but object-generated harmful factors increase due to mechanical distortions and artifacts
Solution Approach 1:
The patent converts the harmful mechanical artifacts and distortions introduced by structured sample application into beneficial correction data. By acquiring images before and during sample application, the system captures the distortion patterns and uses them to create correction algorithms that compensate for these artifacts, turning them into predictable, correctable parameters.
Solution Approach 2:
The system introduces image processing algorithms as intermediaries between the physical sample application process and the final analyte measurement. These intermediary correction layers filter out mechanical artifacts and distortions, allowing the system to maintain manufacturing precision benefits while eliminating harmful factors.
4Measurement precision
If multiple images are acquired to correct for position changes, then measurement precision is improved, but loss of time increases due to extended image acquisition and processing sequences
Solution Approach 1:
The system acquires baseline images of the test field before sample application to pre-establish the test field's optical characteristics and position. This preliminary action allows the system to minimize subsequent acquisition time by only capturing changes during the reaction period rather than continuously monitoring from the start.
Solution Approach 2:
The patent implements periodic image acquisition at key stages: before sample application, during sample application, and at defined time points during the detection reaction. This periodic sampling strategy provides sufficient data for position correction while minimizing total acquisition time compared to continuous monitoring.
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
The method enables precise detection of analytes with reduced artifacts and inaccuracies, allowing for accurate measurement of small sample volumes and robust image analysis, even in hand-held devices, by correcting for mechanical and optical distortions in the image sequence.
Implementation Method 1
various types of detectors are known. Besides single detectors such as photodiodes, various types of devices using detector arrays having a plurality of photosensitive devices are known
Implementation Method 2
various types of detectors are known. Besides single detectors such as photodiodes
Implementation Method 3
test elements comprising one or more test chemistries, which, in presence of the analyte to be detected, are capable of performing one or more detectable detection reactions, such as optically detectable detection reactions
Data Source
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AI summary
A method for detecting at least one analyte in at least one sample of a body fluid is disclosed. Therein, at least one test element (124) is used, the at least one test element (124) having at least one test field (162)with at least one test chemistry (154) is used, wherein the test chemistry (154) is adapted to perform at least one optically detectable detection reaction in the presence of the analyte. The method comprises acquiring an image sequence of images of the test field (162) by using at least one image detector (178). Each image comprises a plurality of pixels. The method further comprises detecting at least one characteristic feature of the test field (162) in the images of the image sequence. The method further comprises correcting a relative position change between the image detector (178) and the test field (162) in the image sequence by using the characteristic feature, thereby obtaining a sequence of corrected images.