Immunochromatography Test Interpretation Using Multi-Image Color Checks
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Solution Overview
Problem
The accuracy and speed of automatic interpretation by diagnostic testing devices in immunochromatography are limited, particularly due to potential false-positive results from viscous samples causing delayed flow and coloration changes.
Innovation Solution
A diagnostic testing device that captures multiple images of the test strip's coloration states and interprets the results based on a consistent positive or negative state across multiple images, using a coloration index threshold to reduce false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are captured and interpreted based on consistent coloration state across multiple images, then measurement precision is improved, but loss of time increases due to multiple capture cycles
Solution Approach 1:
The system dynamically adjusts the interpretation decision process based on the consistency of coloration state across multiple images. By evaluating whether the coloration state remains consistent across N captured images, the system adaptively determines the final interpretation result, resolving the contradiction between requiring multiple measurements for accuracy and minimizing time loss through unnecessary repeated captures.
2Ease of operation
If automatic interpretation is performed to reduce tester workload, then ease of operation is improved, but reliability decreases due to false-positive results from viscous samples
Solution Approach 1:
The system implements a feedback mechanism where the interpretation result is evaluated based on the consistency of coloration state across multiple captured images. When the coloration state shows inconsistency (potential false-positive), the system uses the multi-image interpretation rule to filter out erroneous results, thereby maintaining high reliability while preserving the ease of automatic operation.
3Productivity
If interpretation is made based on single image capture, then productivity is improved, but measurement precision deteriorates due to potential false-positive results
Solution Approach 1:
The system applies partial action by capturing images N times (where N is a small integer greater than 1) rather than requiring extensive repeated measurements. This partial repetition provides sufficient precision improvement to filter false-positives while maintaining high productivity through rapid automated processing of the limited number of captures.
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 the accuracy and speed of test interpretation by reducing false-positive results, ensuring reliable and swift assessment of test results.
Implementation Method 1
The labeling substance is a label of a particular color, and binds to the analyte (in most case, antigen) by antigen-antibody reaction when mixed with the liquid sample
Implementation Method 2
Upon reaching the detection area, the analyte that is bound to the labeling substance is selectively bound to the immobilizing substance, and is immobilized there
Implementation Method 3
The detection area where the analyte bound to the labeling substance is immobilized and accumulated exhibits coloration of a predetermined color by the labeling substance
Data Source
AI summary
A diagnostic testing device is a testing-device for immunochromatography wherein a liquid sample contains an analyte developed in a detection area via a labeling-substance-containing area of a test strip, and a negative or positive interpretation is made from the coloration exhibited by the detection area. The device includes a measuring part for obtaining data on a coloration index associated with coloration state for at least part of the detection area, and a processing part that interprets based on the coloration index data. The processing part delivers a negative interpretation if the coloration state of the analyte detection area is in a negative state in at least one image out of a maximum of N (wherein N is greater than 1) obtained images, and delivers a positive assessment if the coloration state of the analyte detection area is in a positive state in all N images.