Specimen Analysis System for Colorimetric Test Interpretation
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Solution Overview
Problem
Colorimetric tests, such as the Guaiac test for hemoglobin, are subjectively interpreted by human operators due to varying color intensities, leading to inconsistent results and potential false positives.
Innovation Solution
A specimen analysis system that uses a processor to analyze images of testing areas, determining the number of pixels indicating a positive result based on hue, saturation, and brightness criteria across multiple testing areas, with predefined thresholds to objectively determine the presence or absence of a test subject compound.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If colorimetric tests are interpreted visually by human operators, then the interpretation process is simple and quick, but the results are highly subjective and inconsistent
Solution Approach 1:
The patent replaces the human visual interpretation system with an automated optical analysis system that captures images of the test article and uses image processing algorithms to objectively analyze colorimetric changes. This substitution eliminates human subjectivity while maintaining operational simplicity through automated processing.
Solution Approach 2:
The patent introduces an intermediary image capture device and processing system between the test article and the interpretation process. This intermediary objectively records the colorimetric response and translates it into quantifiable data, removing the human operator from the subjective interpretation loop while preserving the simplicity of the overall testing workflow.
2Reliability
If multiple test areas are required to indicate positive response, then false-positive results are minimized, but the complexity of interpretation increases
Solution Approach 1:
The patent divides the test article into multiple discrete test areas and independently analyzes the colorimetric response in each area. By segmenting the analysis into distinct regions with specific pixel evaluation criteria, the system objectively determines how many areas show positive response, reducing false positives while managing complexity through automated regional analysis.
Solution Approach 2:
The patent applies parameter-based evaluation by analyzing hue, saturation, and brightness values of pixels in each test area. This quantitative approach to multiple test areas transforms the complex interpretation of multiple color responses into a systematic parameter comparison process, maintaining reliability while reducing subjective complexity.
3Quantity of substance
If color intensity varies greatly in colorimetric tests, then the test can detect presence of substance, but the interpretation becomes highly subjective
Solution Approach 1:
The patent addresses varying color intensity by analyzing multiple color parameters (hue, saturation, brightness) rather than relying on a single intensity measure. This multi-parameter approach allows the system to objectively evaluate substance presence across different color intensities, maintaining detection capability while eliminating interpretive subjectivity through quantitative analysis.
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 minimizes false-positive results by objectively assessing colorimetric changes across multiple testing areas, providing a consistent and accurate interpretation of test results.
Implementation Method 1
a color of the optical test substance marker may indicate the presence or absence of the test subject substance within the specimen
Implementation Method 2
detect the intensity of a colorimetric change of a plurality of pixels in a plurality of testing areas
Data Source
AI summary
A specimen analysis system includes at least one processor to receive image information that represents a respective plurality of pixels of an image of each of a plurality of testing areas to indicate the presence or absence of a test subject compound; to determine for each testing area a number of pixels that indicates either the presence or the absence of the test subject compound, if the number of pixels indicating positive for each of a plurality of testing areas equals or exceeds a first minimum threshold value indicating that the testing area is positive for either the presence or absence of the test subject compound, totaling all testing areas indicating positive for either the presence or absence of the test subject compound, and if the total number of the testing areas indicating positive for either the presence or absence of the test subject compound equals or exceeds a second minimum threshold value indicating an overall positive test result for either the presence or absence of the test subject compound.