Bodily Fluid Testing Error Detection via Color Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current bodily fluid testing processes are inefficient and prone to errors, requiring patients to wait days for results and lacking reliable error detection methods, which affects the accuracy of test outcomes.
Innovation Solution
A method for determining errors in image data from bodily fluid testing equipment using color comparison, where detected colors are compared to reference colors to determine difference scores, and actions are taken based on predetermined thresholds to identify and correct errors, improving the reliability of the testing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If color comparison method is implemented for error detection, then reliability of testing is improved, but device complexity increases
Solution Approach 1:
The patent uses reference colors as copies or representations of expected test region colors. By capturing reference colors from a known good sample and comparing them against test samples, the system creates a baseline for error detection without requiring complex analytical chemistry equipment. This copying approach simplifies the device while maintaining reliability.
Solution Approach 2:
The patent replaces complex mechanical or chemical analysis systems with an optical/color-based detection system. Instead of using sophisticated instruments to analyze bodily fluid composition, the system uses color imaging and comparison algorithms to detect errors and determine test validity, significantly reducing device complexity while improving reliability.
2Reliability
If error detection is performed using existing methods, then some errors are identified, but measurement precision is insufficient
Solution Approach 1:
The patent implements a feedback mechanism where the detected color of the test region is compared against the reference color, and the difference score feeds back into the error determination process. This closed-loop approach allows the system to continuously refine its error detection by comparing actual measurements with expected values, improving both precision and reliability.
Solution Approach 2:
The patent transforms the complex problem of error detection into a simpler parameter comparison task by focusing on color parameters. By converting visual inspection into quantitative color difference measurements and establishing threshold-based decision criteria, the system achieves high measurement precision through parameter transformation and threshold optimization.
3Productivity
If manual inspection of test results is used, then equipment cost is reduced, but productivity decreases
Solution Approach 1:
The patent enables the testing system to perform self-verification by automatically comparing test region colors against reference colors and determining errors without human intervention. The system serves itself by incorporating error detection and validation capabilities directly into the testing device, eliminating the need for manual review while maintaining simplicity.
Solution Approach 2:
The patent replaces manual visual inspection with automated optical detection and image processing. By using electronic sensors to capture colors and algorithms to compare them against reference values, the system automates the quality control process that previously required trained personnel, thereby increasing productivity without excessive complexity.
4Measurement precision
If multiple reference colors are compared to determine closest match, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent compares the test region color against multiple reference colors to ensure accurate matching, but this is done efficiently by calculating difference scores for each reference color and selecting the closest match. The system performs the necessary comparisons without unnecessary delays, balancing precision with acceptable processing time by stopping once the closest reference color is identified.
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
There is provided a method for determining an error in image data of bodily fluid testing equipment. The method comprises detecting (S304) a first colour of a first testing region in the image data, comparing (S306) the detected first colour to reference colours, determining (S308) respective difference scores between the detected first colour and the reference colours, determining (S310) a closest reference colour wherein the closest reference colour has a lowest difference score, determining (S312) whether the difference score between the detected first colour and the closest reference colour is less than a predetermined maximum difference score, performing (S380) a first action when the difference score is less than the predetermined maximum difference score, and determining (S390) that there is an error in the first testing region in the image data and performing a second action when the difference score is not less than the predetermined maximum difference score.