Color Trajectory Analysis for Urinalysis Precision
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Solution Overview
Problem
Existing automatic urinalysis machines rely on snapshot color matching, neglecting the rate of color change, which limits their ability to report secondary reactions or intermediate reaction rates, and are prone to errors due to subjective human interpretation and ambient lighting conditions.
Innovation Solution
A method and apparatus that continuously or periodically monitor color changes over time, using a sequence of color images to interpret chemical reactions, accounting for time, temperature, and acidity, and providing improved accuracy through statistical cross-referencing and augmented reality interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If snapshot color matching is used for automatic urinalysis, then the device complexity is reduced and operation is simplified, but measurement precision is compromised due to inability to capture color change rates and intermediate reactions
Solution Approach 1:
The system pre-establishes a color trajectory database containing expected color change patterns for various analyte concentrations. During measurement, the actual color trajectory is compared against this pre-established database to determine concentration, eliminating the need for complex real-time differential analysis while improving precision through pattern matching.
Solution Approach 2:
The system continuously captures color images at multiple time points and uses feedback control to adjust measurements. By monitoring the color change rate and comparing it against expected trajectories, the system can identify intermediate reactions and secondary effects, thereby improving measurement precision through iterative refinement.
2Measurement precision
If manual color comparison by naked eye is used, then device complexity is minimized, but measurement precision deteriorates due to subjective interpretation and ambient lighting variations
Solution Approach 1:
The system replaces the mechanical/visual comparison method with an automated digital image processing system. Color images are captured by a camera and analyzed through software algorithms that objectively determine analyte concentration based on color trajectories, eliminating subjective human interpretation and reducing sensitivity to ambient lighting conditions.
Solution Approach 2:
The system transforms the static color comparison parameter into a dynamic parameter by measuring color changes over time. Instead of comparing a single color snapshot against a reference chart, the system analyzes the rate and pattern of color change, providing more robust and objective measurement that is less susceptible to lighting variations.
3Measurement precision
If continuous color monitoring is implemented, then measurement precision is improved through capture of color change rates, but loss of time increases due to extended measurement duration
Solution Approach 1:
The system performs continuous color monitoring but terminates the measurement process early when the color trajectory converges to a stable pattern or when sufficient data points have been collected to accurately determine concentration. This partial action approach captures the essential color change rate information without requiring the full reaction to complete, reducing measurement time while maintaining precision.
Solution Approach 2:
The system uses pre-established color trajectory databases to predict when sufficient measurement data has been collected. By comparing real-time color trajectories against expected patterns, the system can determine when the measurement is complete and terminate early, avoiding unnecessary extended measurement time while preserving the precision benefits of 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
This approach enhances precision by considering the time-gradient of color changes, reducing errors and providing near-real-time, accurate analyte concentration measurements, even in uncontrolled lighting environments.
Implementation Method 1
Each reagent test pad on the dipstick is chemically treated with a compound that is known to change color in the presence of particular reactants
Implementation Method 2
capturing a first color image of a first biological sample at a first time point
Implementation Method 3
a camera or other image capture device to capture a color image of the biological sample at a first time point
Data Source
AI summary
In one embodiment, an apparatus for automatic test diagnosis of a test paddle is disclosed. The apparatus comprises a personal computing device including: a camera to capture images over time of test pads of a test paddle, a processor coupled to the camera, and a display device coupled to the processor. The processor analyzes the color changes over time of each test pad to determine a color trajectory over time for each test pad. The processor compares the color evolution trajectory for each test pad with color calibration curves for each test pad to determine an analyte concentration of a test biological sample, such as urine. During the analysis by the processor, the display device displays a user interface with results of the analyte concentration in response to the analysis over time.