Smartphone-Based Fluid Analysis System for Automated Urine Test Interpretation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional urine testing methods using test strips are subjective, prone to human error, and not practical for high-throughput clinical settings due to manual interpretation and the need for specialized hardware, while smartphones with varying camera quality and lighting conditions complicate their use as regulatory-approved devices.
Innovation Solution
A system and method for analyzing a fluid sample using a smartphone or electronic device that receives an image of a test strip, identifies regions, and computes health parameters based on chemical reactions, employing image processing and machine learning models to standardize images and determine chemical reactions, thereby reducing human error and the need for specialized hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual interpretation of test strip colours is used, then the testing method is simple and requires minimal equipment, but it is subjective, prone to human error, and time-consuming
Solution Approach 1:
The patent replaces manual mechanical interpretation of test strip colors with an automated image processing system using smartphones and computer vision algorithms. The system captures images of test strips and automatically analyzes color changes through image processing, eliminating human subjectivity while maintaining operational simplicity.
Solution Approach 2:
The patent uses digital copies (images) of test strips captured by smartphone cameras as substitutes for manual visual interpretation. These digital images are processed by algorithms to objectively determine test results, replacing the subjective human eye with automated digital analysis.
2Measurement precision
If specialized hardware with pre-calibrated scanners is used, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The patent makes universal smartphones with varying camera qualities suitable for clinical testing by implementing adaptive image processing algorithms. The system works across different smartphone models and lighting conditions, eliminating the need for specialized calibrated hardware while maintaining measurement precision through software-based correction.
Solution Approach 2:
The patent dynamically adjusts image processing parameters based on lighting conditions, camera characteristics, and test strip types. The system adapts its algorithms to compensate for variations in smartphone cameras and environmental lighting, maintaining measurement accuracy without requiring specialized calibrated equipment.
3Ease of operation
If smartphone camera quality varies by brand and model, then accessibility and ease of operation improve, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent performs preliminary characterization of each smartphone camera's optical properties during device setup. The system captures reference images and automatically determines camera-specific parameters such as white balance, color space, and exposure characteristics, storing this calibration data for subsequent test strip analysis to compensate for camera variations.
Solution Approach 2:
The patent applies localized correction techniques tailored to each smartphone camera's specific characteristics. Instead of using a universal correction approach, the system customizes image processing parameters for each device based on its unique optical properties, ensuring consistent measurement precision across different smartphone models.
4Ease of operation
If manual interpretation is used in high-throughput settings, then operational simplicity is maintained, but productivity and efficiency decrease
Solution Approach 1:
The patent implements automated self-service analysis where the system independently processes test strip images without requiring manual interpretation. The automated algorithms perform color analysis, result determination, and report generation automatically, enabling high-throughput processing while maintaining operational simplicity for users.
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 system provides an automated, objective, and accessible method for fluid sample analysis, enabling accurate and reliable results even in non-standard environments, improving patient outcomes by facilitating faster diagnosis and treatment with real-time urine test results.
Implementation Method 1
a degree of chemical reaction may be determined by analysing the set of chemical pads based on the test data
Implementation Method 2
a set of colour markers, and a set of chemical pads... a degree of chemical reaction may be determined by analysing the set of chemical pads
Implementation Method 3
smartphones now feature tremendous computing power, wireless Internet connection, and high-resolution cameras
Data Source
AI summary
A system and a method for analysing a fluid sample. The system receives an image of a test strip. The system identifies a set of regions in the image. The set of regions comprises a code, a set of position markers, a set of colour markers, and a set of chemical pads. Subsequently, the system obtains test data based on the code. The test data includes a set of health parameters, and chemical pad data. Further, the system determines a degree of chemical reaction by analysing the set of chemical pads based on the test data. Furthermore, the set of health parameters may be computed based on the extent of the chemical reaction.