Optical Fluid Sample Detection via Image Processing
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Solution Overview
Problem
Current methods for determining disease status in fluid samples require laboratory settings and are not easily accessible for self-testing at home, necessitating a solution for straightforward and reliable detection of target species in fluid samples.
Innovation Solution
A computer-implemented method using optical properties of fluid samples, where images are captured and processed to determine the presence of target species, employing machine-learning models and a sample vessel design for reagent interaction, allowing for self-testing without the need for clinical facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laboratory-based testing methods are used, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent uses image capture devices (cameras) to capture optical images of the sample vessel, which are then processed to extract optical property data. This creates a simplified copy or representation of the complex laboratory measurement process, enabling disease detection through straightforward image acquisition and processing rather than complex laboratory equipment
Solution Approach 2:
The patent replaces complex mechanical and chemical laboratory testing systems with an optical-based system using image capture devices. Instead of using sophisticated laboratory instruments to analyze fluid samples, the system uses cameras to capture optical properties (color, transparency) and processes these images computationally to determine disease status
2Measurement precision
If laboratory-based testing methods are used, then measurement precision is improved, but ease of operation worsens
Solution Approach 1:
The patent enables users to perform disease testing themselves at home without requiring laboratory facilities or professional technicians. The system includes a sample vessel with reagents that users can easily handle, and an image capture device that automatically processes the sample and provides results, making the entire testing process self-service oriented
Solution Approach 2:
The system captures optical images of the sample vessel and processes these images to extract diagnostic information. This copying approach simplifies the operation significantly - users only need to capture an image with a camera rather than operate complex laboratory equipment, making the process accessible to ordinary users at home
3Ease of operation
If optical property measurement is used, then ease of operation is improved, but measurement precision may worsen
Solution Approach 1:
The system uses machine learning models that have been trained on optical property data to interpret the captured images. The model receives optical property data as input and provides feedback in the form of disease status determination. This feedback mechanism enables accurate target species detection even from simple optical measurements by leveraging learned patterns from training data
Solution Approach 2:
The patent measures multiple optical parameters (color, transparency, absorption) of the fluid sample and uses these parameter changes to detect the presence of target species. By monitoring changes in these optical parameters before and after reagent interaction, the system achieves accurate detection while maintaining ease of operation through simple image capture
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
Enables users to determine disease presence or progression accurately and conveniently at home, using optical properties and machine-learning models, reducing the need for laboratory testing and improving accessibility.
Implementation Method 1
an optical property of the fluid sample is indicative of the presence of the target species
Data Source
AI summary
A computer-implemented method of determining the presence of a target species in a fluid sample comprises: receiving a captured image including an image capture portion of a sample vessel, the image capture portion exposing a fluid sample contained within the sample vessel, wherein an optical property of the fluid sample is indicative of the presence of the target species; processing the captured image to generate optical property data representative of the optical property of the fluid sample; and determining whether the target species is present in the fluid sample based on the optical property data. A sample vessel is also provided.