Mobile Camera Neural Network for Immunoassay Test Strip Analysis
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Solution Overview
Problem
Current home test kits for medical conditions lack ease of use and require complex procedures, often taking weeks to provide results, which can be detrimental in cases like Zika virus detection during pregnancy.
Innovation Solution
A system and method utilizing a mobile device with a camera and software application that captures images of immunoassay test strips, processes them using a trained neural network to provide immediate diagnostic results, allowing for quick detection of medical conditions like Zika virus and pregnancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional home test kits are used for medical diagnosis, then the testing procedure can be performed at home, but the results take weeks to provide and the procedure is complex
Solution Approach 1:
The patent replaces the traditional mechanical/chemical test strip reading system with an optical image capture system using a mobile device camera. The camera captures an image of the test strip, and a neural network processes the image to determine the result, substituting manual interpretation with automated optical recognition.
Solution Approach 2:
The patent introduces a neural network as an intermediary between the test strip visual result and the final diagnostic conclusion. The neural network processes the captured image data and provides the definitive result, acting as a mediator that translates visual patterns into actionable medical information.
2Ease of operation
If traditional home test kits are used for medical diagnosis, then the testing can be done at home, but the procedure is complex and not user-friendly
Solution Approach 1:
The system enables self-service by allowing the user to simply capture an image of the test strip with their mobile device camera. The neural network automatically processes the image and provides the result without requiring the user to perform complex analysis or interpretation steps.
Solution Approach 2:
The patent replaces the complex manual procedure of reading and interpreting test strip results with an automated optical recognition system. The mobile device camera and neural network substitute for the user's manual analysis process, dramatically simplifying the user experience.
3Speed
If rapid diagnostic testing is implemented, then immediate results can be provided, but advanced technology is required
Solution Approach 1:
The patent leverages the universal capabilities of mobile devices (camera, processor, display) that most users already possess. By using the neural network running on the user's existing mobile device rather than requiring specialized equipment, the system achieves rapid results without adding significant complexity to the user's environment.
Solution Approach 2:
The neural network serves as an intermediary that bridges the simple act of image capture with the complex task of rapid diagnostic analysis. It processes the visual data from the test strip and delivers immediate results, hiding the computational complexity from the user while providing fast outcomes.
Data Source
AI summary
A method for providing diagnostic test results is provided. The method comprises providing a software application to be stored on a mobile device, the mobile device having a camera and a viewing screen, initiating operation of the camera, aligning the camera with a visual trigger associated with the diagnostic test, capturing an image of the diagnostic test, sending the image to a server, creating a pixel value array from the pixel values in the image, providing the pixel value array as inputs in a trained neural network, and providing either a positive or negative result from the trained neural network in response to the pixel value array.