Eccentric NIR Vision Screening for Automated Refraction Accuracy
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Solution Overview
Problem
Existing vision screening devices are cumbersome, costly, and prone to inaccuracies due to manual alignment and calibration curves, leading to complex operations and suboptimal refractive error measurements.
Innovation Solution
A compact vision screening system utilizing an eccentric radiation source and sensor configuration to measure refractive error through near-infrared radiation, employing a processor for image analysis and neural networks to determine refractive parameters, and providing automated diagnosis recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing vision screening devices use manual alignment and calibration curves, then the device can perform refractive error tests, but the device becomes cumbersome, costly, and prone to inaccuracies
Solution Approach 1:
The patent replaces manual alignment procedures with an automated imaging system that captures photos of the patient's eyes and uses image processing to automatically determine proper alignment and focus. The system substitutes mechanical calibration curves with computational algorithms that analyze captured images to calculate refractive error, eliminating the need for manual intervention and calibration equipment.
Solution Approach 2:
The system performs self-alignment and self-calibration by automatically capturing images, processing them through algorithms, and determining refractive parameters without requiring manual alignment or external calibration curves. The device serves itself by using its own captured images to calibrate and perform measurements.
2Measurement precision
If existing vision screening devices use range finders and specialized optics, then the device can measure refractive error, but the cost and size of the device increase
Solution Approach 1:
The patent employs a universal imaging approach where a single camera system performs multiple functions: capturing eye images for alignment verification, measuring refractive error through image analysis, and determining focus points. This multi-functional system replaces specialized optics and range finders with a versatile digital imaging platform that accomplishes all measurement tasks through software processing.
Solution Approach 2:
The system replaces physical range finders and specialized optical components with digital image processing algorithms. The camera captures images at various distances, and computational methods determine focus and refractive error, eliminating the need for mechanical ranging devices and complex optical assemblies.
3Ease of operation
If existing vision screening devices use manual alignment procedures, then the device can perform tests, but the testing process becomes time-consuming and complex
Solution Approach 1:
The system performs preliminary alignment and focus determination automatically by capturing and processing images before the actual refractive error measurement. The automated image analysis pre-establishes the proper viewing distance and alignment, eliminating the need for time-consuming manual alignment procedures during the testing process.
Solution Approach 2:
The patent replaces manual alignment procedures with automated image capture and processing. The system takes photos of the patient's eyes, uses algorithms to analyze the images, and automatically determines proper alignment and focus, dramatically reducing the time and complexity associated with manual alignment.
4Measurement precision
If existing vision screening devices use calibration curves, then the device can determine refractive error, but inaccuracies and errors are introduced in recommendations
Solution Approach 1:
The patent replaces calibration curves with computational image analysis algorithms. The system captures images of the patient's eyes at different distances and uses processing algorithms to directly calculate refractive error from the image data, eliminating the intermediate step of calibration curves that introduces inaccuracies and errors in measurements.
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 offers accurate, efficient, and user-friendly refractive error testing with reduced complexity and cost, enabling automated diagnosis and improved measurement precision.
Implementation Method 1
Sensors on the device may then collect corresponding light that is reflected by the retinas
Implementation Method 2
periodically emitting, via a radiation source, near infrared (NIR) radiation for a duration of the timeframe
Data Source
AI summary
A system includes system housing, an eccentric radiation source, and a radiation sensor. The radiation produced by the eccentric radiation source can be collected by the radiation sensor to generate images of retinas for a patient. The system also includes a vision screening device connected with the eccentric radiation source and the radiation sensor via the system house that can control and synchronize actions for the eccentric radiation source and the radiation sensor. The vision screening device further analyzes the images generated by the radiation sensor via neural network algorithms to determine spherical error slopes, refractive errors, and recommendations for the patient.