Eye Astigmatism Measurement Using Reflected Feature Comparison
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Solution Overview
Problem
Existing methods for determining astigmatism parameters of the eye are not fast, easy, versatile, reliable, and accessible, as highlighted by DE 10 2015 100 147 A1.
Innovation Solution
A computer-implemented method using a measurement device to display a known feature on the eye, capture its reflection, determine the eye's position, and generate outcome data by comparing the known and reflected features to calculate astigmatism parameters, leveraging image capturing units and distance measurement devices for precise alignment and calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stationary keratometer is used for determining astigmatism parameters, then measurement precision is improved, but device complexity and accessibility are worsened
Solution Approach 1:
The patent uses a mobile device to capture images of the cornea and creates a digital model of the corneal surface, replacing the need for complex stationary keratometer hardware. The system copies the measurement function into a portable device with standard camera and processing capabilities.
Solution Approach 2:
The patent replaces mechanical optical measurement systems with image processing and computational methods. Instead of using complex mechanical keratometers, the system uses standard mobile device cameras combined with image analysis algorithms to determine astigmatism parameters.
2Measurement precision
If stationary keratometer is used for determining astigmatism parameters, then measurement precision is improved, but ease of operation and accessibility are worsened
Solution Approach 1:
The system enables users to perform their own eye examinations using mobile devices without requiring specialized medical equipment or expert operators. The automated image processing and analysis allow non-experts to obtain astigmatism measurements.
Solution Approach 2:
The patent uses universal mobile devices with standard cameras and processors to perform specialized ophthalmological measurements. The system makes astigmatism measurement accessible through commonly available technology rather than requiring dedicated medical equipment.
3Adaptability or versatility
If portable corneal topographers are used, then accessibility is improved, but measurement precision and reliability are worsened
Solution Approach 1:
The system captures multiple images of the cornea from different angles and uses image processing to create a comprehensive corneal model. The feedback loop involves comparing captured images with reference models to refine measurements and improve precision.
Solution Approach 2:
The system performs preliminary image capture and processing steps to establish baseline corneal geometry before final astigmatism parameter calculation. Multiple pre-processing steps including image alignment, noise reduction, and feature detection are performed before final measurement.
4Ease of operation
If computerized screen methods are used for refraction determination, then ease of operation is improved, but measurement precision is worsened
Solution Approach 1:
The patent replaces subjective refraction methods using computerized screens with objective image-based measurements. Instead of relying on patient responses to visual stimuli, the system directly measures corneal geometry through image capture and analysis.
Solution Approach 2:
The system creates digital copies of the corneal surface from captured images and performs measurements on these digital models. This allows precise geometric analysis without requiring subjective patient participation or complex optical setups.
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
Provides a fast, easy, versatile, reliable, and accurate approach for determining astigmatism parameters, enhancing accessibility and precision in assessing astigmatism without the need for specialized equipment or clinical settings.
Implementation Method 1
displaying the at least one known feature on a measurement device in a manner that the at least one known feature is reflected by the eye of the person
Data Source
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AI summary
The present invention relates to a computer-implemented method '(200) for determining at least one astigmatism parameter of at least one eye (302) of a person (300), the method comprising the following steps: a) generating input data (202) configured to comprise at least one position of the at least one eye (302) of the person (300) relative to the measurement device (110); wherein the at least one position of the at least one eye (302) of the person (300) is determined, in a step iii) (208), by using the measurement device (110); b) generating outcome data (214) configured to comprise at least one astigmatism parameter of the eye (302) of the person (300); wherein the at least one astigmatism parameter of the eye (302) of the person (300) is determined, in a step iv) (216), by comparing at least one known feature (118) to at least one reflected feature (122) comprised in the at least one recorded image of the at least one reflected feature in the eye (302) of the person (300), wherein the position of the at least one eye (302) of the person (300) is considered when the at least one astigmatism parameter of the eye (302) of the person (300) is determined. The present invention further relates to a computer program, a field device (400), a remote device (402), a determining device (100), a data carrier signal (406), a method for producing a geometrical model of at least one spectacle lens (500), a method for producing at least one spectacle lens (502), and a use of an external lens (130). The present invention provides a fast, easy, versatile, reliable, easy accessible and accurate approach for determining at least one astigmatism parameter of an eye (302) of a person (300).