Visual Acuity Modeling With Ocular-Lens Aberration Interaction
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Solution Overview
Problem
Current visual acuity assessment methods, such as the Snellen chart test, are subjective, inconsistent, and inaccurate due to factors like visual fatigue and uncorrected refractive errors, especially in children, and do not account for the interaction of ocular and lens aberrations, including transverse chromatic aberration, which affects spectacle wearers.
Innovation Solution
A method incorporating ocular and lens aberrations, including transverse chromatic aberration, using a statistical model and neural network to predict visual acuity, which includes aberrometry data, ray tracing, and optical character recognition to generate accurate visual acuity values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective techniques like Snellen chart test are used for visual acuity assessment, then accurate evaluation can be achieved, but the test reliability is diminished due to subjective factors such as visual fatigue, degree of concentration, and ability to extract information from blurred images
Solution Approach 1:
The patent replaces the subjective mechanical assessment process (patient reading optotypes and reporting results) with an objective optical measurement system. An aberrometer measures wavefront aberrations of the eye, and a processing system automatically derives visual acuity from these optical parameters, eliminating subjective factors like visual fatigue and concentration variability.
Solution Approach 2:
The system uses the eye's own optical properties (aberrations) to determine visual acuity without requiring patient participation in subjective tasks. The measurement is self-contained, using objective optical data from the eye itself rather than requiring the patient to perform and report on visual tasks.
2Device complexity
If only ocular aberrations are considered in visual acuity models, then the modeling process is simpler, but the accuracy is reduced because certain combinations of aberrations interact with each other to provide superior or degraded vision
Solution Approach 1:
The patent merges ocular aberrations with lens aberrations into a combined optical model. The system measures eye aberrations with an aberrometer, obtains lens aberration data, and processes both sets of data together to predict visual acuity, accounting for the interaction between ocular and lens optical imperfections.
Solution Approach 2:
The patent creates a composite optical model that combines different sources of aberrations (ocular and lens) to predict visual acuity. This composite approach integrates multiple optical components' characteristics to provide a more accurate representation of the complete optical system.
3Productivity
If current visual acuity models are used that are limited to ocular aberrations, then the assessment process is faster, but transverse chromatic aberration impact on visual quality cannot be properly assessed
Solution Approach 1:
The patent replaces the need for physical optotype testing with an optical measurement and computational model approach. An aberrometer rapidly measures wavefront aberrations, and a processing system computationally derives visual acuity, eliminating the time-consuming subjective testing process while capturing chromatic aberration effects.
Solution Approach 2:
The patent changes the measurement parameters from subjective optotype recognition to objective wavefront aberration measurements. By measuring optical parameters (including chromatic aberrations) and computationally deriving visual acuity, the system achieves both speed and accuracy without requiring slow subjective patient responses.
Data Source
AI summary
Systems and methods for visual acuity calculation including consideration of a combination of ocular aberrations and lens aberrations are disclosed. One method includes obtaining ocular aberration data and introducing a correction in the defocus term of the ocular aberration data to account for longitudinal chromatic aberration. Lens aberration data is obtained, including performing raytracing through the ophthalmic lens of the patient. Correction to tilt and defocus terms of the lens aberration data is made to account for transverse and longitudinal chromatic aberrations. Polychromatic Point Spread Functions (PSFs) associated to the ocular aberration data and lens aberration data are used to generate retinal images. Retinal sampling is applied to the retinal images, followed by filtering and normalizing the retinal images is also performed. Finally, a maximum visual acuity value is determined. The methods are performed using one or more computing devices.