Corrective Lens Suitability Assessment Using Predictive Vision Modeling

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Solution Overview

Problem

Existing systems for assessing the suitability of corrective optical devices, such as ophthalmic lenses, do not reliably consider both binocular vision comfort and visual performance, leading to inaccurate evaluations.

Innovation Solution

A system and method that utilize a predictive vision model incorporating accommodation, convergence, and visual performance sub-models to assess the suitability of corrective optical devices, taking into account interactions between these factors to provide a comprehensive evaluation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If existing systems evaluate suitability based on only binocular vision comfort or only visual performance, then the evaluation is simpler, but the reliability of the assessment is reduced

Engineering Contradiction:
Improveassessment reliabilityVSAvoidmodel complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The predictive vision model is divided into three independent sub-models: accommodation sub-model, convergence sub-model, and visual performance sub-model. Each sub-model processes specific aspects of visual function separately, allowing the system to evaluate multiple parameters systematically while maintaining manageable complexity in each individual component.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The three sub-models are integrated into a unified predictive vision model where outputs from one sub-model serve as inputs to another, creating a combined assessment framework. This merging allows the system to simultaneously evaluate binocular vision comfort and visual performance, resolving the contradiction between comprehensive assessment and system complexity.

Inventive Principle:
Principle #5Merging (Combining)

2Reliability

If the system considers both binocular vision comfort and visual performance simultaneously, then the assessment becomes more comprehensive, but the computational complexity increases

Engineering Contradiction:
Improveassessment accuracyVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary calculations by determining accommodative demand and convergence demand as input parameters before processing them through the predictive vision model. This preliminary action organizes the computational flow, allowing the model to process multiple parameters systematically and reduce overall computational complexity.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The visual performance sub-model output provides feedback to the accommodation and convergence sub-models, creating an iterative assessment process. This feedback mechanism allows the system to refine its assessment by considering how visual performance impacts accommodative and convergence responses, improving assessment accuracy while maintaining a structured computational approach.

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP4710839A1System and method for assessing a suitability between a corrective optical device and a subject
Publication Date: 2026.03.18 ESSILOR INTERNATIONAL(COMPAGNIE GENERALE D OPTIQUE)
  • EP4710839A1 patent drawingFigure 1~3
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  • EP4710839A1 patent drawing

AI summary

The invention relates to a system for assessing a suitability between a corrective optical device and a subject, the system being configured to: - determine an accommodative demand (AS) and a convergence demand (VS) to which the subject is submitted in a virtual optical system, the virtual optical system representing the subject looking at a target through the corrective optical device, - calculate, using a predictive vision model of the subject, a response of the subject to the accommodative and convergence demand, the response comprising an accommodation value (AR), a convergence value (VR) and a visual performance value (VP), the predictive vision model taking into account interactions between an accommodation sub-model (100) of the predictive vision model, a convergence sub-model (200) of the predictive vision model and a visual performance sub-model (300) of the predictive vision model, - assess the suitability based on at least one of the accommodation value, the convergence value and the visual performance value.