Optical Element Selection Using Eye Aberrations and Viewing Behavior
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Solution Overview
Problem
Selecting optical elements for vision correction is challenging due to individual eye aberrations and variations in outcomes among users, necessitating a need for personalized and optimized selection methods.
Innovation Solution
A computer-implemented system that utilizes eye optical property information and patient-specific use-case data to determine a quality metric for optical elements, generating scores and rankings to optimize vision correction based on both eye properties and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional optical element selection methods are used, then the selection process is simple, but the vision correction outcome varies significantly among individual users
Solution Approach 1:
The patent segments the optical element selection process into multiple independent evaluation dimensions: ocular aberration parameters, viewing behavior characteristics, lens optical properties, and quality metric calculations. Each dimension is assessed separately and integrated to form a comprehensive selection criterion, enabling personalized optimization without overwhelming system complexity
Solution Approach 2:
The patent transforms the selection criterion from traditional simple prescription parameters to a multi-parameter quality metric system that includes ocular aberrations (spherical aberration, coma, astigmatism), viewing behavior parameters (viewing distance, ambient light, viewing time), and lens optical properties. This parameter transformation enables more precise matching between optical elements and individual user characteristics
2Measurement precision
If optical elements are selected based only on basic prescription parameters, then the selection process is quick, but it fails to account for individual eye aberrations and viewing behaviors
Solution Approach 1:
The patent implements preliminary action by pre-establishing databases of ocular aberration profiles, viewing behavior patterns, and lens optical characteristics. These pre-collected and pre-processed data enable rapid retrieval and comparison during the selection process, achieving high measurement precision without proportionally increasing selection time
Solution Approach 2:
The patent introduces a computer-implemented system as an intermediary that automatically processes and integrates multiple parameters (ocular aberrations, viewing behaviors, lens properties) to calculate quality metrics. This intermediary handles the complex computations and data integration, providing accurate matching results efficiently without requiring manual analysis time
3Adaptability or versatility
If a comprehensive evaluation system considering multiple parameters is implemented, then the vision correction optimization is improved, but the system complexity and computational requirements increase
Solution Approach 1:
The patent creates a universal quality metric calculation framework that can evaluate different types of optical elements (spectacle lenses, contact lenses, intraocular lenses) against various user characteristics (different ocular aberrations, diverse viewing behaviors). This multi-functional system handles multiple lens types and evaluation criteria through a unified approach, achieving high adaptability without proportionally increasing system complexity
Solution Approach 2:
The patent implements feedback mechanisms where the calculated quality metrics provide guidance for optimizing optical element selection. The system compares predicted performance outcomes with desired correction goals and adjusts selections accordingly, enabling continuous improvement while maintaining systematic control over the evaluation process
Data Source
AI summary
Computer-implemented tools to assist a clinician in selecting a lens or other optical element for an optimal patient treatment, such as correction, based on both the optical properties of the patient's eye and certain patient-specific use-case information such as viewing behavior or viewing preferences, or to effect treatment such as to control myopia progression. Clinicians, eye care professionals and others can provide patient-optimized lens fitting or design by use of the tools.