Progressive Lens Merit Function for Variable Peripheral Mean Sphere

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Solution Overview

Problem

Traditional merit functions for progressive addition lenses fail to distribute power components independently, leading to suboptimal and sometimes incorrect results, particularly for a wide range of prescriptions, as they do not adequately account for variations in myopic and hyperopic prescriptions.

Innovation Solution

An improved merit function is introduced, which modulates the peripheral mean sphere reduction based on the prescription, adjusting the width of the near region and minimizing unwanted astigmatism, ensuring better lens performance across a broader range of prescriptions by using specific calculations and weight functions to optimize the lens design.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If traditional merit function is used for progressive addition lens design, then the lens optimization process is simplified, but the power components cannot be distributed independently leading to suboptimal results

Engineering Contradiction:

Improvelens optimization processVSAvoidpower component distribution

Core Design Contradiction:

Ease of manufactureVSManufacturing precision

Solution Approach 1:

The merit function is segmented into multiple independent components: a first merit function term for optimizing the principal line and a second merit function term for optimizing the peripheral regions. This segmentation allows independent control and optimization of different power components (sphere, cylinder, axis) in different lens zones, resolving the contradiction by enabling precise power distribution while maintaining computational feasibility through modular optimization.

Inventive Principle:

Principle #1Segmentation

2Reliability

If constant peripheral mean sphere reduction is applied, then myopic prescriptions show improved performance, buthyperopic prescriptions show smaller improvement

Engineering Contradiction:

Improvelens performance for myopic prescriptionsVSAvoidlens performance across prescription range

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The peripheral mean sphere reduction is made dynamic rather than constant. The optimization process adaptively adjusts the reduction amount based on the specific prescription parameters (sphere, cylinder, axis) and the patient's visual needs. This dynamic approach allows the system to maximize improvement for myopic prescriptions while also providing appropriate optimization forhyperopic prescriptions, thereby improving both reliability for specific groups and versatility across the full prescription range.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The merit function incorporates variable parameters that change based on prescription type and severity. By modifying the optimization parameters (weights, reduction factors, target values) according to the specific prescription characteristics, the system achieves better performance for myopic cases while maintaining adaptability forhyperopic cases, resolving the contradiction between specialized optimization and broad applicability.

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If power components are optimized together in traditional merit function, then computational complexity is reduced, but incorrect results occur due to interdependence

Engineering Contradiction:

Improveoptimization calculation structureVSAvoidpower component optimization accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The optimization calculation is segmented into separate merit function terms that can be evaluated and optimized independently. The first term handles principal line optimization while the second term handles peripheral region optimization with independent weightings. This segmentation resolves the contradiction by allowing precise independent optimization of interdependent power components while maintaining a computationally manageable multi-term structure rather than a single complex interdependent calculation.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11520308B2Progressive lenses with variable reduced peripheral mean sphere

Publication Date: 2022.12.06 INDIZEN OPTICAL TECHNOLOGIES OF AMERICA LLC

AI summary

An improved method for configuring progressive ophthalmic lenses is disclosed. The method includes computing an improved merit function that modulates reduction of peripheral values of the mean sphere according to the prescription sphere. According to the method the amount of reduction of mean sphere of the lens peripheral regions is dependent on the prescription resulting from a modified merit function. As such, the reduction of peripheral mean sphere varies based on the prescription. According to the modified merit function and resulting improved merit function, the greater the hyperopia and/or presbyopia defined in a prescription, the smaller the reduction of the peripheral value of mean sphere. Accordingly, when the peripheral mean sphere reduction is relaxed, a near region is made wider.