Next-Generation Visual System Characterization Platform

Publication ID: 24-11857254_0010_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Visual System Characterization Platform,” Published Technical Disclosure No. 24-11857254_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857254_0010_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,254.

Summary of the Inventive Concept

A futuristic visual system characterization platform that leverages artificial intelligence, machine learning, and digital twins to provide real-time, personalized, and predictive visual system assessments.

Background and Problem Solved

The original patent disclosed a method for characterizing the visual system of a subject using measures of sensitivity to contrast. However, this approach has limitations, such as being time-consuming, requiring extensive data collection, and lacking personalization. The new inventive concept addresses these limitations by introducing a paradigm shift in visual system characterization, enabling real-time, predictive, and personalized assessments.

Detailed Description of the Inventive Concept

The next-generation visual system characterization platform comprises a neural network-based visual signal processing module, a cloud-based data repository, a machine learning-based analytics engine, and a visualization module. The platform uses digital twins to simulate the impact of internal noise sources on the visual system, allowing for real-time optimization of characterization parameters. Additionally, the platform includes a wearable device for real-time visual system characterization, providing personalized recommendations for visual system improvement. The platform's predictive capabilities enable the forecasting of visual system degradation, allowing for proactive measures to be taken.

Novelty and Inventive Step

The new inventive concept introduces a novel combination of artificial intelligence, machine learning, and digital twins to revolutionize visual system characterization. The use of neural networks, cloud-based data repositories, and machine learning-based analytics engines provides a significant improvement over the original patent's approach, enabling real-time, personalized, and predictive assessments.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, varying levels of digital twin complexity, or the integration of additional sensors and data sources. Variations could also include the application of the platform in different industries, such as healthcare, education, or entertainment.

Potential Commercial Applications and Market

The next-generation visual system characterization platform has vast commercial potential in various industries, including healthcare, education, and entertainment. The platform's predictive capabilities and personalized recommendations could revolutionize the way visual system disorders are diagnosed and treated, while its real-time assessment capabilities could transform the way visual system performance is evaluated and improved.

CPC Classifications

SectionClassGroup
A A61 A61B3/0025
A A61 A61B3/0041
A A61 A61B3/022
A A61 A61B3/032
A A61 A61B3/066
G G16 G16H30/40
G G16 G16H50/30

Field of Art

Medical imaging and visual system diagnostics, with expertise in neurophysiological assessment techniques, signal processing, and advanced diagnostic technologies involving ophthalmological and neurological measurement systems

Person of Ordinary Skill (PHOSITA) Profile

A professional with advanced training in biomedical engineering, neuroscience, or medical physics, possessing knowledge of signal processing algorithms, neural system characterization methods, and emerging diagnostic technologies

Obviousness Rationale

A person having ordinary skill would recognize that the published technical disclosure represents a predictable technological evolution of the source patent's visual system characterization method by integrating contemporary machine learning and digital twin technologies. The fundamental approach of quantifying visual system sensitivity remains consistent, with the PTD merely introducing computational and predictive enhancements that would be considered routine optimization by a skilled practitioner. The core technical problem of characterizing visual system performance is addressed through increasingly sophisticated computational techniques that extend rather than fundamentally transform the original patent's methodology.

Obvious Combinations & Variations

Source Patent Element
Quantifying visual signal processing elements' impact through equivalent input noise values
PTD Variation
Neural network-based learning of internal noise source impacts on visual system sensitivity
Obviousness Reasoning
Applying machine learning to noise characterization represents a predictable application of contemporary computational techniques to an established diagnostic methodology
Source Patent Element
Measuring sensitivity to contrast across different luminance and frequency ranges
PTD Variation
Digital twin simulation of visual system performance across varied parameters
Obviousness Reasoning
Creating computational models to simulate complex physiological systems is a known technique for extending diagnostic capabilities through predictive modeling
Source Patent Element
Visual test methodology involving external noise application
PTD Variation
Cloud-based data repository and machine learning analytics for trend identification and personalized assessment
Obviousness Reasoning
Leveraging big data and machine learning for diagnostic pattern recognition is a standard technological progression in medical diagnostic technologies
Source Patent Element
Characterizing visual system processing elements
PTD Variation
Wearable device for real-time continuous visual system monitoring
Obviousness Reasoning
Miniaturization and continuous monitoring represent incremental technological improvements that would be obvious to a skilled practitioner seeking more dynamic diagnostic capabilities
Source Patent Element
Contrast threshold assessment methodology
PTD Variation
Predictive modeling of future visual system degradation using historical data
Obviousness Reasoning
Developing prognostic capabilities through statistical modeling is a natural extension of diagnostic technologies, representing an obvious improvement to existing assessment methodologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857254 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations obvious, as they represent predictable technological extensions employing known computational techniques to enhance visual system characterization methodologies. The disclosed innovations constitute routine optimization and combination of prior art elements, rendering subsequent claims involving similar technological approaches anticipated and non-patentable under standard obviousness criteria.

Original Patent Information

Patent NumberUS 11,857,254
TitleMethod and system for characterizing the visual system of a subject
Assignee(s)Essilor International, SORBONNE UNIVERSITE