UserLens - Web Accessibility Tool for Autism, Dyslexia & Cognitive Disorders

Abstract

Web usability continues to pose major challenges for individuals with disabilities, sensory sensitivities, or cognitive differences, as most modern websites are not designed to accommodate their varied accessibility needs. Navigating complex, dynamic, and visually dense interfaces can often be overwhelming or impractical, reducing independence and limiting participation in the digital world. The lack of adaptable design options leaves many users struggling to engage comfortably and effectively with online content. To address this, we propose a universal, user-controlled tool that enables individuals to reshape any webpage in real time according to their unique preferences. The tool allows users to adjust layouts, alter colour schemes, simplify interactions, and personalize content presentation—helping to remove distractions, improve readability, and enhance comfort. Through its modular and intuitive interface, it supports customizable profiles for different accessibility needs, such as Autism, Dyslexia, low vision, or ADHD. Designed for seamless integration with modern browsers and web platforms, it empowers users to transform online spaces into more inclusive, functional, and personally adaptive environments, demonstrating the potential of user-driven accessibility to advance digital equity.

Introduction

The text discusses UserLens, a browser-based accessibility system designed to improve web accessibility for individuals with cognitive and neurological disabilities such as dyslexia, ADHD, and Autism Spectrum Disorder (ASD). Despite the internet being a major platform for education, healthcare, and information access, many websites remain difficult to use due to accessibility barriers, excessive visual complexity, and poor compliance with accessibility standards. Studies such as the WebAIM Million report reveal millions of accessibility errors across websites, highlighting the urgent need for inclusive digital solutions.

Existing accessibility tools like reading aids, text-to-speech systems, and browser extensions provide useful features such as dyslexia-friendly fonts, summarization, and distraction reduction. However, these tools usually focus on a single accessibility function, forcing users to switch between multiple extensions and creating fragmented workflows. UserLens addresses this problem by combining visual customization, cognitive reading assistance, and AI-powered contextual support into one unified browser extension.

The related work section reviews research on:

• Adaptive interfaces, which dynamically adjust content according to user needs.
• Accessibility browser extensions, such as Grammarly, Speechify, and Helperbird.
• AI-based accessibility systems, including text simplification and summarization tools.

The text identifies several limitations in previous systems:

1. Most systems focus only on interface adaptation without improving content comprehension.
2. Existing browser extensions provide isolated rather than integrated features.
3. AI tools are often external to the browsing environment.
4. Privacy and security concerns reduce user trust in third-party tools.

UserLens overcomes these issues through a modular client-server architecture. The browser extension, built using Google Chrome Manifest V3, includes:

• A background service worker for communication and API handling.
• A popup interface for quick accessibility settings.
• A side panel offering advanced reading tools, accessibility profiles, and AI chat.
• A content script that dynamically transforms webpage content in real time.

The AI backend, developed with FastAPI, handles tasks such as:

• Text summarization
• Simplification
• Retrieval-Augmented Generation (RAG)-based question answering

The system applies accessibility transformations directly to webpages by modifying the DOM and adapting visual elements according to user preferences. Privacy safeguards are also included, automatically disabling AI processing on sensitive pages like login or payment forms.

The methodology involved literature analysis, modular system design, browser extension development, backend AI integration, and evaluation using metrics such as:

• System Usability Scale (SUS)
• NASA-TLX workload index
• WCAG compliance improvements
• Readability scores

Conclusion

UserLens proposes an integrated approach to web accessibility by combining adaptive interface customization, cognitive reading support, and AI-based contextual assistance within a single browser extension. The system is designed to address common barriers faced by users with dyslexia, ADHD, autism spectrum disorder, and low vision, especially when browsing complex and visually dense websites. By shifting accessibility support directly into the browsing environment, the project reduces dependence on separate tools and improves the continuity of user interaction. The modular architecture, privacy safeguards, and evaluation framework make the system practical for future development and research. UserLens therefore represents a step toward more inclusive, flexible, and user-centered web access.

References

Several research papers have influenced the design of UserLens: [1] Findlater et al. – Adaptive interfaces for users with disabilities. [2] Rello & Baeza-Yates – Typography optimization for dyslexic readers. [3] Rayner et al. – Rapid Serial Visual Presentation for attention challenges. [4] Lewis et al. – Retrieval-Augmented Generation architecture. [5] Bangor et al. – System Usability Scale evaluation framework. [6] Fichten et al. – Browser extensions for students with disabilities. [7] Alekseev – Integrated adaptive accessibility systems for web applications.

Copyright

Copyright © 2026 Mrs. B. Komala, Yadlapati Siva Sai Maruthi Charan, Sree Vibha Panchagnula, Pulivendala Guru Prasad, Laksh Vijayvargiya, Saisri Vaishnavi Kompella. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.