AI and Accessibility: Developing an App to Adapt Texts and Interfaces for Neurodivergent Inclusion

• Ian Miranda Gomes de Souza UNIFEI
• Fabiana Costa Guedes UNIFEI

DOI: https://doi.org/10.5753/sbcas_estendido.2025.7029

Abstract

This paper presents the development of an application based on artificial intelligence (AI)for adapting texts and digital interfaces, aiming to promote accessibility for neurodivergent individuals, such as those with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). The application leverages AI to simplify texts and improve reading and digital interaction experiences. Preliminary results indicate that the proposed approach significantly enhances text comprehension, contributing to the digital inclusion of neurodivergent individuals.

References

DIX, A. Human-Computer Interaction. 3. ed. New Jersey: Prentice Hall, 2004. 17 p.

World Wide Web Consortium. Introduction to Web Accessibility. 2024. Disponível em: [link]. Acesso em: 6 dez. 2024.

American Psychiatric Association. Manual Diagnóstico e Estatístico de Transtornos Mentais: DSM-5. 5. ed. Porto Alegre: Artmed, 2014.

PASHOJA, A. C. et al. Improving reading in adolescents and adults with high-functioning autism through an assistive technology tool: A cross-over multinational study. Frontiers in Psychiatry, v. 10, 2019. DOI: 10.3389/fpsyt.2019.00546.

KIRKPATRICK, A. et al. Web Content Accessibility Guidelines (WCAG) 2.1. 2023. Disponível em: [link].

RAO, R. It’s time to prioritize assistive technology for neurodiversity. Fast Company, 2023. Disponível em: [link].

REHMAN, I. U. et al. Features of mobile apps for people with autism in a post covid-19 scenario: Current status and recommendations for apps using AI. Diagnostics, v. 11, n. 10, 2021.

REIS, B. P. F.; FELIPE, E. R. Design de interface em dispositivos móveis com foco na acessibilidade de pessoas com TEA. UNIFEI – Instituto de Ciências Tecnológicas, 2023.

MASCOTTI, T. D. S. et al. Estudos brasileiros em intervenção com indivíduos com transtorno do espectro autista: Revisão sistemática. Gerais: Revista Interinstitucional de Psicologia, v. 12, n. 1, p. 107–124, 2019. DOI: 10.36298/gerais2019120109.

PAIVA JUNIOR, F. Revista Autismo, Edição 25. São Paulo: Revista Autismo, 2024. Disponível em: [link].

FAST, E.; CHEN, B.; BERNSTEIN, M. S. Empath: Understanding topic signals in large-scale text. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI). San Jose, CA, USA: ACM, 2016. Disponível em: [link].

YUSRI, A. N. bin et al. Speed reading tool powered by artificial intelligence for students with ADHD, dyslexia, or short attention span. In: Computational Intelligence, Universiti Teknologi Malaysia. Johor Bahru, Malaysia, 2024. Disponível em: [link].

DEVARAJ, A. et al. Paragraph-level simplification of medical texts. arXiv preprint, arXiv:2104.05767, 2021. Disponível em: [link]. Acesso em: 6 dez. 2024.

KNAPPICH, F. et al. Simplificação textual baseada em pesos de perda ponderados: Estudo com modelos LLaMA-2. Journal of Language Models, 2023.