Early Detection of Dyslexia Using Multimodal Analysis of Behavioral, Neurophysiological and Linguistic Markers

Garima Swami, Yogesh K M

2025

Abstract

Dyslexia is a complex neurodevelopmental learning disorder characterized by persistent difficulties in reading, spelling, and writing, which can significantly impact academic performance, self-esteem, and overall quality of life. Despite its prevalence, dyslexia often goes undiagnosed due to the limitations of traditional diagnostic methods, which are typically timeconsuming, subjective, and require substantial resources. Early identification and targeted interventions are critical to mitigating the negative effects of dyslexia and improving learning outcomes. This paper explores the potential of artificial intelligence (AI) technologies to revolutionize the detection and support of dyslexic learners through automation and precision. It proposes an innovative system that integrates advanced AI methodologies, including machine learning, natural language processing, and adaptive learning systems, to deliver a robust and scalable solution. By leveraging multimodal data such as eye-tracking metrics, phonological assessments, and text-based evaluations, the system offers a holistic approach to dyslexia diagnosis and support.

Paper Citation

in Harvard Style

Swami G. and K M Y. (2025). Early Detection of Dyslexia Using Multimodal Analysis of Behavioral, Neurophysiological and Linguistic Markers. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 338-345. DOI: 10.5220/0013615600004664

in Bibtex Style

@conference{incoft25,
author={Garima Swami and Yogesh K M},
title={Early Detection of Dyslexia Using Multimodal Analysis of Behavioral, Neurophysiological and Linguistic Markers},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={338-345},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013615600004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Early Detection of Dyslexia Using Multimodal Analysis of Behavioral, Neurophysiological and Linguistic Markers
SN - 978-989-758-763-4
AU - Swami G.
AU - K M Y.
PY - 2025
SP - 338
EP - 345
DO - 10.5220/0013615600004664
PB - SciTePress