Predictive Model for Dyslexia from Fixations and Saccadic Eye Movement Events

• Published in: Computer methods and programs in biomedicine Vol. 195; p. 105538
• Main Authors: Jothi Prabha, A, Bhargavi, R
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.10.2020
• Subjects: Algorithms; Dispersion-threshold identification algorithms; Dyslexia - diagnosis; Eye Movements; Humans; Hybrid SVM–PSO; K-Nearest Neighbor; Logistic Regression; Random Forest Classifier; Reading; Saccades; Statistical features; Support Vector Machine; Velocity-threshold identification algorithm; Dispersion-threshold identification algorithms; Logistic Regression; K-Nearest Neighbor; Support Vector Machine; Statistical features; Velocity-threshold identification algorithm; Hybrid SVM–PSO; Random Forest Classifier

•Explore and identify a set of eye movement features that contribute more for prediction of dyslexia using machine automatically•A machine learning model to classify dyslexics and non-dyslexics using the identified eye movement features Dyslexia is a disorder characterized by difficulty in reading s...