Visualization of Eye-Tracking Patterns in Autism Spectrum Disorder: Method and Dataset

Abstract

Autism spectrum disorder (ASD) is a lifelong condition generally characterized by social and communication impairments. One of the characteristic hallmarks of ASD is the difficulty of making or maintaining eye contact. In this respect, the eye-tracking technology has come into prominence to support the study and analysis of autism. This paper develops a methodology to visualize the eye-tracking patterns of ASD-diagnosed individuals with particular focus on children at early stages of development. The key idea is to transform the dynamics of eye motion into a visual representation, and hence diagnosis-related tasks could be approached using image-based techniques. The visualizations produced are made publicly available in an image dataset to be used by other studies aiming to experiment the potentials of eye-tracking within the ASD context. It is believed that the dataset can allow for developing further useful applications or discovering interesting insights using Machine Learning or data mining techniques