Classification of Autism spectrum disorder severity using eye tracking data based on visual attention model

Published: 30-08-2019| Version 1 | DOI: 10.17632/z2zfh673wy.1
Contributor:
Mirian Biasão

Description

We proposed a supervised method to classify autism spectrum disorder in two groups (severe and nonsevere) by using eye-tracking data processed based on a computational Model of Visual Attention. The use of eye tracking to classify subgroups of ASD may contribute to aid in decision making from diagnosis to treatment definition. Further studies, using larger sample sizes, other phenotypic data, such as the presence of comorbidities, behavioral profile, as well as using more free viewing images are necessary so that the use of eye tracking technique could be used to subgroup patients in clinical practice.

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