Eye Movement Patterns for Predicting ADHD

Attention Deficit Hyperactivity Disorder (ADHD) is a common disorder all over the world that usually diagnosed only during the years of elementary school but is developed from birth. ADHD diagnosis is based on the read and write capabilities of the subject.
Early diagnosis enables early intervention that can improve the outcome. Therefore, it is necessary to examine another method for diagnosing ADHD. In this project we examine the relation between ADHD and traces of eye movements.
Our database is eye movements recordings of preschool children (ages 4-6) during attentional tasks. This database was collected with the eye-tracker ‘Tobii’.
In order to assess the children’s attentional skills, we used the Conners questionnaire - a questionnaire that the children’s parents filled.
We developed an algorithm that predicts Conners results based on the eye movements recordings.
In addition, we developed a graphic interface (GUI) that represents the relation between different eye movements and Conners results.

Eye Movement Patterns for Predicting ADHD

Collaboration:

Prof. Tzipi Horowitz-Kraus, Faculty of Education in Science and Technology