Computer-aided autism diagnosis based on visual attention models using eye tracking.

ABSTRACT: An advantage of using eye tracking for diagnosis is that it is non-invasive and can be performed in individuals with different functional levels and ages. Computer/aided diagnosis using eye tracking data is commonly based on eye fixation points in some regions of interest (ROI) in an image. However, besides the need for every ROI demarcation in each image or video frame used in the experiment, the diversity of visual features contained in each ROI may compromise the characterization of visual attention in each group (case or control) and consequent diagnosis accuracy. Although some approaches use eye tracking signals for aiding diagnosis, it is still a challenge to identify frames of interest when videos are used as stimuli and to select relevant characteristics extracted from the videos.

SUBMITTER: Oliveira JS 

PROVIDER: S-EPMC8115570 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature