The ‘autism symptom index’ captures gaze patterns that track with severity of autism traits. One of the algorithms, called the ‘autism risk index,’ identifies gaze patterns that correlate with autism diagnosis. The researchers created two algorithms based on eye-tracking data from 150 of the children. In one clip, a person tells her officemate to be quiet in another, abstract shapes share the screen with a person engaging in an ordinary activity, such as kicking a ball. The video shows social scenes or a mixture of social and nonsocial stimuli. In a room next to the clinic, researchers monitored the children’s gaze as the children watched a five-minute video. All of the children had been flagged as being at risk for autism and referred to a clinic for standard diagnostic testing 91 of them received an autism diagnosis based on standard clinical tests. The researchers used eye-tracking data from 201 children aged 1 to 17 years to create algorithms that predict autism risk and severity. In the new study, researchers parlay this disparity in gaze into a diagnostic tool. People on the spectrum tend to focus on different parts of an object or scene than their typical peers do 2. 44 children (ASD n 21 TD n 23) participated in the study (10,362 valid observations) across ve regions of interest (left eye, right eye, eye region, face and screen). Some scientists have suggested that eye tracking could speed autism diagnosis and make it more objective. 20 animal faces) among children with ASD using an eye tracking paradigm. These assessments can take up to three hours to administer. They might also provide clues to the severity of the child’s autism features, according to a new study 1.Ĭlinicians typically diagnose autism using both a caregiver questionnaire (the Autism Diagnostic Interview-Revised) and a rigorous clinical evaluation called the Autism Diagnostic Observation Schedule (ADOS). Two novel algorithms that analyze where a child looks as she views a video could help clinicians spot autism. 2002) monitored the eye movements of five adult males with autism and five controls whilst they performed a test of emotion recognition from photographs of facial expressions. Using eye tracking, our past studies revealed that when presented with social and geometric images, a subset of ASD toddlers preferred viewing geometric images, and these toddlers also had greater symptom severity than ASD toddlers with greater social. One of the first studies using eye-tracking in autism (Pelphrey et al. We investigated the fixation times of 37 ASD and 37 typically developing (TD) children ages 46 watching a 10-second video of a female speaking. To overcome the difficulties of working with young children, developing a short and informative paradigm is crucial for ET. Watchful gaze: Researchers track a person’s eyes as they land on ‘regions of interest,’ such as a face or objects in the environment.Ĭourtesy of Thomas Frazier and Eric Klingemier / Cleveland Clinic Children’s Center for Autism The wide range of ability and disability in ASD creates a need for tools that parse the phenotypic heterogeneity into meaningful subtypes. Eye tracking (ET) holds potential for the early detection of autism spectrum disorder (ASD).