Diagnosis of mental problems by electronic tracking of eye movements

Scientific American    Eye-tracking has become the tech trend du jour. Advertisers use data on where you look and when to better capture your attention. Designers employ it to improve products. Game and phone developers utilize it to offer the latest in hands-free interaction.

Eye-tracking has become the tech trend du jour. Advertisers use data on where you look and when to better capture your attention. Designers employ it to improve products. Game and phone developers utilize it to offer the latest in hands-free interaction.

“Visual scanning reflects a model of the world that exists inside the brain of each individual,” explains Moshe Eizenman, a leading eye-tracking researcher at the University of Toronto. “People with mental disorders have a model of the world that is slightly different than that of normal people—and by moving their eyes, they provide information about this different model.” Autistic children, for example, tend to avoid social images in favor of abstract ones, and they also more rarely and fleetingly make eye contact when looking at faces in an image or video in comparison with nonautistic kids. Similarly distinct, abnormal eye-movement patterns occur in a number of mental disorders, scientists have found. [...]

In a small, proof-of-concept study (pdf) Itti’s team found that their algorithm could classify mental disorders through eye-movement patterns: They identified elderly Parkinson’s patients with nearly 90 percent accuracy as well as children with attention deficit hyperactivity disorder (ADHD) or fetal alcohol spectrum disorder with 77 percent accuracy. “This is very different from what people have done before. We’re trying to have completely automated interpretation of the eye movement data,” Itti says. “So you don’t need to have a scientist look at the data to figure out what’s going on; we’re using algorithms and machines to [identify] the linkage between eye-movement and cognition.”