They say that your eyes are the window to your soul.
Could they be the window to your mental health, too?
While advertisers use data on where you look and how to better catch your attention, designers use similar data to improve their products, with game and phone developers using it to offer the newest hands-free interaction technology.
Not surprisingly, eye-tracking has become a revolutionary tool for neurologists in recent years, too. In fact, research has discovered that your tiny, rapid eye movements (saccades) actually function as a window into your brain. For psychologists and other mental health professionals, they give light to your inner mental functioning.
The next question is: can capturing such rapid eye movements aid clinicians with making diagnoses of mental and neurological disorders? Whether it be autism, attention-deficit hyperactivity disorder, Parkinson’s disease or others, many researchers think there is massive potential.
“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.”
For example, autistic children typically avoid social images in favor of abstract ones, and they are less likely to make eye contact when looking at faces in images, videos– or real life. Distinct, abnormal eye-movement patterns that are similar to those found in autistic children occur in a variety of mental disorders, researchers have discovered.
As technology costs have dropped and their accuracy has improved (even at the civilian level), eye-tracking might be of greater use in the clinical setting– and soon. “There is going to be a huge growth in the accessibility of eye-tracking devices to clinicians and others,” Eizenman believes. “It won’t remain the domain of experts.”
Paired with a group of researchers from the University of Southern California and Queen’s University in Ontario, Laurent Itti, a member of USC’s iLab, concocted a data-heavy, low-cost way to identify brain disorders through eye-tracking in 2012.
Subjects in the test watched a video for 15 minutes while their eye-movements were noted. The result was a spate of data that Itti’s team needed to interpret, as they distinguished irregular eye-movement patterns from normal ones.
What Itti’s team found was astonishing: eye-movement patterns can classify mental disorders, with astonishing accuracy. They were able to identify elderly Parkinson’s patients with almost 90 percent accuracy, as well as children with attention deficit hyperactivity disorder (ADHD). Furthermore, they even identified 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.”
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