University of Southern California (USC) researchers have developed a method for detecting several neurological disorders by studying a person's eye movements.
Attention Deficit Hyperactivity Disorder (ADHD), Fetal Alcohol Spectrum Disorder (FASD), and Parkinson's disease each involve ocular control and attention dysfunctions, which can be identified through an evaluation of how people move their eyes while they watch TV.
As part of the study, participants were asked to watch TV clips for 20 minutes while their eye movements were recorded. Their eye-tracking data then was combined with eye-tracking data from healthy volunteers, and a computational model of visual attention extracted 224 quantitative features. The researchers then used new machine-learning techniques to identify critical features that stood out in ADHD, FASD, and Parkinson's disease patients.
The technique was able to identify older adults with Parkinson's disease with 89.6 percent accuracy, and children with either ADHD or FASD with 77.3 percent accuracy. The researches say their method provides an easily deployed, low-cost, high-throughput screening tool. "For the first time, we can actually decode a person’s neurological state from their everyday behavior, without having to subject them to difficult or time-consuming tests," says USC professor Laurent Itti.
From USC News
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