According to Medical News Today, a new study published in the Journal of Neurology claims diagnosis of ADHD, Parkinson’s disease, and Fetal Alcohol Spectrum Disorder may happen earlier thanks to the findings in this study. Each of these conditions involves attention dysfunctions and ocular control. According to the study these conditions are easy to identify by simply evaluating how the patient moves his/her eyes while watching television.
The Study of Eye Movement – New Tool in Diagnosing ADHD
This study provides new insight into what aspects of gaze control and attention ADHD affects. This information applies to other related disorders. The study reveals a promising tool as an easy and low cost screening tool, especially for young children where traditional testing methods can be difficult and inconclusive. For parents, this could be the breakthrough they have been waiting for to detect ADHD earlier. It’s a well established fact that the earlier ADHD is diagnosed the better the outcome.
“Natural attention and eye movement behavior – like a drop of saliva – contains a biometric signature of an individual and her/his state of brain function or dysfunction,” the article states. “Such individual signatures and especially potential biomarkers of particular neurological disorders that they may contain; however, have not yet been successfully decoded.”
Previous methods of detection included structured behavioral tasks, clinical evaluation, and neuroimaging. These methods are time consuming and costly, and they are also limiting because they are dependent on the patient being able to understand the directions and follow them.
Researchers at USC Viterbi School of Engineering
That’s why Professor Laurent Itti and doctoral student Po-He Tseng of the Department of Computer Science at the USC Viterbi School of Engineering, along with collaborators at Queen’s University in Canada, set out to determine a new screening method, and if the early research is any indicator, it appears they’ve been successful.
Those participating in the study had to watch television clips for 20 minutes while researchers recorded their eye movements. Researchers collected eye-tracking data, and then devised a computational model of visual attention that extracted 224 quantitative features. This allowed researchers to use the new machine learning techniques that would allow them to identify critical features that differentiated patients from control subjects.
With eye movement data from 108 subjects, the team was able to identify older adults with Parkinson’s disease with 89.6% accuracy and children with either ADHD or FASD with 77.3% accuracy.
New Test Cost Effective and Fast
“For the first time, we can actually decode a person’s neurological state from their everyday behaviour, without having to subject them to difficult or time-consuming tests,” Itti said.
Funding for this research came from the National Science Foundation, the Army Research Office, the Human Frontier Science Program and the Canadian Institutes of Health Research.
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1) n.p. (2012, September 2). “A Method Designed For Detecting Certain Neurological Disorders Through The Study Of Eye Movements.”