According to the researchers, natural attention and the eye movements of the patients are akin to a drop of saliva. It contains a biometric signature of a person and can indicate the state of brain function.

The conventional methods of diagnosis for these diseases include clinical evaluation, neuroimaging and structured behavioural tasks. These diagnostic methods are costly, involve lot of labor and are heavily dependant on the patient's ability to follow instructions.

On the other hand, this new method is a cost-effective screening tool that can be easily put to use in the young and the old alike. It has been designed by Po-He Tseng, a doctoral student, and Professor Laurent Itti of the Department of Computer Science at the USC Viterbi School of Engineering and their collaborators at Queen's University, Canada.

During the study, participants were told to "watch and enjoy" television clips for a period of 20 minutes. During this time, their eye movements were recorded.

Eye-tracking data was combined with normative eye-tracking data, along with a computational model of visual attention, to extract 224 quantitative features that allowed the usage of new techniques to differentiate key features that separated patients from control subjects.

Eye movement data from about 108 subjects were retrieved which allowed the researchers to identify older adults suffering from Parkinson's with 89.6 percent accuracy and those with ADHD or FASD with 77.3 percent accuracy.

It is, indeed, for the first time that the neurological state of a person has been evaluated using eye movements. This is a welcome development as it is possible to diagnose the problem subjecting them to time-consuming and difficult tests.

This research work has been published in the Journal of Neurology.

Source: Medindia