Eye-tracking technology (Brain Health EyeQ; RightEye, Bethesda, MD) that captures data on people’s eye movements has been used to produce a database of 1 billion data points from 100,000 individuals. Data includes eye tracking measures of alignment, object tracking, depth perception, and dynamic visual acuity. It is hoped that these data will help develop new understanding of early indicators for neurologic disorders.
As the technology collects more data, machine learning algorithms produce findings for well-known and underrepresented conditions that were not previously associated with eye movements and vision. The metrics provide a high level of granularity for oculomotor-related data, and eventually could comprise a comparator data set when examining individuals for concussions or other neurologic disorders.
Research organizations are actively using the information to study traumatic brain injury and identify eye-movement patterns that might aid in earlier detection of conditions such as Parkinson’s disease.
“We have compelling data that eye tracking can be used to reliably detect neurologic dysfunction across multiple domains,” said George Gitchel, PhD, director of clinical research at the Southeast Parkinson’s Disease Research, Education, and Clinical Center at the Richmond Veterans Affairs Medical Center. “The output from the Righteye system represents an evolutionary leap in eye tracking research. Large studies, epidemiological research and other protocols that were once thought to be incredibly burdensome and logistically impossible have suddenly become easy to conduct using Righteye.”
Kevin J. Felice, DO
Arnold M. Salazar; Amanda M. Leisgang; Andrew A. Ortiz; and Jefferson W. Kinney, PhD