Machine learning eye exams aid neurological research

Eye exams that leverage machine learning to track eye movement behavior are providing universities, research institutions and governmental agencies with more than a billion data points to better understand the connection between vision and neurological disease, according to health tech company RightEye.

RightEye “EyeQ” tests incorporate more than 650 unique metrics that capture precise information about a patient’s eye movements, the company said in a statement, including eye alignment and teaming, object tracking, depth perception and dynamic visual acuity. More than 100,000 tests have been conducted using the system, resulting in over a billion data points RightEye claims provide an “unprecedented level of granularity” for identifying vision-related issues and opportunities to strengthen vision.

The company has compiled its findings in a database that’s been used by Emory University, Duke University, the Richmond Veteran Affairs Medical Center, the U.S. government and more to study eye movement. The U.S. Department of Defense and Department of Veterans Affairs are applying the tech to a traumatic brain injury research project, and the Richmond center uses RightEye to detect distinct eye movement patterns that might signal the onset of serious neurological conditions like Parkinson’s disease.