DR. LOUIS ALPERT
As an MIT alumnus who began his mathematics teaching career at the institute nearly 60 years ago, I have quoted from the “MIT Technology Review” at times when explaining issues, especially those on the cutting edge of science. Today, I reference the MIT Review’s article “Looking Concussion In The Eye.”
This article describes a most exciting contribution to medical science which is the “brain child” of two sisters, Dr. Rosina Samadani, an MIT alumnus with two degrees in Mechanical Engineering from MIT and a PhD in Biomedical Engineering from Northwestern University and her sister,Dr. Uzma Samadani, Associate professor of Neurosurgery at the University of Minnesota.
“Ask three neurologists if someone has a concussion, …and you’ll get four different opinions. A concussion, typically caused by a blow to the head, is an injury that temporarily impairs brain function-and with no clinical standard, or even an agreed-upon symptom checklist, diagnosis comes down to a judgment call based on hard-to-assess things like how nauseated or drowsy someone feels.”
“About seven years ago, Uzma was trying to determine whether severely brain-injured patients were improving, so she developed an eye-tracking device to see if they could follow a moving video on a screen…As she evaluated the data gathered by her device, she realized it was allowing her to detect not only the patients’ tracking ability but also restrictions in their eyes’ range of motion. It dawned on her that these restrictions indicated problems with specific nerve pathways, meaning that she had found a way to measure-and possibly locate-brain injury..”
Uzma then consulted with her sister, Rosina,and they formed a company, Oculogica, and developed a tabletop eye-tracking device called “EyeBox” which sends a small video clockwise around the perimeter of a rectangular screen for 220 seconds. As a patient watches this video, a binocular camera separately tracks each eye and gathers about 100,000 data points at high frequency which is then fed into algorithms that calculate nearly 100 different things such as speed, coordination and range of motion. “Using statistical analysis and machine learning, Uzma identified the metrics strongly correlated with concussion in clinical studies and she developed an algorithm based on these metrics to score the severity of a brain injury….
EyeBox is in clinical trials and Oculogica is working on getting FDA clearance for concussion diagnosis-something no other device currently has!”
This article concludes by stating that EyeBox “minimizes the guesswork involved in diagnosing concussions…that kind of tool can be a big help to (football) coaches trying to attract players and defend a sport increasingly seen as too dangerous.”
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