Researchers from the American University of Florida Atlantic have developed – in cooperation with universities and other institutions – an innovative initial model based on deep learning, and benefits from direct health data to help diagnose “nystagmus”, which is a pathological condition during which involuntary movements occur in the eye, and are often associated with neurological or physical disorders (disorders that occur in the vestibular system responsible for balance And eye movements).
The new approved tool provides a low -cost and easy -to -use alternative for a dimension as the tool follows 468 reference points in the face instantaneously, analyzes the speed of eye movement, and generates ready reports to offer to doctors.
There are several problems facing the traditional diagnostic tools that are usually used to monitor the nystagmus such as: VIG’s “VNG” or electronic planning “ENG”, the most important of which are: high costs that exceed 100 thousand dollars sometimes, the large equipment you need, and the inconvenience that may cause it to patients during the tests. While the new artificial intelligence tool provides a low -cost and comfortable alternative to the patient, it provides a quick and reliable examination to detect balance disorders and abnormal eye movements.
“Although our technology is still in its early stages, it has the ability to change the form of health care for patients with vestibular and neurological disorders. Through its ability to provide a non -surgical and impressive analysis that can be widely used in clinics, emergency rooms and even in homes,” said Dr. Harshall Sangovi, the lead author of the study and post -PhD classmate.
The research team is currently improving the accuracy of the model, expanding its test to include various categories of patients in different regions, and obtaining the approval of the US Food and Drug Administration “FDA” for wide use in the medical field.