Researchers from the American University of Florida Atlantic, in cooperation with universities and other institutions, have developed 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 movements Eye).
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 -made reports to offer to doctors.
The traditional diagnostic tools that are usually used to monitor the nystagrams such as: Video 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 tool dependent on artificial intelligence provides a low cost alternative Uncomfortable with 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 non -surgical and impressive analysis, it 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.
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 American Food and Drug Administration (FDA) for wide use in the medical field.