Eye-tracking-based Artificial Intelligence Detects Abnormalities of the Oculomotor System in Type 1 Diabetes
Eye-tracking-based Artificial Intelligence Detects Abnormalities of the Oculomotor System in Type 1 Diabetes
Abnormalities of the oculomotor system may represent an early sign of diabetic neuropathy and are currently poorly studied. The investigators designed an eye-tracking-based test to evaluate the oculomotor function in patients with type 1 diabetes.
The investigators used the SRLab -Tobii TX300 Eye tracker®, an eye-tracking device, coupled with a software that we developed to test abnormalities of the oculomotor system. The software consists in a series of screens divided in 5 classes of parameters (Resistance, Wideness, Pursuit, Velocity and Optokinetic Nystagmus [OKN]) to evaluate both smooth and saccadic movement in different directions. 40 healthy volunteers and 40 patients with long-standing type 1 diabetes will be enrolled to analyze the alterations in the oculomotor system and function.
The study will enroll 40 healthy volunteers and 40 patients with long-standing type 1 diabetes. The aim of the study is to analyze alterations in the oculomotor system function as an early sign of diabetic neuropathy. A novel eye-tracking-based test will be employed and 5 parameters will be analyzed through the use of a computer-based test which will record timeframes of eye movements towards an object, type of eye movements, time between the first eye movement, number of visualization required to recognize the object across the screen. Each of these parameter will be employed to assess whether Resistance, Wideness, Pursuit, Velocity of eye movements and movements related to the Optokinetic Nystagmus are altered in type 1 diabetes as compared to non diabetic subjects.
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