A High Frame Rate Affordable Nystagmus Detection Method with Smartphones Used in Outpatient Clinic

In this work, we present a high frame rate affordable nystagmus detection aid for outpatient clinic use. Using a Frenzel goggles and the high-speed video recording feature of a smartphone, high-frame rate eye videos of patients are obtained. Then, OpenCV morphological operation and blob detection library were modified to manually adjust the parameters according to the video to capture and track the eye center movements. Next, we correct the error caused by hand shaking during photography and predict the eyeball movement during blinking. Finally, with rule-based detecting method, nystagmus was detected and classified based on the modified tracking data. In our experimental, we collaborated with a professional ENT doctor to obtain multiple high-frame rate eye videos of patients. Experimental results show that this procedure can provide preliminary diagnosis results for physicians to refer to, but the final diagnosis needs to be made by a professional ophthalmologist. Plus, this method has been used by the ENT doctor to record the result simultaneously.