Abstract

Eye movement research is an established methodology and widely used in fundamental research fields such as psychology or neuroscience. Most research is performed in controlled environments with screen-based eye trackers, but demand for a wearable requirement is on the rise. Yet, a state of the art wearable eye tracking system thus far has not been feasible for subjects with refractive errors; therefore, a trial frame is proposed for researching the eye movement of people with or without refractive errors. Two iris cameras and several infrared radiation LEDs were fixed behind the frame for recording eye images. The images were sent to a host computer using 2.4G wireless, which was also fixed on the frame. The entire electronic system in the trial frame was driven using a battery. Eye position in the images was recognized and segmented by a model that was trained through machine learning. Then the pupil and blinks were detected from the segmented eye area using ellipse fitting and the eye aspect ratio. Experiments showed that the correct rate of pupil and blink detections were 97.24% and 96.14%, respectively.

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