فهرست مطالب j. safaie

Electrooculogram is a bio-potential signal that can play an important role in Brain Computer Interface systems. EOG, which is the result of moving human eye bulb, has the advantage of relatively easy recording due to its higher amplitude and signal-to-noise ratio compared to other modalities (e.g. EEG). Real-time processing, classification, and feature extraction are another important factors in applicable BCI systems. In the present study, a real-time processing and cost effective BCI system have been designed and developed based on EOG signals. It contains an updated eyeglass for fixing EOG electrodes on the subject’s face and a 3D accelerometer for detecting subject’s movement. EOG signals were acquired by subject’s eye movement toward the four middle part of screen edges, which was placed in front of him/her. Expected results of the system was real-time generating of four different digital commands (Quadcopter navigation) based on the eye movement of a subject in four different directions (up, down, left and right). At the end system have been tested on five different Subjects (five trials for each subject), and 94.4% of system accuracy in detecting eye movements have been achieved.