Classifying Electrooculogram to Detect Directional Eye Movements

Human computer interfaces that can be controlled by eye movements may be used as intelligent rehabilitation aids. Electrooculogram (EOG), the bio-potential produced around eyes due to eye ball motion can be used to track eye movements. This paper presents a comparative study of different methods for Electrooculogram classification to utilize it to control rehabilitation aids. Electrooculogram is acquired with a designed data acquisition system and different signal features are extracted. Those features are used to classify the movements of the eyeball in horizontal and vertical direction. Based on these classified signals control commands can be generated for human computer interface.