A human-robot interface based on electrooculography

Abstract

Design and implementation of an electrooculography based gaze-controlled robotic system is presented. The robot system consists of signal acquisition, pattern recognition, control strategy and robot motion modules. The user's eye gaze movements are reconstructed from electrooculogram (EOG) signals, which are recorded from the face in real time. The eye movement patterns, e.g., saccades, fixation and blinks are detected from the raw eye gaze movement data by a pattern recognition module. The control strategy module interprets the user's intention from the eye movement patterns based on predefined protocols. A horizontally mounted robot, emulating the skeletomuscular configuration of the human arm, is controlled by the robot motion control module to execute the interpreted user intention. The performance results of two control strategies are discussed.