Sensing and Processing of EOG Signals to Control Human Machine Interface System

Human Machine Interface (HMI) has been extensively discussed to control electromechanical rehabilitation techniques using bio-signals such as EEG, EOG and EMG etc. When patients become completely or partially paralyzed, the only source or a resource offered to them are bio-signals. Among the various biosignals, EOG signals have been studied in depth because of the occurrence of a definite signal pattern. This work has been focused on controlling Human-machine interface (HMI) system that is based on Electrooculography (EOG) signals for guiding wheelchair motion manually. The user look up, down, left, right and blink to guide the wheelchair to move forward, backward, left, right and stop respectively. A New Algorithm named as “Navigation point Algorithm” has been designed to navigate the wheelchair and finds a direct path from the origin to the goal point in a single head movement. Obstacle detection sensor is also being used to notify about the obstacle that may be found in the path. The distance between the sensors and the nearest obstacle will be detected by this sensor.The process ends when the wheelchair reaches the goal