Controlling Vehicles Using EEG Signal and Eye-Arm Collaboration
The researches and investigations on Brain signals get more popular in research areas. The remote controlling vehicles is the notice fiable research area in this concept. This study focused on this idea. In this study, electroencephalography (EEG) signals are firstly taken and analyzed. P300 potentials are taken into consideration when data are taken. The received data can be analyzed in real time by pre-processing step. The obtained EEG signals are classified by using entropy, route mean square, variance, expected value, max, min and standard deviation. For the control of the device, the closed eye and the arm standing below represent the first state, while the open eye and the air-standing arm represent the second state. In this way, in case of involuntary eye and arm movements, incorrect control of the device will be prevented. As a result of the study, the best classification result is obtained by ANN, while the best working time belongs to the proposed method. In this study, a person with proper muscular system can control the device. Moreover, for people with muscular system problems, the device can be brought to usable level with thought training for a while. Thus, the dream of 'remote control with thought' can be realized. Keywords - EEG, Brain Signal, Eye Movement, Machine Control.