Abstract

Brain Computer Interfaces (BCI) are applications that allow users to communicate and control external devices directly by analyzing changes in brain activity without using muscle and nerve cells, which are normal pathways of the brain. It can also be said that BCIs are an alternative means of communication between the human brain and the outside world based on the electrical activities of brain activity, which can be measured by electroencephalography (EEG) devices. In the EEG measured from the human brain, when a person wants to move a limb, the potentials associated with the event are observed in the EEG. This suggests that information about changes in the activity of the human brain in the cognitive or movement decision process can be detected in the observed EEG. In this study, the attributes of the signals obtained using a four-channel EEG recorder are extracted and classified. Because the experimental study was performed while the user was awake, it processed beta signals. Considering the artifacts, the processed data was used as input data for the interface by realizing offline and online trial. The data obtained from the EEG device was processed in a computer and transmitted to a microcontroller used to control the model vehicle. Data communication is carried out wirelessly. The model vehicle is allowed to move forward-backward / right-left and diagonally.

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