The work presented in this thesis concerns the development of a system which performs motion control in a mobile robot in accordance to the eyes’ blinking of a human operator via a synchronous and endogenous Electroencephalography-based Brain-Computer Interface, which uses alpha brain waveforms. The received signals are filtered in order to extract suitable features. These features are fed as inputs to a neural network, which is properly trained in order to properly guide the robotic vehicle. Experimental tests executed, proved that the system developed is able to perform movements of the robotic vehicle, under control, in forward, left, backward and right direction according to the alpha brainwaves of its’ operator, with an overall accuracy equal to 92.1%.
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University of West Attica
