Modern achievements accomplished in both cognitive neuroscience and humanâ??machine\ninteraction technologies have enhanced the ability to control devices with the human brain by\nusing Brainâ??Computer Interface systems. Particularly, the development of brain-controlled mobile\nrobots is very important because systems of this kind can assist people, suffering from devastating\nneuromuscular disorders, move and thus improve their quality of life. The research work\npresented in this paper, concerns the development of a system which performs motion control in a\nmobile robot in accordance to the eyesâ?? blinking of a human operator via a synchronous and\nendogenous Electroencephalography-based Brainâ??Computer Interface, which uses alpha brain\nwaveforms. The received signals are filtered in order to extract suitable features. These features are\nfed as inputs to a neural network, which is properly trained in order to properly guide the robotic\nvehicle. Experimental tests executed on 12 healthy subjects of various gender and age, proved that\nthe system developed is able to perform movements of the robotic vehicle, under control, in\nforward, left, backward, and right direction according to the alpha brainwaves of its operator, with\nan overall accuracy equal to 92.1%.
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