Abstract
This paper presents a new approach to the issue of recognition and classification of electroencephalographic signals (EEG). A small number of investigations using the Emotiv Epoc Flex sensor set was the reason for searching for original solutions including control of elements of robotics with mental orders given by a user. The signal, measured and archived with a 32-electrode device, was prepared for classification using a new solution consisting of EEG signal integration. The new waveforms modified in this way could be subjected to recognition both by a classic authorial software and an artificial neural network. The properly classified signals made it possible to use them as the signals controlling the LEGO EV3 Mindstorms robot.
Highlights
Algorithms in Implementation for aAn electroencephalogram (EEG) is an image of electric activity pattern coming from the cerebral cortex
Most registered signals come from the neurons in which a large number of bioelectric phenomena, such as action potentials, post-synaptic potentials (PSP) and the phenomenon of a long-term neuron depolarization take place
It should be noted that this paper presented a few original methods and approaches to the issue of EEG signal classification that have not been used so far
Summary
An electroencephalogram (EEG) is an image of electric activity pattern coming from the cerebral cortex. Since the electric activity of the cortex is measured in microvolts, it must be increased many times—about a million times—to be observed on a computer screen. Most registered signals come from the neurons in which a large number of bioelectric phenomena, such as action potentials, post-synaptic potentials (PSP) and the phenomenon of a long-term neuron depolarization take place. Action potentials are connected with a short-term (10 ms or shorter) local current flow in an axon and a very limited potential field. A long-term depolarization of neurons or even glia may cause changes in EEG. Neuron activation potential is propagated along the axon to the nerve ending, where neurotransmitters are released. It is the synaptic potential that is the most important source of an electroencephalogram [1,2,3,4]
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