Artifacts Removing From EEG Signals by Ica Algorithms
Asadi Srinivasulu · IOSR Journal of Electrical and Electronics Engineering · 2012
Recent advances in computer hardware and signal processing have now a way to communicate with the outside world, but even with the last modern techniques, such systems still suffer communication Recent advances in computer hardware and signal processing have made possible the use of EEG signals or "brain waves" for communication between humans and computers The EEG is composed of electrical potentials arising from several sources.Each source (including separate neural clusters, blink artifact) projects a unique topography onto the scalp.These maps are mixed according to the principle of linear superposition.Here we attempt a Independent component analysis (ICA) of different algorithms to reverse the superposition by separating the EEG into mutually independent scalp maps, later removing their noise by set the threshold level and finally we classify the five mental tasks through the use of the electroencephalogram (EEG) by the neural network technique.