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Using Neural Networks for Classification of the Changes in the EEG Signal Based on Facial Expressions

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Analysis and Classification of EEG Signals for Brain–Computer Interfaces

Part of the book series: Studies in Computational Intelligence ((SCI,volume 852))

Abstract

Artificial intelligence dates back to 1950, when a group of pioneers in informatics began asking questions related to the ability “to think” by computers defined as automation of intellectual tasks performed by human beings. The consequences of the questions asked by the pioneers of informatics have been discovered until now in the form of many scientific and technological achievements. Artificial intelligence in itself is a very general discipline, which includes the issues from such fields of knowledge as machine learning and deep learning, and also numerous other approaches that do not require learning.

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Reference

  1. Ghaemia, A., Rashedia, E., Mohammad Pourrahimib, A., Kamandara, M., Rahdaric, F.: Automatic channel selection in EEG signals for classification of left or right hand movement in brain computer interfaces using improved binary gravitation search algorithm. Biomed. Signal Process. Control 33, 109–118 (2017). https://doi.org/10.1016/j.bspc.2016.11.018

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Correspondence to Szczepan Paszkiel .

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Paszkiel, S. (2020). Using Neural Networks for Classification of the Changes in the EEG Signal Based on Facial Expressions. In: Analysis and Classification of EEG Signals for Brain–Computer Interfaces. Studies in Computational Intelligence, vol 852. Springer, Cham. https://doi.org/10.1007/978-3-030-30581-9_7

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