Artificial Neural Networks as a Tool for Recognition of Movements by Electroencephalograms

Semen A. Kurkin, Elena N. Pitsik, Vyacheslav Yu. Musatov, Anastasia E. Runnova, Alexander E. Hramov

2018

Abstract

Recognition of human brain activity associated with imaginary or real movements is a complex task that requires an accurate and conscious choice of analysis approach. Recent researches revealed the great potential of machine learning algorithms for electroencephalography data analysis due to the ability of these methods to establish nonlinear and nonstationary correlations, and the most attention is focused on artificial neural networks (ANNs). Here, we introduce the ANN-based method for recognition and classification of patterns in electroencephalograms (EEGs) associated with imaginary and real movements of untrained volunteers. In order to get the fastest and the most accurate classification performance of multichannel motor imagery EEG-patterns, we propose our approach to selection of appropriate type, topology, learning algorithm and other parameters of neural network. We considered linear neural network, multilayer perceptron, radial basis function network and support vector machine. We revealed that appropriate quality of recognition can be obtained by using particular groups of electrodes according to extended international 10−10 system. Besides, pre-processing of EEGs by low-pass filter can significantly increase the classification performance. Obtained results provide better insight on neural networks potential for integration in brain-computer interfaces that are based on EEG patterns recognition.

Paper Citation

in Harvard Style

A. Kurkin S. (2018). Artificial Neural Networks as a Tool for Recognition of Movements by Electroencephalograms.In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-321-6, pages 166-171. DOI: 10.5220/0006860201660171

in Bibtex Style

@conference{icinco18,
author={Semen A. Kurkin},
title={Artificial Neural Networks as a Tool for Recognition of Movements by Electroencephalograms},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2018},
pages={166-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006860201660171},
isbn={978-989-758-321-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Artificial Neural Networks as a Tool for Recognition of Movements by Electroencephalograms
SN - 978-989-758-321-6
AU - A. Kurkin S.
PY - 2018
SP - 166
EP - 171
DO - 10.5220/0006860201660171