MATEC Web Conf.
Volume 161, 201813th International Scientific-Technical Conference on Electromechanics and Robotics “Zavalishin’s Readings” - 2018
|Number of page(s)
|Robotics and Automation
|18 April 2018
Mobile robot control based on noninvasive brain-computer interface using hierarchical classifier of imagined motor commands
Peter the Great Saint-Petersburg Polytechnic University, Russia
2 Sagol School of Neuroscience, Tel Aviv University, Israel
* Corresponding author: firstname.lastname@example.org
The study describes approaches of direct and supervisor control of a mobile robot based on a non-invasive brain-computer interface. An interface performs electroencephalographic signal decoding, which includes several steps: filtering, artefact detection, feature extraction, and classification. In this study, a classifier with hierarchical structure was developed and applied. Description of a committee of classifiers based on neural networks and support vector machines is given. The developed classifier demonstrated accuracy 50 ± 5% of single trial decoding of four classes of imaginary fine movements. Prospects of using non-invasive brain-computer interface for control of mobile robots was described. Key applications of the system are maintenance of immobilized patients and rehabilitation procedures both in clinic and at home.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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