Classifying BCI signals from novice users with Extreme Learning Machine
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2017Disciplina/s
Ingeniería, Industria y ConstrucciónMateria/s
Computer ScienceArtificial Intelligence
Resumen
Volume 15, Issue 1
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Classifying BCI signals from novice users with extreme learning machine
Germán Rodríguez-Bermúdez
/ Andrés Bueno-Crespo
/ F. José Martinez-Albaladejo
Published Online: 2017-07-07 | DOI: https://doi.org/10.1515/phys-2017-0056
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Abstract
Brain computer interface (BCI) allows to control external devices only with the electrical activity of the brain. In order to improve the system, several approaches have been proposed. However it is usual to test algorithms with standard BCI signals from experts users or from repositories available on Internet. In this work, extreme learning machine (ELM) has been tested with signals from 5 novel users to compare with standard classification algorithms. Experimental results show that ELM is a suitable method to classify electroencephalogram signals from novice users.