Classifying BCI signals from novice users with Extreme Learning Machine

Área de investigación: Biomedical Engineering Año: 2017
Tipo de publicación: Artículo Palabras clave: Brain Computer Interface, Motor Imagery, Extreme Learning Machine, Novice users
Autores: Rodríguez-Bermúdez, Germán; Bueno-Crespo, Andrés; Martinez-Albaladejo, F. José
Journal: Open Physics Volumen: In press
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 has been tested with signals from 5 novel users to compare with standard classification algorithms. Experimental results show that Extreme Learning Machine is a suitable method to classify electroencephalogram signals from novice users.