EVALUATION OF PSD COMPONENTS AND AAR PARAMETERS AS INPUT FEATURES FOR A SVM CLASSIFIER APPLIED TO A ROBOTIC WHEELCHAIR

André Ferreira, Teodiano Freire Bastos-Filho, Mário Sarcinelli-Filho, José Luis Martín Sánchez, Juan Carlos García García, Manuel Mazo Quintas

2009

Abstract

Two distinct signal features suitable to be used as input to a Support-Vector Machine (SVM) classifier in an application involving hands motor imagery and the correspondent EEG signal are evaluated in this paper. Such features are the Power Spectral Density (PSD) components and the Adaptive Autoregressive (AAR) parameters. Different classification times (CT) and time intervals are evaluated, for the AAR-based and the PSD-based features, respectively. The best result (an accuracy of 97.1%) is obtained when using PSD components, while the AAR parameters generated an accuracy of 94.3%. The results also demonstrate that it is possible to use only two EEG channels (bipolar configuration around C3 and C4), discarding the bipolar configuration around Cz. The algorithms were tested with a proprietary EEG data set involving 4 individuals and with a data set provided by the University of Graz (Austria) as well. The resulting classification system is now being implemented in a Brain-Computer Interface (BCI) used to guide a robotic wheelchair.

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Paper Citation


in Harvard Style

Ferreira A., Freire Bastos-Filho T., Sarcinelli-Filho M., Luis Martín Sánchez J., Carlos García García J. and Mazo Quintas M. (2009). EVALUATION OF PSD COMPONENTS AND AAR PARAMETERS AS INPUT FEATURES FOR A SVM CLASSIFIER APPLIED TO A ROBOTIC WHEELCHAIR . In Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009) ISBN 978-989-8111- 64-7, pages 7-12. DOI: 10.5220/0001379100070012


in Bibtex Style

@conference{biodevices09,
author={André Ferreira and Teodiano Freire Bastos-Filho and Mário Sarcinelli-Filho and José Luis Martín Sánchez and Juan Carlos García García and Manuel Mazo Quintas},
title={EVALUATION OF PSD COMPONENTS AND AAR PARAMETERS AS INPUT FEATURES FOR A SVM CLASSIFIER APPLIED TO A ROBOTIC WHEELCHAIR},
booktitle={Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009)},
year={2009},
pages={7-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001379100070012},
isbn={978-989-8111- 64-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009)
TI - EVALUATION OF PSD COMPONENTS AND AAR PARAMETERS AS INPUT FEATURES FOR A SVM CLASSIFIER APPLIED TO A ROBOTIC WHEELCHAIR
SN - 978-989-8111- 64-7
AU - Ferreira A.
AU - Freire Bastos-Filho T.
AU - Sarcinelli-Filho M.
AU - Luis Martín Sánchez J.
AU - Carlos García García J.
AU - Mazo Quintas M.
PY - 2009
SP - 7
EP - 12
DO - 10.5220/0001379100070012