loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Maria Claudia F. Castro ; João Pedro de O. P. Galhianne and Esther Luna Colombini

Affiliation: Centro Universitário da FEI, Brazil

ISBN: 978-989-8565-36-5

Keyword(s): EEG, Band-power Extraction, Pattern Recognition, Linear Discriminant Analysis (LDA).

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: C EEG channel data are usually used when building systems that aim at distinguishing among right and left hand movements. Few alternatives use multichannel systems when bigger sets of motor imagery are subject to classification and more inputs are required. In this context, this work proposes the use of 8 EEG channels (F,C,P, and O), disposed in a non-conventional set up, to classify up to 4 motor imagery of the upper limbs through a Linear Discriminant Analysis classifier. A spatial feature selection, prior to classification, is applied in order to improve the classification accuracy. For the many channel combinations tested, results suggest that, in addition to the motor areas, other brain areas should be considered. For the proposed system, the best classification accuracy was achieved when distinguishing between left arm and left hand (89.74%) and using only the electrodes in F areas. For the right versus left hand a 71.80% rate was obtained, with electrodes either in P and O area s or in F and P areas. To discriminate between arms and hands, independently of the body side, the best score was 83.33%, for F and P channels, whereas for right and left limbs the best score was 66.02%, with only P channels. The best classification accuracy for the 4 movement problem achieved 50.00%, using all electrodes. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.229.76.193

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Castro, Maria Claudia F.; Pedro de O. P. Galhianne, J. and Luna Colombini, E. (2013). EEG Motor Imagery Classification of Upper Limb Movements.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 314-317. DOI: 10.5220/0004235003140317

@conference{biosignals13,
author={Castro, Maria Claudia F. and João Pedro de O. P. Galhianne. and Esther Luna Colombini.},
title={EEG Motor Imagery Classification of Upper Limb Movements},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={314-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004235003140317},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - EEG Motor Imagery Classification of Upper Limb Movements
SN - 978-989-8565-36-5
AU - Castro, Maria Claudia F.
AU - Pedro de O. P. Galhianne, J.
AU - Luna Colombini, E.
PY - 2013
SP - 314
EP - 317
DO - 10.5220/0004235003140317

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.