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Authors: Mario Salerno ; Giovanni Costantini ; Daniele Casali ; Giancarlo Orengo ; Pietro Cavallo ; Giovanni Saggio ; Luigi Bianchi ; Lucia Quitadamo and Maria Grazia Marciani

Affiliation: Università di Roma “Tor Vergata”, Italy

ISBN: 978-989-674-018-4

Keyword(s): Support Vector Machine, Classification, Brain computer interface.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer Vision, Visualization and Computer Graphics ; Cybernetics and User Interface Technologies ; Devices ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Information and Systems Security ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: A Support Vector Machine (SVM) classification method for data acquired by EEG registration for brain/computer interface systems is here proposed. The aim of this work is to evaluate the SVM performances in the recognition of a human mental task, among others. Such methodology could be very useful in important applications for disabled people. A prerequisite has been the developing of a system capable to recognize and classify the following four tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a nursery rhyme. The data set exploited in the training and testing phases has been acquired by means of 61 EEG electrodes and consists of several time series. These time data sets were then transformed into the frequency domain, in order to obtain the power frequency spectrum. In such a way, for every electrode, 128 frequency channels were obtained. Finally, the SVM algorithm was used and evaluated to get the prop osed classification. (More)

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Paper citation in several formats:
Salerno M.; Costantini G.; Casali D.; Orengo G.; Cavallo P.; Saggio G.; Bianchi L.; Quitadamo L.; Grazia Marciani M. and (2010). SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS.In Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010) ISBN 978-989-674-018-4, pages 240-244. DOI: 10.5220/0002721802400244

@conference{biosignals10,
author={Mario Salerno and Giovanni Costantini and Daniele Casali and Giancarlo Orengo and Pietro Cavallo and Giovanni Saggio and Luigi Bianchi and Lucia Quitadamo and Maria {Grazia Marciani}},
title={SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS},
booktitle={Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)},
year={2010},
pages={240-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002721802400244},
isbn={978-989-674-018-4},
}

TY - CONF

JO - Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)
TI - SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS
SN - 978-989-674-018-4
AU - Salerno, M.
AU - Costantini, G.
AU - Casali, D.
AU - Orengo, G.
AU - Cavallo, P.
AU - Saggio, G.
AU - Bianchi, L.
AU - Quitadamo, L.
AU - Grazia Marciani, M.
PY - 2010
SP - 240
EP - 244
DO - 10.5220/0002721802400244

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