Self-Organizing Maps for Event-Related Potential Data Analysis

Lukáš Vařeka; Pavel Mautner

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Paper

Self-Organizing Maps for Event-Related Potential Data Analysis

Topics: Human-Machine Interfaces for Disabled Persons; Pattern Recognition and Machine Learning

In Proceedings of the International Conference on Health Informatics - Volume 0BIOSTEC, 387-392, 2014 , ESEO, Angers, Loire Valley, France

Authors: Lukáš Vařeka and Pavel Mautner

Affiliation: University of West Bohemia, Czech Republic

Keyword(s): Event-Related Potentials, P300, Self-Organizing Maps, BCI.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Health Information Systems ; Human-Machine Interfaces for Disabled Persons ; Pattern Recognition and Machine Learning

Abstract: Event-Related Potentials (ERPs) and especially the P300 component have been gaining attention in braincomputer interface design and neurobiological research. The detection of the P300 component in electroencephalographic signal is challenging since its signal-to-noise ratio is very low. Instead of using traditional supervised pattern recognition, this paper discusses using unsupervised neural networks for the P300 classification purposes. To validate the proposed approach, a method for the P300 detection based on matching pursuit and self-organizing maps is proposed and evaluated. The results may be applied to the design of brain-computer interfaces.

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Paper citation in several formats:

Vařeka, L. and Mautner, P. (2014). Self-Organizing Maps for Event-Related Potential Data Analysis. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2014) - HEALTHINF; ISBN 978-989-758-010-9; ISSN 2184-4305, SciTePress, pages 387-392. DOI: 10.5220/0004885103870392

@conference{healthinf14,
author={Lukáš Va\v{r}eka. and Pavel Mautner.},
title={Self-Organizing Maps for Event-Related Potential Data Analysis},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2014) - HEALTHINF},
year={2014},
pages={387-392},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004885103870392},
isbn={978-989-758-010-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2014) - HEALTHINF
TI - Self-Organizing Maps for Event-Related Potential Data Analysis
SN - 978-989-758-010-9
IS - 2184-4305
AU - Vařeka, L.
AU - Mautner, P.
PY - 2014
SP - 387
EP - 392
DO - 10.5220/0004885103870392
PB - SciTePress