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Classification of Electro-encephalographic Spatial Patterns
| Book Series | Lecture Notes in Computer Science |
| Publisher | Springer Berlin / Heidelberg |
| ISSN | 0302-9743 (Print) 1611-3349 (Online) |
| Volume | Volume 1933/2000 |
| Book | Medical Data Analysis |
| DOI | 10.1007/3-540-39949-6 |
| Copyright | 2000 |
| ISBN | 978-3-540-41089-8 |
| DOI | 10.1007/3-540-39949-6_9 |
| Pages | 67-82 |
| Subject Collection | Computer Science |
| SpringerLink Date | Saturday, January 01, 2000 |
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Classification of Electro-encephalographic Spatial Patterns
T. Müller6 , T. Ball7, R. Kristeva-Feige7, Th. Mergner7 and J. Timmer6 
| (6) |
Zentrum für Datenanalyse und Modellbildung, Universität Freiburg, Eckerstr. 1, 79104 Freiburg, Germany |
| (7) |
Neurologische Universitätsklinik, NeurozentrumBreisacher Str. 64, 79106 Freiburg, Germany |
Abstract
The aim of this study is to describe a general approach to determine important electrode positions in the case when the measured
EEG-signal is used for classification. To classify planning of movement of right and left index finger, three diferent approaches
were compared: classification using a physiologically motivated set of four electrodes, a set determined by principal component
analysis and electrodes determined by spatial pattern analysis. Spatial pattern analysis enhanced the classification rate
significantly from 61:3 ±1:8% (with four electrodes) to 71:8 ±1:4% whereas the classification rate using the principal component
analysis is significantly lower (65:2 ±1:4%). Most of the 61 electrodes used had no influence on the classification rate so
that in future experiments the setup can be simplified drastically to 6 to 8 electrodes without loss of information.
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