Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

Classification of Electro-encephalographic Spatial Patterns

T. MüllerContact Information, T. Ball7, R. Kristeva-Feige7, Th. Mergner7 and J. TimmerContact Information

(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.

Contact Information T. Müller
Email: muellert@physik.uni-freiburg.de

Contact Information J. Timmer

URL: http://www.fdm.uni-freiburg.de
Fulltext Preview (Small, Large)
Image of the first page of the fulltext

References secured to subscribers.



Export this chapter
Export this chapter as RIS | Text
 
Remote Address: 38.107.191.107 • Server: mpweb05
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)