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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Müller, T., Ball, T., Kristeva-Feige, R., Mergner, T., Timmer, J. (2000). Classification of Electro-encephalographic Spatial Patterns. In: Brause, R.W., Hanisch, E. (eds) Medical Data Analysis. ISMDA 2000. Lecture Notes in Computer Science, vol 1933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39949-6_9
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DOI: https://doi.org/10.1007/3-540-39949-6_9
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