Designing optimal spatial filters for single-trial EEG classification in a movement task (1998)
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BibTeX
@MISC{Müller-Gerking98designingoptimal,
author = {Johannes Müller-Gerking and Gert Pfurtscheller and Henrik Flyvbjerg},
title = {Designing optimal spatial filters for single-trial EEG classification in a movement task},
year = {1998}
}
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Abstract
We devise spatial filters for multi-channel EEG that lead to signals which discriminate optimally between two conditions. We demonstrate the effectiveness of this method by classifying single-trial EEGs, recorded during preparation for movements of left or right index finger or right foot. Best classification rates for 3 subjects were 94%, 90% and 84%, respectively. The filters are estimated from a set of multichannel EEG data by the method of Common Spatial Patterns, and reflect the selective activation of cortical areas. By construction, we obtain an automatic weighting of electrodes according to their importance for the classification task. Computationally, this method is parallel by nature, and demands only the evaluation of scalar products. So it is well suited for on-line data processing. The recognition rates obtained with this relatively simple method are as good or higher than those obtained previously with other methods. The high recognition rates and the method's procedural ...
