articleIEEE Signal Processing MagazineJan 1, 2008Closed access

Optimizing Spatial filters for Robust EEG Single-Trial Analysis

BBBenjamin BlankertzRTRyota TomiokaSLSteven LemmMKMotoaki KawanabeKMKlaus‐Robert Müller

Technische Universität Berlin · University of Florida · +2 more institutions

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Abstract

Due to the volume conduction multichannel electroencephalogram (EEG) recordings give a rather blurred image of brain activity. Therefore spatial filters are extremely useful in single-trial analysis in order to improve the signal-to-noise ratio. There are powerful methods from machine learning and signal processing that permit the optimization of spatio-temporal filters for each subject in a data dependent fashion beyond the fixed filters based on the sensor geometry, e.g., Laplacians. Here we elucidate the theoretical background of the common spatial pattern (CSP) algorithm, a popular method in brain-computer interface (BCD research. Apart from reviewing several variants of the basic algorithm, we reveal…

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Topics
Keywords
  • Computer science
  • Preprocessor
  • Brain–computer interface
  • Signal processing
  • Noise (video)
  • Artificial intelligence
  • Electroencephalography
  • SIGNAL (programming language)
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