A review on feature extraction & classification techniques for biosignal processing (Part II: Electroencephalography)

Abstract

This paper concentrates on Electroencephalography (EEG) signal processing with the emphasis on seizure detection. Manually by reviewing EEG recordings for detection of electrographical patterns is a time consuming business. Therefore, the ability to automate the classification of interesting electrographical patterns is a good supplement to the wide range of detection algorithms currently used for EEG analysis. Multi channel recordings of the electrographically patterns from neural currents in the brain would generate a large amounts of data. Suitable feature extraction methods are useful to facilitate the representation and interpretation of the data. © 2008 Springer-Verlag.