Clustering of Spectral Patterns Based on EMD Components of EEG Channels with Applications to Neurophysiological Signals Separation

Abstract

The notion of information separation in electrophysiological recordings is discussed. Whereas this problem is not entirely new, a novel approach to separate muscular interference from brain electrical activity observed in form of EEG is presented. The EEG carries brain activity in form of neurophysiological components which are usually embedded in much higher in power electrical muscle activity components (EMG, EOG, etc.). A novel multichannel EEG analysis approach is proposed in order to discover representative components related to muscular activity which are not related to ongoing brain activity but carry common patterns resulting from non-brain related sources. The proposed adaptive decomposition approach is also able to separate signals occupying same frequency bands what is usually not possible with contemporary methods. © 2009 Springer Berlin Heidelberg.