EEG classification using neural networks and independent component analysis

Abstract

In this paper we used Independent component analysis model of electroencephalography (EEG) signals for preprocessing and then Hidden Markov Modeling (HMM) analysis for feature extraction from electroencephalography signal which this features are useful in Brain Computer Interface (BCI) application. Then we used Neural Networks for recognition of some diseases like epileptic seizure, Cerebral Palsy, etc. © 2008 Springer-Verlag.