Wavelet analysis of electrical signals from brain: The electroencephalogram

Abstract

The Electroencephalogram (EEG) is a measure of neural activity and is used to study cognitive processes, physiology, and complex brain dynamics. The analysis and processing of EEG data and to extract information from it, is a difficult task. The EEG signals are non-stationary signals. So, only transformation of these signals from time to frequency domain does not serve the purpose, it is required to know the time domain information too associated with the frequency domain information. Wavelet transform is one such tool being used recently for such analysis of non-stationary signals like EEG. In this paper, wavelet packet decomposition of EEG signals is presented. Feature extraction from EEG signal is also introduced in this paper.