Feature Extraction of EEG Signal using Wavelet Transform

Abstract

EEG signal analysis is such an important thing for disease analysis and brain-computer analysis. Using Electroencephalography (EEG) monitoring the state of the user's brain functioning and treatment for any psychological disorder, where the difficulty in learning and comprehending the arithmetic exists and it could allow for analysis disease the user to train the corresponding brain. In this paper, we proposed a method for EEG signal processing includes signal de-noising, segmentation of de-noise signal using PCM and signal segments feature extraction done using wavelet as an alternative to the commonly used discrete Fourier transform (DFT).These feature classified using support vector machine classifier, Using the Matlab software proposed method accompanied.