Speech synthesizer And Feature Extraction Using DWT With classification By Euclidian Distance and neural network of EEG signals

The goal of proposed work is the development of an electroencephalogram (EEG) based BCI system. The overview of this work is, the user thought is extracted from the brain activity of a healthy person. Pre-processing is performed using filters and wavelet transforms to extract the features and classify them to their respective class. The intention of this work is to enhance human interaction with computers, providing a communication channel between human brain and computer. Patients who suffer from severe motor impairments and are unable to speak may use such an EEG based BCI system as an alternative form of communication by mental activity. Keywords— Brain Computer Interface (BCI), Electroencephalogram (EEG), European data format (EDF), wavelet transform (DWT), Euclidian distance, neural network.