Classification of Motion and Speech Based Brain EEG Signals using Bilayer Bayesian Classifier with Association Rule (BBC-AR)

Abstract

This paper aims at developing Brain Computer Interface (BCI) system which uses EEG signals. In this, user thinking is extracted from brain activity of healthy person. Features are extracted from pre-processed signals and classify them into their respective alpha, beta, delta and gamma signal classes. Main intension of this work is to provide better communication interface to a person using brain signals. This is helpful to patients who have severe motor impairments and also unable to speak. This system can be used as an alternative form of communication by using mental activity.