Analysis of Visual Colour Perception using EEG Spectral Features

Electroencephalography signals are the electrophysiological measures of brain function and used to develop a brain machine interface (BMI). BMI system is used to provide a communication and control technology for the differentially enabled people having neuromuscular disorders. In this paper, a simple BMI system based on EEG signal emanated while visualizing of different colours has been proposed. The proposed BMI uses the color visualization tasks (CVT) and aims to provide a communication link using brain activated control signal. For each EEG signal, using spectral analysis, alpha, beta and gamma band frequency statistical spectral features such as spectral energy, mean spectral energy and standard deviation spectral energy are obtained. The extracted features are then associated to different control signals and a probabilistic neural network model has been developed to observe the classification accuracy of this three features.