Performance analysis of different techniques for Brain Computer Interfacing

Abstract

Recent works on different types of Brain Computer Interface (BCI) and their performance analysis have provided some remarkable features for applications. The aim of this work is to compare the accuracies of different types of BCI to find out the suitable techniques. The study shows that each technique performance depends on the type of BCI. A batter performance of the BCI systems is supported by the artificial neural network.