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
