Statistical Based Feature Selection Approaches for Motor Imagery EEG Signals in Brain Computer Interface

Abstract

The fabulous growth of Intelligence Computing leads to the progress of Human Computer Interaction. The Human Nervous System and behavior patterns interactive with intelligence based machine. Now a days, Lot of researchers are concentrate in this area. In this paper, we analysis the existing methodology and also find the feature selection methods. We propose a new Feature Selection method such as Z-Test, Population Variance, Population Standard Deviation, Sample Variance and Sample Standard Deviation. It will outperformed better than some of the benchmark feature selection Methodology.