EEG Motion Artifacts Removal for Robotic Motion Control Using Brain Computer Interface

With invent of technological platforms the robotic has become essential part of our life. The Brain Computer Interface (BCI) is the heart of human brain based robotic control systems. EEG signal based robotic motion control system have proven there efficiency in the recent times. The brains signals are captured using the electrodes placed on human scalp. The captured signals suffer from the various motion artifacts. This paper is primarily focused to removal of the motion artifacts from the EEG signals captured for robotic motion and direction control systems. Paper first describes the utility of the BCI system in robotics. Paper compares the performance of various artifact removal algorithms as ICA, EEMD-CCA, and EEMD-CCA-DWT. The various results of Intrinsic Mode Functions (IMF`s) decomposed from these methods are evaluated and compared for the artifact removal application in Robotics. It is found based on quantitative analysis that CCA based methods are faster than other and are efficient too.