Artifacts Removal in EEG Data
Suyash Bajpai, Hemant Kumar Moolchandani, Mridu Sahu, Samrudhi Mohdiwale · SSRN Electronic Journal · 2018
Every real time signal composed of original signal affected by some environmental factors called artifact. The paper incorporates the artifact in the EEG signal. Artifacts in electroencephalography (EEG) are the signal that are not desired and which may induce changes in the frequency and affect the signal. The best way of working with electroencephalography (EEG) signal is to completely avoid the happening of artifacts when recording starts, the electroencephalography signal often is contaminated by different physiological factors other than internal activity, which are of no interest. For instance, ocular movements, cardiac activity, muscular activity and eye blinks are among the most common types of artifacts. In this paper Ocular artefact is considered for evaluation of filtering methods to remove artifact among various type of artifacts present in EEG signal. Adaptive filters adjust itself as the data changes continuously with time hence best suited for nonstationary signal like EEG. In this paper LMS, RLS techniques of adaptive filtering is applied to evaluate the performance of the method for successfully removal of noise in EEG signal.