Taxonomy on EEG Artifacts Removal Methods, Issues, and Healthcare Applications

Electroencephalogram (EEG) signals are progressively growing data widely known as biomedical big data, which is applied in and healthcare research. The measurement processing of EEG signal result the probability contamination through artifacts can obstruct important features information quality existing signal. To diagnose human neurological diseases like epilepsy, tumors, problems associated with trauma, these must be properly pruned assuring that there no loss main attributes signals. In this paper, latest updated terms key arranged tabulated extensively by considering 60 published technical research papers based on artifact removal method. Moreover, paper a review vision about works area to summarizes challenges, gaps, opportunities improve more precisely.