-3bf97310184a13a8c1e60b 20230303051655114 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 03 30 2023 11 6 Assistant Professor, Indian Institute of Information Technology, Nagpur (Maharashtra), India. Dr. Sagar Motdhare https://orcid.org/0009-0007-4806-4694 Dr. Garima Mathur https://orcid.org/0000-0002-9547-7412 Professor, Poornima University, Jaipur (Rajasthan), India. Electroencephalography (EEG) offers a wide range of uses in a variety of industries. Low SNR (signal to noise ratios), nevertheless, limit EEG applicability. EEG noise is caused by a variety of artifacts and numerous strategies have already been developed to identify and eliminate these inconsistencies. Various methods differ from merely identifying and discarding artifact ridden segments to isolating the EEG signal's noise content. With an emphasis on the previous half decade, we discuss a range of contemporary and traditional strategies for EEG data artifact recognition and removal. We assess the approaches' merits and drawbacks before proposing potential prospects for the area. 03 30 2023 74 79 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true No, I did not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. Not relevant. The present article has been submitted having equal contribution from both the authors. 10.35940/ijrte.F7497.0311623 https://www.ijrte.org/portfolio-item/F74970311623/