A Review on Detection and Correction of Artifacts from EEG Data
Sagar Motdhare1, Garima Mathur2
1Dr. Sagar Motdhare, Assistant Professor, Indian Institute of Information Technology, Nagpur (Maharashtra), India.
2Dr. Garima Mathur, Professor, Poornima University, Jaipur (Rajasthan), India.
Manuscript received on 24 February 2023 | Revised Manuscript received on 28 February 2023 | Manuscript Accepted on 15 March 2023 | Manuscript published on 30 March 2023 | PP: 74-79 | Volume-11 Issue-6, March 2023 | Retrieval Number: 100.1/ijrte.F74970311623 | DOI: 10.35940/ijrte.F7497.0311623
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Electroencephalography (EEG), Artifact, Artifact Removal, Artifact Correction
Scope of the Article: Signal Control System & Processing