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
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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 ratio), however, limits EEG applicability. A variety of artefacts cause EEG noise, and numerous strategies have already been developed to identify and eliminate these inconsistencies. Various methods differ from merely identifying and discarding artefact-ridden segments to isolating the noise content of the EEG signal. With an emphasis on the previous half decade, we discuss a range of contemporary and traditional strategies for EEG data artefact recognition and removal. We assess the merits and drawbacks of the approaches before proposing potential prospects for the area.
Keywords: Electroencephalography (EEG), Artifact, Artifact Removal, Artifact Correction
Scope of the Article: Signal Control System & Processing