@article{Thottempudi_Kumar_Deevi_2024, title={EEG Artifact Removal Strategies for BCI Applications: A Survey}, volume={18}, url={https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/eeg-artifact-removal-strategies-for-bci-applications-a-survey/}, DOI={10.30486/mjee.2024.1986441.1136}, abstractNote={This paper aims to provide a comprehensive examination of the Brain-Computer Interface and the more scientific discoveries that have resulted from it. The ultimate goal of this review is to provide extensive research in BCI systems while also focusing on artifact removal techniques or methods that have recently been used in BCI and important aspects of BCIs. In its pre-processing, artifact removal methodologies were critical. Furthermore, the review emphasizes the applicability, practical challenges, and outcomes associated with BCI advancements. This has the potential to accelerate future progress in this field. This critical evaluation examines the current state of BCI technology as well as recent advancements. It also identifies various BCI technology application areas. This detailed study shows that, while progress is being made, significant challenges remain for user advancement A comparison of EEG artifact removal methods in BCI was done, and their usefulness in real-world EEG-BCI applications was talked about. Some directions and suggestions for future research in this area were also made based on the results of the review and the existing artifact removal methods.  }, number={1}, journal={Majlesi Journal of Electrical Engineering}, publisher={OICC Press}, author={Thottempudi, Pardhu and Kumar, Vijay and Deevi, Nagesh}, year={2024}, month={Apr.}, keywords={BCI, EOG, EMG, EEG, eCG} }