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A Review of EEG Artifact Removal Methods for Brain-Computer Interface Applications.
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Khan, Safdar Sardar ; Sudan, Jaskirat Singh1; Pathak, Anuj1; Pandit, Rakesh1; Rane, Pinky1; Kumawat, Ashish Kumar1
- Source:
Ingénierie des Systèmes d'Information. Feb2024, Vol. 29 Issue 1, p247-252. 6p.- Subject Terms:
- Source:
- Additional Information
- Abstract: The use of electroencephalogram signals in brain-computer interface Applications is widely used in Neuroscience. EEG records electrical activity in the brain but can also capture unwanted electrical activities called artifacts. They can originate from environmental noise, experimental errors, and physiological sources. To address these challenges, EEG Data Analysis involves different data preprocessing and statistical techniques. This systematic review conducted on more than 25 papers, aims to provide an overview of various types of artifacts such as extrinsic and intrinsic artifacts and methods available for removing those artifacts from EEG signals. Each approach presents unique advantages and challenges, contributing to the enhancement of the quality and reliability of EEG data for accurate analysis and interpretation. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Ingénierie des Systèmes d'Information is the property of International Information & Engineering Technology Association (IIETA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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