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Removal of Artifacts from EEG Signals: A Review

Sensors · 2019 · Vol. 19(5) · pp. 987–987
Jiang XiaoGui‐Bin BianZean Tian

Abstract

Electroencephalogram (EEG) plays an important role in identifying brain activity and behavior. However, the recorded electrical activity always be contaminated with artifacts and then affect the analysis of EEG signal. Hence, it is essential to develop methods to effectively detect and extract the clean EEG data during encephalogram recordings. Several methods have been proposed to remove artifacts, but the research on artifact removal continues to be an open problem. This paper tends to review the current artifact removal of various contaminations. We first discuss the characteristics of EEG data and the types of different artifacts. Then, a general overview of the state-of-the-art methods and their detail analysis are presented. Lastly, a comparative analysis is provided for choosing a suitable methods according to particular application.

EEG and Brain-Computer InterfacesBlind Source Separation TechniquesNeural dynamics and brain functionElectroencephalographyArtifact (error)Computer scienceArtificial intelligenceSIGNAL (programming language)Pattern recognition (psychology)NeurosciencePsychology

MeSH terms

AlgorithmsBrainElectroencephalographyHumansSignal Processing, Computer-AssistedArtifacts

Funding

  • National Natural Science Foundation of China
  • Chinese Academy of Sciences
  • Youth Innovation Promotion Association of the Chinese Academy of Sciences
  • National Key Research and Development Program of China
  • Youth Innovation Promotion Association
Citations
786
FWCI
44.07
field-weighted impact
References
124
Percentile
100%
vs. same field & year
Citations per year
References
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