Research Area:  Machine Learning

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.

Keywords:  

Author(s) Name:  Xiao Jiang ,Gui-Bin Bian and Zean Tian

Publisher name:  MDPI

DOI:  10.3390/s19050987

Volume Information:  2019, Volume 19, Issue 5

Paper Link:   https://www.mdpi.com/1424-8220/19/5/987