Abstract

Info

Title:: Electrooculogram artifacts removal based on variational mode decomposition

Author(s):: ZHAO Li; CUI Lijie; School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China

Keywords:: Keywords: electrooculogram artifact; electroencephalogram signal; variational mode decomposition; modal component

Abstract:: Abstract: Electroencephalogram (EEG) signals can reflect the state of human brain activity and accurately transmit the information in the brain to the outside, which is of great significance to brain science research. In practice, the acquisition of EEG signals is accompanied by some noises, and the presence of electrooculogram (EOG) artifacts will seriously interfere with EEG signals. Therefore, a variational mode decomposition-based method for removing EOG artifacts is proposed. The acquired EEG signals are decomposed into K modal components by variational mode decomposition. According to the frequency characteristics of EOG artifacts, the modal components corresponding to EOG artifacts are selected out, and the remaining modal components are reconstructed after removing the artifacts. The results show that by processing the experimental data, variational mode decomposition can be used to effectively remove EOG artifacts and maintain the characteristics of EEG signals.