An Improved Method for Removing the Artifacts of Electrooculography

Huimin Zhao, Chao Chen, Abdelkader Nasreddine Belkacem, Jiaxin Zhang, Lin Lu, Penghai Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to solve the problem that the removal effect of EEG artifacts is not ideal in EEG preprocessing, PCA-JADE-ARX is used in this paper. Firstly, PCA is used to select the number of components, and then JADE method is used to remove the artifacts. Based on the results of removing the artifacts, ARX model is estimated to find the optimal model and complete the correction of JADE results. Finally, clean and reliable real EEG signals are restored. The relative error, stability and effectiveness of the method are improved, which shows the practical application of the method.

Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Computer Engineering and Networks
EditorsQi Liu, Xiaodong Liu, Bo Chen, Yiming Zhang, Jiansheng Peng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages516-525
Number of pages10
ISBN (Print)9789811665530
DOIs
Publication statusPublished - 2022
Event11th International Conference on Computer Engineering and Networks, CENet2021 - Hechi, China
Duration: Oct 21 2021Oct 25 2021

Publication series

NameLecture Notes in Electrical Engineering
Volume808 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th International Conference on Computer Engineering and Networks, CENet2021
Country/TerritoryChina
CityHechi
Period10/21/2110/25/21

Keywords

  • ARX
  • EEG signal
  • JADE
  • PCA

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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