A Comparative Investigation of Mode Mixing in EEG Decomposition Using EMD, EEMD and M-EMD

Raymond Ho, Kevin Hung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)

Abstract

This paper presents and discusses the empirical mode decomposition method (EMD), its mode mixing problem and the primary causes of it. The ensemble EMD (EEMD) and masking EMD (M-EMD) methods are discussed as solutions for the mode mixing problem. Both improved methods were applied to process an EEG signal and the results were compared. The M-EMD provided the best result making good separation of the EEG signal into delta, theta, alpha, and beta band signals.

Original languageEnglish
Title of host publicationISCAIE 2020 - IEEE 10th Symposium on Computer Applications and Industrial Electronics
Pages203-210
Number of pages8
ISBN (Electronic)9781728150338
DOIs
Publication statusPublished - Apr 2020
Event10th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2020 - Virtual, Malaysia
Duration: 18 Apr 202019 Apr 2020

Publication series

NameISCAIE 2020 - IEEE 10th Symposium on Computer Applications and Industrial Electronics

Conference

Conference10th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2020
Country/TerritoryMalaysia
CityVirtual
Period18/04/2019/04/20

Keywords

  • EEG
  • EEMD
  • EMD
  • M-EMD
  • empirical mode decomposition
  • masking signal
  • mode mixing

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