A comparison of ICA algorithms in surface EMG signal processing

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15 Citations (Scopus)

Abstract

Recent research has resulted in development of number of different Independent Component Analysis (ICA) technique. While there are some researchers who have compared their techniques with the existing methods for audio examples, there is no comparison of performance between ICA algorithms for biosignal applications. With ICA being the feasible method for source separation and decomposition of biosignals, it is important to compare the different techniques and determine the most suitable method for the applications. This paper presents the performance of five ICA algorithms (SOBI, TDSEP, FastICA, JADE and Infomax) for decomposition of surface electromyogram (sEMG) to identify subtle wrist actions.

Original languageEnglish
Pages (from-to)363-374
Number of pages12
JournalInternational Journal of Biomedical Engineering and Technology
Volume6
Issue number4
DOIs
Publication statusPublished - Aug 2011
Externally publishedYes

Keywords

  • Blind source separation
  • BSS
  • ICA
  • Independent component analysis
  • MES
  • Myoelectric signal
  • sEMG
  • Source separation
  • Surface electromyogram

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