A comparison of ICA algorithms in surface EMG signal processing

Ganesh R. Naik

doi:10.1504/IJBET.2011.041774

A comparison of ICA algorithms in surface EMG signal processing

Ganesh R. Naik

Research output: Contribution to journal › Article › peer-review

16 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 language	English
Pages (from-to)	363-374
Number of pages	12
Journal	International Journal of Biomedical Engineering and Technology
Volume	6
Issue number	4
DOIs	https://doi.org/10.1504/IJBET.2011.041774
Publication status	Published - Aug 2011
Externally published	Yes

Keywords

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

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A comparison of ICA algorithms in surface EMG signal processing

Abstract

Keywords

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