Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review

Ganesh R. Naik, Sridhar Arjunan, Dinesh Kumar

Research output: Contribution to journalReview articlepeer-review

29 Citations (Scopus)

Abstract

The surface electromyography (sEMG) signal separation and decphompositions has always been an interesting research topic in the field of rehabilitation and medical research. Subtle myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of myoelectric signals to control human-assisting robots or rehabilitation devices. This paper reviews recent research and development in independent component analysis and Fractal dimensional analysis for sEMG pattern recognition, and presents state-of-the-art achievements in terms of their type, structure, and potential application. Directions for future research are also briefly outlined.

Original languageEnglish
Pages (from-to)179-193
Number of pages15
JournalAustralasian Physical and Engineering Sciences in Medicine
Volume34
Issue number2
DOIs
Publication statusPublished - Jun 2011
Externally publishedYes

Keywords

  • Blind source separation
  • Fractal dimension
  • Fractal theory
  • Independent component analysis
  • Surface electromyography

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