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

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.

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Naik, G.R., Arjunan, S. & Kumar, D. Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review. Australas Phys Eng Sci Med 34, 179–193 (2011). https://doi.org/10.1007/s13246-011-0066-4

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Keywords

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