Literature DB >> 21416388

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

Ganesh R Naik1, Sridhar Arjunan, Dinesh Kumar.   

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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Year:  2011        PMID: 21416388     DOI: 10.1007/s13246-011-0066-4

Source DB:  PubMed          Journal:  Australas Phys Eng Sci Med        ISSN: 0158-9938            Impact factor:   1.430


  3 in total

1.  Classification of surface electromyographic signals by means of multifractal singularity spectrum.

Authors:  Gang Wang; Doutian Ren
Journal:  Med Biol Eng Comput       Date:  2012-11-07       Impact factor: 2.602

2.  Systems biology, emergence and antireductionism.

Authors:  Srdjan Kesić
Journal:  Saudi J Biol Sci       Date:  2015-06-27       Impact factor: 4.219

3.  Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI.

Authors:  Galina V Portnova; Alina Tetereva; Vladislav Balaev; Mikhail Atanov; Lyudmila Skiteva; Vadim Ushakov; Alexey Ivanitsky; Olga Martynova
Journal:  Front Hum Neurosci       Date:  2018-01-09       Impact factor: 3.169

  3 in total

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