Surface electromyography signal processing and classification techniques

Rubana H. Chowdhury, Md. Mamun Ibne Reaz, Mohd Alauddin Bin Mohd Ali, Ahmad Ashrif A Bakar, Kalaivani Chell, T. G. Chang

Research output: Contribution to journalArticle

265 Citations (Scopus)

Abstract

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

Original languageEnglish
Pages (from-to)12431-12466
Number of pages36
JournalSensors (Switzerland)
Volume13
Issue number9
DOIs
Publication statusPublished - 17 Sep 2013

Fingerprint

electromyography
Electromyography
signal processing
Signal processing
Processing
preprocessing
research and development
classifying
Patient rehabilitation
Artifacts
Prostheses and Implants
artifacts
Rehabilitation
recording
Equipment and Supplies
preparation
evaluation
Research

Keywords

  • Artificial neural network
  • Electromyography
  • EMD
  • HOS
  • ICA
  • Noise source
  • Wavelet

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics
  • Analytical Chemistry
  • Biochemistry

Cite this

Surface electromyography signal processing and classification techniques. / Chowdhury, Rubana H.; Ibne Reaz, Md. Mamun; Bin Mohd Ali, Mohd Alauddin; A Bakar, Ahmad Ashrif; Chell, Kalaivani; Chang, T. G.

In: Sensors (Switzerland), Vol. 13, No. 9, 17.09.2013, p. 12431-12466.

Research output: Contribution to journalArticle

Chowdhury, Rubana H. ; Ibne Reaz, Md. Mamun ; Bin Mohd Ali, Mohd Alauddin ; A Bakar, Ahmad Ashrif ; Chell, Kalaivani ; Chang, T. G. / Surface electromyography signal processing and classification techniques. In: Sensors (Switzerland). 2013 ; Vol. 13, No. 9. pp. 12431-12466.
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