ELECTROMYOGRAPHY SIGNAL ON BICEPS MUSCLE IN TIME DOMAIN ANALYSIS

Authors

  • Abu Bakar Yahya Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Wan Mohd Bukhari Wan Daud Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Chong Shin Horng Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Rubita Sudirman Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

DOI:

https://doi.org/10.15282/jmes.7.2014.17.0115

Keywords:

Electromyography (EMG); time domain; force estimation; non-invasive.

Abstract

Features extraction is important for electromyography (EMG) signal analysis. The paper’s objective is to evaluate the features extraction of the EMG signal. The experimental set-up for EMG signal acquisition followed the procedures recommended by Europe’s Surface Electromyography for Non-invasive Assessment of Muscle (SENIAM) project. The EMG signal’s data were analysed in the time domain to get the features. Four features were considered based on the analysis, which are IEMG, MAV, VAR and RMS. The average muscle force condition can be estimated by correlation between the EMG voltage amplitude with linear estimation with the full-wave rectification method. The R-squared value determined the correlation between the EMG voltage amplitude with the loads. IEMG was chosen as the reference feature for estimation of the muscle’s force due to its R-squared value equal to 0.997. By referring to the IEMG, the linear equation obtained from the correlation was used for estimation of the muscle’s force. These findings can be integrated to design a muscle force model based on the biceps muscle.

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Published

2014-12-31

How to Cite

[1]
Abu Bakar Yahya, Wan Mohd Bukhari Wan Daud, Chong Shin Horng, and Rubita Sudirman, “ELECTROMYOGRAPHY SIGNAL ON BICEPS MUSCLE IN TIME DOMAIN ANALYSIS”, J. Mech. Eng. Sci., vol. 7, no. 1, pp. 1179–1188, Dec. 2014.

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