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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2013 Vol.3(6): 515-519 ISSN: 2010-3697
DOI: 10.7763/IJMO.2013.V3.332

Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle

Wan Mohd Bukhari Wan Daud, Abu Bakar Yahya, Chong Shin Horng, Mohamad Fani Sulaima, and Rubita Sudirman
Abstract—Electromyography (EMG) is widely used in various fields to investigate the muscular activities. Since EMG signals contain a wealth of information about muscle functions, there are many approaches in analyzing the EMG signals. It is important to know the features that can be extracting from the EMG signal. The ideal feature is important for the achievement in EMG analysis. Hence, the objective of this paper is to evaluate the features extraction of time domain from the EMG signal. The experiment was setup according to surface electromyography for noninvasive assessment of muscle (SENIAM). The recorded data was analyzed in time domain to get the features. Based on the analysis, three features have been considered based on statistical features. The features was then been evaluate by getting the percentage error of each feature. The less percentage error determines the ideal feature. The results shows that the extracted features of the EMG signals in time domain can be implement in signal classification. These findings could be integrated to design a signal classification based on the features extraction.

Index Terms—Biceps brachii, electromyography (EMG), features extraction, time domain.

The authors are with the Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Malaysia (e-mail: bukhari@utem.edu.my; abubakar1110@gmail.com; horng@utem.edu.my, rubita@fke.utm.my).

[PDF]

Cite:Wan Mohd Bukhari Wan Daud, Abu Bakar Yahya, Chong Shin Horng, Mohamad Fani Sulaima, and Rubita Sudirman, "Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle," International Journal of Modeling and Optimization vol. 3, no. 6, pp. 515-519, 2013.

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