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.
