Approximate Entropy in Electromyography during Muscle Fatigue

Authors: Payam Wali M. Hussein¹ & Kadir Tufan² & Serkan Dursun^3
1Computer Engineering Department, Faculty of Engineering, Ishik University, Erbil, Iraq
²Faculty of Computer Science and IT, Tirana, Albania
³Computer Science Department at University of Houston, Houston, TX, USA

Abstract:  Muscle fatigue (MF) is a phenomenon that involves the decline of one’s ability to perform physical action. The early detection of MF is important in the field of ergonomics, sports, occupational work, and human-computer interaction, as MF affects performance and may cause injury. Since MF is not a quantitative value, existing researches in this field are mostly based on different measurable parameters. Electromyography is among the most commonly used signals in analysing MF. The main purpose of this paper is to analyse MF during isometric contractions. For this purpose Discrete Wavelet Transform (DWT) is used to divide each signal to get sub-band frequencies. Approximate Entropy (ApEn) is applied to each sub-band. In the next step, each band is segmented into three sections. Finally, a comparison between the first segment and last segment is performed to evaluate MF.

Keywords: Muscle Fatigue, Electromyography, Discrete Wavelet Transform, Approximate Entropy
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doi: 10.23918/eajse.v4i4p28

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