Title: Generalised Warblet transform-based analysis of biceps brachii muscles contraction using surface electromyography signals

Authors: Diptasree Maitra Ghosh; Ramakrishnan Swaminathan

Addresses: Non-Invasive Imaging and Diagnostics Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036, Tamilnadu, India ' Non-Invasive Imaging and Diagnostics Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036, Tamilnadu, India

Abstract: In this work, an attempt has been made to utilise the time-frequency spectrum obtained using generalised Warblet transform (GWT) for fatigue analysis. Signals are acquired from the biceps brachii muscles of 20 healthy volunteers during isometric contractions. The first and last 500 ms lengths of a signal are assumed as non-fatigue and fatigue zones respectively. Further, the signals from these zones are subjected to GWT for the computation of time-frequency spectrum. Features such as instantaneous mean frequency (IMNF), instantaneous median frequency (IMDF), instantaneous spectral entropy (ISPEn), and instantaneous spectral skewness (ISSkw) are estimated. The results show that the IMNF, IMDF and ISPEn increased by 24%, 34% and 36% respectively in non-fatigue condition. In contrast, 22% higher ISSkw is observed for fatigue condition. The statistical analysis indicates that the features are significant with p < 0.001. It appears that the current method is useful in analysing muscle fatigue disorders using sEMG signals.

Keywords: surface electromyography; sEMG; biceps brachii; muscle fatigue; generalised Warblet transform; GWT.

DOI: 10.1504/IJBET.2020.112419

International Journal of Biomedical Engineering and Technology, 2020 Vol.34 No.4, pp.305 - 318

Received: 05 Jul 2017
Accepted: 20 Nov 2017
Published online: 15 Jan 2021 *

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