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Differentiating muscle fatigue and nonfatigue conditions using surface emg signals and zhao-atlas-marks based time-frequency disribution
Published in International Society of Automation (ISA)
Pages: 117 - 123
Muscle fatigue is a neuromuscular condition where muscles fail to generate the required force. It occurs in normal as well as abnormal subjects. The analysis of muscle fatigue plays a significant role in the field of clinical studies, myo-electric control, ergonomics and sports biomechanics. In this work, an attempt has been made to differentiate the sEMG signals under muscle non-fatigue and fatigue conditions using Zhao-Atlas-Marks (ZAM) based time frequency distribution. For this purpose, sEMG signals are recorded from fifty healthy volunteers during isometric contractions under well defined protocol. The acquired signals are preprocessed and subjected to ZAM based time-frequency analysis. The time-frequency based features such as instantaneous median frequency (IMDF) and instantaneous mean frequency (IMNF) are extracted from the time-frequency spectrum. The results show that IMDF and IMNF are distinct for muscle non-fatigue and fatigue conditions. Further, more number of frequency components are observed in the time-frequency spectrum of signals recorded in nonfatigue conditions. The t-test performed on these features has shown significant difference (p<0.01) in between non-fatigue and fatigue conditions. Thus the study seems to be useful for the analysis of various neuromuscular conditions.
About the journal
Journal52nd Annual Rocky Mountain Bioengineering Symposium and 52nd International ISA Biomedical Sciences Instrumentation Symposium 2015
PublisherInternational Society of Automation (ISA)
Open AccessNo
Concepts (8)
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    Surface emg
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