2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES) 2014
DOI: 10.1109/iecbes.2014.7047649
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Determination of muscle fatigue in SEMG signal using empirical mode decomposition

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Cited by 6 publications
(3 citation statements)
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“…Due to its advantages, EMD has been successfully used in the analysis of non-linear and non-stationary biomedical signals including EMG [31,33,34]. These resultant IMFs can also be considered as different scales of the original signal for multi-scale analysis [25].…”
Section: Empirical Mode Decompositionmentioning
confidence: 99%
“…Due to its advantages, EMD has been successfully used in the analysis of non-linear and non-stationary biomedical signals including EMG [31,33,34]. These resultant IMFs can also be considered as different scales of the original signal for multi-scale analysis [25].…”
Section: Empirical Mode Decompositionmentioning
confidence: 99%
“…The results of the above studies indicate that the way to induce muscle fatigue may count, and it is better to select an endurance task similar to the test motion. The conclusion seems to be the common practice for the sEMG-related muscle fatigue studies, such as the studies that induced fatigue by running on a treadmill [29,30]/overground [31], walking [32], and cycling [33][34][35]. In this paper, we study the effect of muscle fatigue in walking, so long walking time on a treadmill was selected as the method to induce fatigue.…”
Section: Related Workmentioning
confidence: 99%
“…Fatigue in the muscles occurs when the cell lacks the energy to continue its activation [1]. Muscle fatigue can be defined as the inability to provide a certain amount of force required to complete a task [2]. Fatigue can also occur due to Parkinson's disease, endocrine disturbances, carcinoma, malnutrition, and immobilization [3].…”
Section: Introductionmentioning
confidence: 99%