1. Muscle fatigue analysis in biceps brachii surface electromyography signals using synchrosqueezed Morlet wavelet and singular value decomposition
- Author
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Lakshmi M. Hari, G. Venugopal, and S. Ramakrishnan
- Subjects
Electrical activity in neurophysiological processes ,Signal processing and detection ,Bioelectric signals ,Digital signal processing ,Integral transforms ,Other topics in statistics ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Abstract Muscle fatigue during isometric contraction of biceps brachii is analysed using synchrosqueezed continuous wavelet transform with Morlet wavelet and singular value decomposition (SVD) features. The recorded surface electromyography signals are decomposed to time frequency matrix using Morlet wavelet and the characteristics are extracted using singular value features such as maximum singular value and zero crossing frequency. The percentage difference in feature values for each segment with the progression of fatigue is calculated. Results show that the recorded signals are complex, non‐stationary, multicomponent, and random in nature. Maximum singular value represents the non‐stationarity of a signal, with an increasing trend towards the fatigue condition. Zero crossing frequency represents the complexity or randomness in the signals and it decreases with the progression of fatigue. It is found that both the features are statistically significant with p
- Published
- 2021
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