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- W2374780706 abstract "Electromyography (EMG) finds more and more application areas, such as the workload evaluation and the robotic control. The key is the feature analysis and extraction. Various methods for the analysis of the EMG can be grouped into the linear methods and the nonlinear methods. The methods based the entropy theory and the complexity are among the nonlinear methods. The entropy methods include various entropy calculation algorithms, and the Renyi Entropy and Wavelet Entropy are the typical methods. In this paper the EMG are obtained from two volunteers while they are doing the push-up exercise, and the measures of the Renyi entropy, Wavelet entropy and LZC complexity are calculated. In the algorithm, the segments of the EMG are made to achieve better analysis results. The complexity of the EMG is reflected by these measures, as is validated by analysis. The value of the wavelet entropy implies the power of the EMG, and a higher power is obtained for the muscle fiber concentrated discharge, and so the complexity is decreased. The results from the Renyi entropy and LZC are the same. With these methods, the EMG is divided into several segments based on the muscle fatigue and EMG complexity. The results show that with these methods the EMG is a promising research field in the future, and these measures can also be applied to muscle fatigue." @default.
- W2374780706 created "2016-06-24" @default.
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- W2374780706 date "2009-01-01" @default.
- W2374780706 modified "2023-09-28" @default.
- W2374780706 title "Electromyography Analysis Based on the Entropy Theory and Complexity Measures" @default.
- W2374780706 hasPublicationYear "2009" @default.
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