Muscle Fatigue Analysis With Optimized Complementary Ensemble Empirical Mode Decomposition and Multi-Scale Envelope Spectral Entropy

Muscle Fatigue Analysis With Optimized Complementary Ensemble Empirical Mode Decomposition and Multi-Scale Envelope Spectral Entropy

The preprocessing of surface electromyography (sEMG) signals with complementary ensemble empirical mode decomposition (CEEMD) improves frequency identification precision and temporal resolution, and lays a good foundation for feature extraction. However, a mode-mixing problem often occurs when the C...

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Bibliographic Details
Main Authors: Juan Zhao, Jinhua She, Edwardo F. Fukushima, Dianhong Wang, Min Wu, Katherine Pan
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Neurorobotics
Subjects:
surface electromyography
complementary ensemble empirical mode decomposition
least-squares mutual information
multi-scale envelope spectral entropy
muscle fatigue
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2020.566172/full

Internet

https://www.frontiersin.org/articles/10.3389/fnbot.2020.566172/full

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