An improved ensemble empirical mode decomposition and Hilbert transform for fatigue evaluation of dynamic EMG signal

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• 作者：Q. Wu^a ; ^{wuqi7812@sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; C.F. Wei^b ; Z.X. Cai^a ; L. Ding^a ; R. Law^c
• 关键词：Mean instantaneous frequency ; Ensemble empirical mode decompositions ; Intrinsic mode function (IMF) ; Muscular fatigue ; Hilbert spectrum
• 刊名：Optik - International Journal for Light and Electron Optics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：126
• 期：24
• 页码：5903-5908
• 全文大小：1986 K

文摘

A hybrid dynamic fatigue diagnosis method based on a variation of ensemble empirical mode decomposition (VEEMD) and mean instantaneous frequency (MIF) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. In the method here proposed, a particular noise is added at each stage of the decomposition and a unique residue is computed to obtain each mode. Our results showed that MIF estimated from each instantaneous frequency of intrinsic mode functions (IMFs) decomposed by the proposed VEEMD is a relevant feature to muscular fatigue diagnosis. We found that MIF reduces when the force level of the muscle contraction increases.