VMD-based denoising methods for surface electromyography signals

Abstract

Objective. Since noise is inevitably introduced during the measurement process of surface electromyographic (sEMG) signals, two novel methods for denoising based on the variational mode decomposition (VMD) method were proposed in this work. Prior to this study, there has been no literature relating to how VMD is applied to sEMG denoising. Approach. The first proposed method uses the VMD method to decompose the signal into multiple variational mode functions (VMFs), each of which has its own center frequency and narrow band, and then the wavelet soft thresholding (WST) method is applied to each VMF. This method is termed the VMD-WST. The second proposed method uses the VMD method to decompose the signal into multiple VMFs, and then the soft interval thresholding (SIT) method is performed on each VMF, which is abbreviated as VMD-SIT. Ten healthy subjects and ten stroke patients participated in the experiment, and the sEMG signals of bicep brachii were measured and analyzed. In this paper, three methods are used for quantitative evaluation of the filtering performance: the signal-to-noise ratio (SNR), root mean square error and R-squared value. The proposed two methods (VMD-WST, VMD-SIT) are compared with the empirical mode decomposition (EMD) method and the wavelet method. Main results. The experimental results showed that the VMD-WST and VMD-SIT methods can effectively filter the noise effect, and the denoising effects were better than the EMD method and the wavelet method. The VMD-SIT method has the best performance. Significance. This study provides a new means of eliminating the noise of sEMG signals based on the VMD method, and it can be applied in the fields of limb movement classification, disease diagnosis, human-machine interaction and so on.

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals : A Review

“…Although EMD has many advantages, it also has disadvantages, including its sensitivity to noise and the fact that the frequency bands of the components may overlap each other [106]. To address issues of the EMD method, [107] have developed a new decomposition method called variational mode decomposition (VMD).…”

“…Since the VMFs and their respective center frequency can be obtained from the model, the signal is reconstructed using the inverse Fourier transform. [106] compared their VMD-based methods to both the EMD-based and wavelet-based methods in terms of SNR and RMSE and demonstrated that both proposed methods performed better at denoising. Moreover, they showed that the VMD-SIT version was more effective than the VMD-WST in addition to producing a smoother and continuous signal.…”

Estimated ECG Subtraction method for removing ECG artifacts in esophageal recordings of diaphragm EMG

“…Wavelet-based adaptive filters have been increasingly proposed for removal of ECG noise from EMG recordings of various muscles, including the diaphragm, and with and without the use of extra channels for ECG recording [15][16][17]20,29,30]. This method performs well particularly when the ECG to EMG amplitude is high.…”

Degradation Trend Prediction of Pumped Storage Unit Based on MIC-LGBM and VMD-GRU Combined Model

“…It has a sound theoretical foundation and is suitable for dealing with nonlinear and non-stationary series [38]. It decomposes the complex series into a series of approximately orthogonal simple modes and is popular in the fields of signal denoising [39], runoff forecasting [40], wind speed forecasting [41], etc. Thus, the complex PDI sequences are decomposed into simpler modes by VMD before being fed into GRU to improve the accuracy of prediction.…”