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Myoelectrical denoising method based on CEEMD (complementary ensemble empirical mode decomposition) and interval thresholds

A threshold and denoising technology, applied in the field of signal denoising, can solve problems such as data deviation, and achieve the effect of reducing influence, improving signal-to-noise ratio, and improving recognition rate

Inactive Publication Date: 2019-04-09
HANGZHOU DIANZI UNIV
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Problems solved by technology

This algorithm can make up for the discontinuity of the wavelet threshold, but as the amount of data increases, it will cause a large deviation in the data

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  • Myoelectrical denoising method based on CEEMD (complementary ensemble empirical mode decomposition) and interval thresholds
  • Myoelectrical denoising method based on CEEMD (complementary ensemble empirical mode decomposition) and interval thresholds
  • Myoelectrical denoising method based on CEEMD (complementary ensemble empirical mode decomposition) and interval thresholds

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Embodiment Construction

[0058] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following the described embodiment.

[0059] Such as figure 1 As shown, this embodiment includes the following steps:

[0060] Step 1, the collected surface EMG signal x(t) will contain noise n(t):

[0061] x(t)=s(t)+δn(t)

[0062] In the formula, s(t) is the SEMG signal without noise, x(t) is the SEMG signal with noise, n(t) is white noise, and δ is the scale factor of the noise.

[0063] Step 2, perform complementary set empirical mode decomposition on the noisy signal x(t) obtained in step 1, the specific steps are as follows:

[0064] ①The noisy signal x(t) is added with a pair of complementary po...

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Abstract

The invention relates to a myoelectrical denoising method based on CEEMD (complementary ensemble empirical mode decomposition) and interval thresholds. The method comprises the steps as follows: decomposing sEMG (surface electromyography) by CEEMD to obtain intrinsic mode function components; then, selecting proper intrinsic mode function components through component correlation analysis, and performing improved interval threshold processing on each selected intrinsic mode function component; finally, performing signal reconstruction by treated intrinsic mode function components and intrinsicmode function components not subjected to improved interval threshold processing to obtain denoised signals. Due to self-adaptability in signal processing, the method is suitable for analysis of nonlinear and non-stationary sEMG, adverse effects caused by mode aliasing can be reduced, besides, useful information in signals is reserved as much as possible, effects of noise are reduced, so that thesignal-to-noise ratio is increased, the recognition rate is increased, and the application of sEMG is wider.

Description

technical field [0001] The invention belongs to the field of signal denoising, and relates to an improved interval threshold surface electromyography signal denoising method based on complementary set empirical mode decomposition. Background technique [0002] Surface electromyography (sEMG) is a weak bioelectric signal collected by the collection electrode. This bioelectric signal can reflect the relevant information of muscles and human behavior. It has been widely used in sports medicine, rehabilitation areas such as training and machine control. The surface EMG signal is mainly distributed between 10Hz-500Hz, its amplitude is only 1μV, and it also has nonlinear and non-stationary characteristics. Therefore, EMG signals are easily polluted by noise. There are three main sources of noise: power line interference, white Gaussian noise, and baseline drift. Therefore, maintaining the purity of the signal is a prerequisite for the analysis and application of surface EMG sig...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0488A61B5/00
CPCA61B5/7203A61B5/7235A61B5/316A61B5/389
Inventor 席旭刚章燕石鹏袁长敏杨晨范影乐罗志增
Owner HANGZHOU DIANZI UNIV
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