Static surface electromyogram signal decomposition method

A myoelectric signal, static technology, applied in the field of muscle neuron discharge information, can solve the problem that it cannot be separated reliably

Pending Publication Date: 2022-04-15
HANGZHOU DIANZI UNIV
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Problems solved by technology

The main limitation of the BBS method is that the ability to identify MUs is mainly determined by the energy of their action potentials: almost all MUs with high MUAP energies can be reliably extracted, whereas MUs with low energy MUAPs are considered physiological noise , cannot be reliably separated out

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  • Static surface electromyogram signal decomposition method
  • Static surface electromyogram signal decomposition method
  • Static surface electromyogram signal decomposition method

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with specific examples. The following description is only for demonstration and explanation, and does not limit the present invention in any form.

[0046] Step 1. Use the electromyography acquisition device to collect the surface electromyography signals of the biceps brachii, the sampling frequency is 2000 Hz, the number of channels is 64 channels, and the sampling time is 10 seconds.

[0047] Step 2. Perform 20-500 Hz band-pass filtering on the collected signal, and perform delay expansion with a delay factor of 10, and the expanded signal matrix should be 640x20000.

[0048] Step 3. Perform cyclic CKC decomposition on the preprocessed signal to obtain the preliminary MU discharge sequence, and divide the MU discharge sequence into a good sequence and a poor sequence according to the index. The structure is as follows figure 1 As shown, the specific steps are:

[0049]3-1. Calculate the covariance...

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Abstract

The invention discloses a static surface electromyogram (sEMG) decomposition method. Aiming at the problem that a traditional sEMG decomposition method based on blind source separation cannot extract a small motion unit (MU), the method adopts a mode of combining multiple strategies to decompose the MU. The method comprises the following steps: firstly, acquiring an electric signal of biceps brachii muscle of a subject by adopting myoelectricity acquisition equipment, and performing preprocessing and channel expansion; and then the large MU is accurately decomposed through cyclic CKC, and the small MU is decomposed by combining an improved cyclic CKC method with a strict iteration strategy (Post-Processor) and a stripping strategy. Compared with the prior art, the method has the advantages that the decomposition yield and the decomposition precision of the MU are greatly improved, a good decomposition result can be obtained in a high-noise environment, and the robustness is high.

Description

technical field [0001] The invention relates to a method for decomposing static surface electromyography signals, in particular to a method for obtaining discharge information of muscle neurons by decomposing static surface electromyography signals. Background technique [0002] Over the past few decades, surface electromyography (sEMG) has received considerable attention due to its non-invasive nature, high yield of motor units (MU), and application to high contraction levels of muscle force. Through major advances in sEMG signal acquisition and processing, this technology has played a key role in understanding the neurophysiology of the neuromuscular system and in the diagnosis of motor neurological and neuromuscular disorders. The sEMG signal is the sum of active motor unit action potentials (MUAPs). sEMG decomposition, a technique capable of decomposing sEMG signals into individual MUAPs, is essential for the study of MU discharge information and MUAP waveforms. [000...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 郑赟马玉良汪婷席旭刚
Owner HANGZHOU DIANZI UNIV
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