Time-frequency-space muscle collaborative analysis method based on wavelet and non-negative tensor decomposition

A technology of non-negative tensor decomposition and analysis method, applied in the field of time-frequency space-time muscle synergy analysis based on wavelet and non-negative tensor decomposition, which can solve the problems of lack of evidence

Pending Publication Date: 2022-03-18
YANSHAN UNIV
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Problems solved by technology

[0004] At present, there is still insufficient evidence on the neura...

Method used

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  • Time-frequency-space muscle collaborative analysis method based on wavelet and non-negative tensor decomposition
  • Time-frequency-space muscle collaborative analysis method based on wavelet and non-negative tensor decomposition
  • Time-frequency-space muscle collaborative analysis method based on wavelet and non-negative tensor decomposition

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Embodiment

[0052] Such as figure 1 As shown, a time-frequency space-time muscle synergy analysis method based on wavelet and non-negative tensor decomposition includes the following steps:

[0053] Step 1, adopt the Wireless EMG wireless synchronous acquisition system to synchronously collect the electromyographic signals of 8 channels;

[0054] Synchronous acquisition of multi-channel surface electromyographic signals during upper limb movement:

[0055] The superficial muscles of the right upper extremity were collected using the electrode patch sensor: biceps brachii (Biceps Brachii, BB), brachioradialis (Brachioradialis, B), flexor carpi radialis (FCR), palmar Palmarislongus (PL), extensor carpi radialis (ECR), extensor digitorum (ED), extensor carpi ulnaris (ECU) and flexor digitorum superficialis ( Flexor Digitorum Superficialis, FDS) as the research object is considered to be the main muscle group involved in wrist movement, which meets the research needs. First, wipe the skin ...

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Abstract

The invention discloses a time-frequency-space muscle collaborative analysis method based on wavelet and non-negative tensor decomposition, and belongs to the technical field of neurological rehabilitation engineering and movement mechanisms, and the method comprises the steps: firstly, carrying out the synchronous collection and preprocessing of multi-channel surface electromyogram signals in an upper limb movement process; secondly, wavelet decomposition is carried out on the preprocessed data, and wavelet signal data tensors are constructed for the time-frequency electromyographic signals after wavelet transformation and multi-channel time-frequency signals of the same action; the number of decomposition layers is set in advance, the three matrixes obtained after decomposition are multiplied by the kernel tensor, a reconstructed data tensor is obtained, and then a fitting value FIT is calculated; judging a cooperative and non-cooperative relationship; and finally, judging the spectrum component of the synergy muscle. From the perspective of motion generation and execution, the function activation states of synergy muscles in the muscle synergy model on different frequency bands are discussed, the internal mode of nervous system functions can be revealed, and a physiological basis can be provided for the motion rehabilitation process of a stroke patient.

Description

technical field [0001] The invention relates to the technical field of neurorehabilitation engineering and motion mechanism, in particular to a time-frequency-space muscle synergy analysis method based on wavelet and non-negative tensor decomposition. Background technique [0002] According to the "China Stroke Prevention Report", the current morbidity and mortality of stroke are relatively high, and after the onset of stroke, there is a 75% possibility of causing different degrees of motor dysfunction. The most common clinical symptom of stroke patients is hemiplegia of the contralateral upper limb, manifested as muscle weakness or contracture, joint laxity and other states. How to promote the recovery of upper limb motor function is a hot and difficult point in rehabilitation medicine. The central nervous system (CNS) receives incoming information from all parts of the body, and transmits the nerve excitation impulse to the muscles, which excites the muscles and generates...

Claims

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Application Information

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IPC IPC(8): A61B5/397A61B5/00
CPCA61B5/397A61B5/7203A61B5/7225A61B5/7253
Inventor 谢平常清雅程生翠陈晓玲王新宇杨轶楠胡晓翎
Owner YANSHAN UNIV
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