Method for identifying human lower limb surface EMG signals (electromyographic signals)

A technology of electromyographic signal and identification method, which is used in applications, medical science, sensors, etc.

Inactive Publication Date: 2016-10-12
成都奥特为科技有限公司
View PDF8 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the study of lower limb EMG signals, in 2016, John A.Spanias et al. used the LDA algorithm to study the method of classifying only EMG signals and classifying EMG signals and other types of data returned by instrument sensors; 2014 In 2010, AJ Young et al. used the method of Sensor Time History to classify EMG signals, but this method only considered the time span of the signal in the whole process

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for identifying human lower limb surface EMG signals (electromyographic signals)
  • Method for identifying human lower limb surface EMG signals (electromyographic signals)
  • Method for identifying human lower limb surface EMG signals (electromyographic signals)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] Below in conjunction with accompanying drawing, describe technical scheme of the present invention in detail:

[0034] Such as figure 1 As shown, the present invention is used for the identification method of human body lower limb surface electromyography signal, mainly comprises the following steps:

[0035] Step 1) Acquisition of the original EMG signal of the lower limb movement:

[0036] Stick the disposable EMG electrode on the skin of the muscle tissue of the lower limbs, and collect the surface EMG signal c(t) of the corresponding muscle mass under the stimulation of the activity in real time;

[0037] Step 2) Raw signal preprocessing (artifact removal method):

[0038] Perform artifact removal on the acquired original EMG signal, which includes filtering out power frequency interference noise, Gaussian white noise, and baseline drift noise. There is no fixed order for the filtering of the three kinds of noise in this step. Here, the order of filtering of powe...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a method for identifying human lower limb surface EMG signals (electromyographic signals). The method comprises the following main steps: acquiring surface EMG signals of corresponding muscle blocks under the stimulation of movement actions in real time; carrying out pretreatment on the collected EMG signals, thus obtaining the EMG signals with artifact signals eliminated; carrying out decomposition on the obtained EMG signals by adopting a discrete wavelet transform method, thus obtaining a low-frequency coefficient vector and a high-frequency coefficient row; carrying out singular value decomposition on obtained wavelet components by adopting a filtering method combining time domain with frequency domain, and constituting a characteristic matrix by adopting the singular values obtained by decomposition; carrying out training on a characteristic sample by adopting a support vector machine, and generating a support vector machine classifier for carrying out classification and identification on a blind sample. The method has the beneficial effects that compared with the prior art, the novel lower limb EMG signal preprocessing method is provided.

Description

technical field [0001] The invention is designed to be used in the technical field of artifact elimination, feature extraction and identification of surface electromyographic signals (Electromyographic Signal, EMG) in bioelectric signals of human lower limbs. Background technique [0002] According to statistical data, my country has officially entered the aging society at the beginning of the 21st century, and the aging process exceeds that of other countries. It is estimated that the elderly population in my country will reach 248 million in 2020 and 400 million in 2050. The elderly and the physically disabled are rapidly expanding in the population structure, and the salient feature of the above-mentioned population is that they need assistance in their daily activities. Paralysis is one of the most common causes of loss of mobility in the above populations, especially lower body paralysis, which involves partial or complete loss of function of the limbs and trunk. At pr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0488A61B5/04
CPCA61B5/316A61B5/389
Inventor 张羿温悦欣张向刚秦开宇
Owner 成都奥特为科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap