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Method for recognizing human walking gait cycle with electromyographic signal

A technology of electromyographic signals and human body recognition, applied in applications, medical science, sensors, etc., can solve problems such as zero drift, high equipment prices, and large calculations

Inactive Publication Date: 2011-07-27
HEBEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a method for identifying the human body's walking gait cycle with the electromyographic signal, which is a method for identifying the human body's walking gait cycle based on the electromyographic signal of the segmental integration algorithm, and adopts a method based on the trough amplitude. The signal amplitude is analyzed, so the present invention overcomes the easy wear and tear of the signal sensor of the human body motion signal in the prior art, and overcomes the zero drift problem of the myoelectric signal sensor, and only needs a single-channel signal as an information source. And each person has multiple muscles as a choice, which improves the versatility of the application, and also overcomes the shortcomings of the existing gait cycle recognition methods, which are complicated, the equipment price is too high, and the amount of calculation is large

Method used

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  • Method for recognizing human walking gait cycle with electromyographic signal
  • Method for recognizing human walking gait cycle with electromyographic signal
  • Method for recognizing human walking gait cycle with electromyographic signal

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Experimental program
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Effect test

Embodiment 1

[0079] The first step, the equipment used and its installation

[0080] according to Figure 10 As shown, stick the disposable three-point differential input ECG electrode with non-drying conductive gel on the muscle surface of the human leg, and follow the straight line where the positive input electrode 1 and the negative input electrode 2 are located along the human leg. The direction of the muscle fiber is placed on the muscle belly, and the reference ground electrode 3 is pasted at the same distance from the positive input electrode and the negative input electrode. Any two of the positive input electrode 1, the negative input electrode 2 and the reference ground electrode 3 The distances between the electrodes are all equal; the MyoScan-Pro EMG sensor of Thought Technology Company is placed on the above-mentioned ECG electrode, and the three electrodes of the above-mentioned ECG electrode are connected with the MyoScan-Pro EMG sensor through a conductive buckle. Connect...

Embodiment 2

[0097] Except the calculation method of the signal peak-valley linear interpolation piecewise integration algorithm (PVLI&PI) for calculation, other steps and methods are the same as in Embodiment 1.

[0098] Using the peak-valley linear interpolation piecewise integration algorithm, the obtained valley t 1 The eigenvalues ​​are represented by trough t 1 Amplitude is referenced at trough t 1 with crest t 2 Linear interpolation between, trough t 1 to crest t 2 The integral value S of the amplitude after interpolation3 , the resulting peak t 2 The eigenvalues ​​are represented by trough t 3 Amplitude is referenced at peak t 2 with trough t 3 Linear interpolation between, peak t 2 to trough t 3 The integral value S of the amplitude after interpolation 4 , is a negative value, the specific process is:

[0099] The positive phase eigenvalue S including the trough location 3 , that is, record the negative phase eigenvalue S of the rising change of the signal and the peak...

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Abstract

The invention discloses a method for recognizing a human walking gait cycle with an electromyographic signal and relates to a method for measuring human limbs movements. The method for recognizing the human walking gait cycle with the electromyographic signal is characterized in that a utilized device comprises a singlechip, an electromyographic signal sensor and a three-point differential input electrocardio electrode based on a segmentation integral algorithm, wherein the electromyographic signal sensor records and processes the electromyographic signal collected by the electromyographic signal sensor to obtain a positive level unstable signal, then the singlechip transfers, moves and calculates an average filter by utilizing a peak-valley segmentation integral algorithm or a simplified algorithm of a peak-valley linear interpolation segmentation integral algorithm to obtain a human walking gait cycle, therefore, the method solves the problems of easy abrasion of a signal sensor of a human movement signal and zero drift of the electromyographic signal sensor and also overcomes the defects that the traditional gait cycle recognizing method is complex and has high equipment price and larger calculation amount. The method for recognizing the human walking gait cycle with the electromyographic signal only needs a single channel signal as an information source and improves the application universality because a plurality of muscles of a person can be selected.

Description

technical field [0001] The technical scheme of the invention relates to a method for measuring the movement of human body limbs, specifically a method for identifying the walking gait cycle of a human body by using electromyographic signals. Background technique [0002] After literature search, it is found that at present, video detection technology is mainly used for the recognition of gait cycle at home and abroad. CN101477618 The automatic extraction method of pedestrian gait cycle in the video discloses a method for automatically extracting the gait cycle characteristics of the pedestrian target in the video through a theory of frequency domain analysis, but in the evaluation of artificial limbs, walking aids and rehabilitation training Obtaining gait cycle information through these methods in the fields such as these makes the price of the equipment too high, and the calculation amount is relatively large. In 2006, He Lesheng and others published a paper "A Method for...

Claims

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Application Information

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IPC IPC(8): A61B5/11A61B5/0488
Inventor 杨鹏周丽红陈玲玲张腾宇
Owner HEBEI UNIV OF TECH
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