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Tennis elbow recognition method based on electromyographic signals

A recognition method, electromyography signal technology, applied in the field of muscle force calculation and recognition

Pending Publication Date: 2020-09-11
SHANGHAI MARITIME UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These examples all use electromyographic signals to identify simple gait and tennis elbow. At present, there is no relevant literature in China.

Method used

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  • Tennis elbow recognition method based on electromyographic signals
  • Tennis elbow recognition method based on electromyographic signals
  • Tennis elbow recognition method based on electromyographic signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] A kind of identification method based on the tennis elbow of electromyographic signal, its specific embodiment is:

[0018] A method for identifying tennis elbow based on electromyographic signals, comprising the following steps:

[0019] Step 1: The motion capture of the patient's elbow flexion and extension uses 10 cameras, and the sampling frequency of the cameras is 100HZ;

[0020] Step 2: Use Vicon software to model the arm, build a static model, and add motion trajectories on this basis to establish a dynamic model of arm flexion and extension movement. The established dynamic model, where there are missing trajectories and points, complement the missing trajectory and points, get a complete dynamic model, and output C3D files;

[0021] Step 3: Open the Visual 3D software, import the C3D file, and analyze and obtain the corresponding elbow flexion and extension exercise EMG graph of the tennis elbow patient;

[0022] Step 4: Export the EMG of the patient's brach...

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Abstract

The invention provides a tennis elbow recognition method based on electromyographic signals. According to the method, a camera is used for capturing the flexion and extension motion of the elbow a patient; vicon software is used for carrying out modeling on the captured motion; after model establishment, the elbow flexion and extension motion trail of the model is perfected to obtain a motion model; data obtained by Vicon processing is imported into virtual 3D software, and elbow flexion and extension motion is analyzed to obtain a corresponding myoelectricity graph; and the myoelectricity graph is imported into a model learning by using a convolutional neural network (CNN) algorithm to identify tennis elbow.

Description

technical field [0001] The invention mainly relates to the field of muscle force calculation and recognition in biomechanics, in particular to a method for recognizing tennis elbow based on electromyographic signals. Background technique [0002] Tennis elbow is an overuse condition characterized by inflammation and pain in the extensor muscles of the forearm on the outside of the elbow joint. Patients will feel pain when exerting force on the elbow joint, and the susceptible people are mainly tennis players, badminton players, weightlifters, and some laborers who have used the elbow joint for a long time are also prone to tennis elbow. The scientific name of tennis elbow is also called "lateral epicondylitis of the humerus". The two muscles that are often selected for research are the brachioradialis and the extensor carpi ulnaris. The starting point of the brachioradialis is located above the lateral epicondyle of the humerus, and its insertion point is the radial styloid...

Claims

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Application Information

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IPC IPC(8): G16H50/50G06N3/04G06N3/08G16H50/20
CPCG16H50/50G16H50/20G06N3/08G06N3/045
Inventor 唐刚伍川邵长专王冬梅
Owner SHANGHAI MARITIME UNIVERSITY
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