Upper limb movement recognition method and system based on surface electromyogram signals

A technology of electromyographic signal and motion recognition, applied in the field of motion recognition, can solve the problems of increasing the amount of data and signal processing complexity, reducing the rate of motion recognition, and the number of types of recognized motions, etc., to reduce data redundancy, improve accuracy, The effect of reducing the delay time

Active Publication Date: 2020-12-04
QUFU NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] To sum up, in the current research and application, most of the simple action recognition of single-joint movement is performed by using surface electromyography signals. The amount of data and the complexity of signal processing will reduce the action recognition rate

Method used

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  • Upper limb movement recognition method and system based on surface electromyogram signals
  • Upper limb movement recognition method and system based on surface electromyogram signals
  • Upper limb movement recognition method and system based on surface electromyogram signals

Examples

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Embodiment 1

[0057]This embodiment discloses an upper limb movement recognition method based on surface electromyography signal multi-joint continuous movement, which can use 8-channel sEMG signals to accurately identify shoulder level adduction / abduction, elbow flexion / shoulder extension, elbow inward 14 kinds of upper body movements such as retraction / abduction, elbow flexion / extension, wrist adduction / abduction, wrist flexion / extension, fist clenching / stretching fist, etc. The method includes an offline classification model training stage and an online action recognition stage, such as figure 1 shown.

[0058] (1) Offline classification model training stage

[0059] Step 1: Obtain multiple muscle EMG signals corresponding to various upper limb movements as a training data set.

[0060] In this embodiment, the EMG sEMG signals of 8 muscles were collected when 8 subjects performed 14 kinds of upper limb movements: deltoid muscle, pectoralis major, biceps brachii, flexor carpi radialis, ...

Embodiment 2

[0160] The purpose of this embodiment is to provide an upper limb motion recognition system based on surface electromyographic signals.

[0161] An upper limb movement recognition system based on surface electromyographic signals, comprising:

[0162] The signal acquisition module acquires the myoelectric signals of multiple muscles of the upper limb;

[0163] The signal preprocessing module performs denoising preprocessing on the EMG signal, and extracts the active segment signal in the EMG signal based on the frame energy method;

[0164] The feature extraction module performs feature extraction on the active segment signal according to the optimal feature fusion method;

[0165] The feature fusion module fuses the extracted features;

[0166] The action recognition module uses the SVM classifier for action recognition according to the fused features.

Embodiment 3

[0168] The purpose of this embodiment is to provide an electronic device.

[0169] An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, when the processor executes the program, the following steps are implemented, including:

[0170] Obtain EMG signals from multiple muscles in the upper limbs;

[0171] Based on the sub-frame energy method, the active segment signal in the EMG signal is extracted;

[0172] Perform feature extraction and feature fusion on the active segment signal according to the optimal feature fusion method;

[0173] According to the fused features, the SVM classifier is used for action recognition.

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Abstract

The invention discloses an upper limb motion recognition method and system based on surface electromyogram signals. The method comprises the following steps of obtaining electromyogram signals of muscles of multiple positions of an upper limb; extracting an active segment signal in the electromyographic signal based on a framing energy method; performing feature extraction and feature fusion on the active segment signal according to the optimal feature fusion mode; and performing action recognition by adopting an SVM classifier according to the fused features. According to the method, by searching for the optimal feature combination mode, it is guaranteed that the needed features can be rapidly and accurately obtained and fused, and the efficiency and accuracy of action recognition are improved.

Description

technical field [0001] The invention belongs to the technical field of motion recognition, in particular to an upper limb motion recognition method and system based on surface electromyography signals. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] The upper limb motion recognition technology based on surface electromyographic signals is safe, real-time, and convenient, and is widely used in many fields such as prosthetic limb control, somatosensory game control, teleoperation, sports medicine, biomedicine, and rehabilitation engineering. [0004] According to the inventor's understanding, the existing recognition methods with high offline recognition rate often have fewer types of recognized actions (4-6), simple actions, and fewer participating joints (1-2), and often do not go through online action recognition verification. There ar...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/20G06F2218/06G06F2218/04G06F2218/08G06F18/2411G06F18/253
Inventor 曹佃国武玉强解学军张中才李聪
Owner QUFU NORMAL UNIV
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