Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for controlling grasping force of myoelectric prosthesis

A prosthetic and myoelectric technology, applied in the field of prosthetics, can solve the problems of poor recognition accuracy, less information obtained, and inconvenient use.

Pending Publication Date: 2021-12-03
GUILIN UNIV OF ELECTRONIC TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the prior art, myoelectric prosthetics use fewer sensors to identify the grasping force, so that less information is obtained, the recognition accuracy is poor, and the force adjustment is not suitable, resulting in inconvenient use

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 controlling grasping force of myoelectric prosthesis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0007] Such as figure 1 As shown, after wearing the prosthetic system, the user needs to manually turn on the switch to power on and initialize the prosthetic system. The prosthetic system will collect myoelectric signals through the control center, and classify and recognize the myoelectric signals through the pre-trained recognition model to judge the user's action intention. Here, the myoelectric signal is collected by the myoelectric sensor, the analog signal is converted into a digital signal through the PCF8591 chip, and the data is sent to the K210 processor (neural network processor) in the control center using the I2C bus.

[0008] The recognition model here is obtained by training the training samples using a Support Vector Machine (SVM). Each action needs to collect 30 sets of data, each set of data has 1000 original EMG signal eigenvalues, and the training set and test set are divided according to 6:4. Normalize the training set to the [-1, 1] interval according ...

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 discloses a method for controlling the grasping force of a myoelectric prosthesis, and the method comprises the steps: obtaining a myoelectric signal through a myoelectric sensor, and judging the action intention of a user; when the neural network control center recognizes that the user has grasping and pinching action intentions, driving the artificial limb assembly to act according to the action intentions of the user; starting a camera module to shoot the action target, recognizing the object, and judging the expected pressure needed for holding the object; obtaining and comparing information of the pressure sensor with expected pressure, and adjusting the force applying state of the artificial limb assembly; and when it is recognized that the user has the action intentions of releasing, stretching and the like, the artificial limb assembly is driven to release the grabbed object. The action intention of the user is judged through the electromyographic signals, the grasping force is adjusted in a visual and pressure bidirectional feedback mode, information acquisition channels are increased, force adjustment of the electromyographic artificial limb under various gestures is achieved, and the use scene of the artificial limb is enriched.

Description

technical field [0001] The invention relates to the technical field of artificial limbs, in particular to a method for controlling the grasping force of myoelectric artificial limbs. Background technique [0002] For amputee patients, the installation of limb prosthetics can greatly improve their quality of life and work. With the advancement of technology, the prosthesis can perform more and more actions according to the user's wishes; taking the myoelectric prosthesis as an example, the myoelectric prosthesis can recognize the collected user's myoelectric signal and generate corresponding recognition results for further control The actuator performs corresponding actions. However, in the prior art, myoelectric prosthetics use fewer sensors to identify the grasping force, so that less information is obtained, the recognition accuracy is poor, and the force adjustment is not suitable, resulting in inconvenient use. Contents of the invention [0003] In order to solve the...

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): A61F2/72
CPCA61F2/72
Inventor 李华魏紫屈嘉豪李垚杜晓霞
Owner GUILIN UNIV OF ELECTRONIC TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com