Arm surface electromyogram signal-based gesture recognition method

A myoelectric signal and gesture recognition technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of large amount of calculation and complex gesture classification methods, achieve low power consumption, reduce data processing complexity, The effect of strong portability

Active Publication Date: 2017-06-13
NANJING UNIV OF INFORMATION SCI & TECH
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problems raised by the above-mentioned background technology, the present invention aims to provide a gesture recognition metho

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
  • Arm surface electromyogram signal-based gesture recognition method
  • Arm surface electromyogram signal-based gesture recognition method
  • Arm surface electromyogram signal-based gesture recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] Such as figure 1 As shown, a gesture recognition method based on arm surface electromyographic signals, the steps are as follows:

[0038] Step 1: Set the sampling frequency to 200 Hz and the sampling time to 500 ms to repeatedly sample the electromyographic signals to obtain M electromyographic signals in total, and the length of each electromyographic signal is N=100.

[0039] Step 2: Calculate the mean value of the absolute value of the collected myoelectric signal, calculate the first-order difference of the mean value of the absolute value of the adjacent two segments of the myoelectric signal, and calculate the mean value of the absolute value of the myoelectric signal, the absolute value of the two adjacent segments of the myoelectric signal The first-order difference of the mean value is used as the eigenvalue of the EMG sig...

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 an arm surface electromyogram signal-based gesture recognition method. According to the method, specific features of electromyogram signals which are bio-electricity signal are utilized, so that the data processing complexity is reduced, and the gesture recognition efficiency can be up to a relatively high level. Compared with the traditional method, the method disclosed by the invention saves a signal time frequency analysis process, so that the complexity and calculation amount are greatly reduced, the requirements for performance of data processors are not high, and the cost is saved.

Description

technical field [0001] The invention belongs to the technical field of human motion recognition, and in particular relates to a gesture recognition method based on arm surface electromyographic signals. Background technique [0002] Surface electromyography (SEMG) is a bioelectrical signal associated with neuromuscular activity. When the motor command is transmitted to the relevant muscle fibers through the central nervous system, the potential on the muscle fibers will change and the contraction of the muscle fibers will occur. The electromyographic electrodes collect electrical signal information. The surface electromyography signal contains the information of muscle contraction mode and contraction intensity. Different body movements correspond to different electromyography signals. By analyzing the surface electromyography signal, the specific action pattern corresponding to the signal can be identified. [0003] The existing gesture discrimination method requires time...

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
IPC IPC(8): G06K9/00
CPCG06V40/28G06F2218/08G06F2218/12
Inventor 张自嘉徐晨严程
Owner NANJING UNIV OF INFORMATION SCI & TECH
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