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

Left-right hand motor imagery electroencephalogram characteristic extraction method mixing wavelet and common spatial pattern

A common spatial mode and EEG signal technology, applied in diagnostic signal processing, medical science, sensors, etc., can solve the problem that the time-frequency characteristics and spatial characteristics of EEG signals cannot be extracted at the same time

Active Publication Date: 2015-04-01
CHONGQING UNIV OF POSTS & TELECOMM
View PDF8 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, in view of the problem that the existing EEG signal feature extraction methods cannot simultaneously extract the time-frequency characteristics and spatial domain characteristics of the EEG signal, the present invention provides a motor imagery EEG signal of left and right hands that mixes wavelet and common spatial patterns feature extraction method

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
  • Left-right hand motor imagery electroencephalogram characteristic extraction method mixing wavelet and common spatial pattern
  • Left-right hand motor imagery electroencephalogram characteristic extraction method mixing wavelet and common spatial pattern
  • Left-right hand motor imagery electroencephalogram characteristic extraction method mixing wavelet and common spatial pattern

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] In this method, wavelet transform is firstly used to decompose the left and right hand motor imagery EEG signals to obtain wavelet coefficients that can reflect its time-frequency characteristics; Analysis, and then extract the eigenvalues ​​that can reflect the time-frequency and space-time characteristics of the left and right hand motor imagery EEG signals.

[0021] Specific steps are as follows:

[0022] Step 1: Wavelet decomposition is performed on the motor imagery EEG signals of the left and right hands to obtain wavelet coefficients that can reflect their time-frequency characteristics.

[0023] When a person imagines a unilateral hand movement, the amplitude of the EEG μ rhythm (8-12 Hz) and β rhythm (14-30 Hz) in the corresponding primary sensorimotor cortex area on the opposite side decreases. This phenomenon is called ev...

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 relates to a left-right hand motor imagery electroencephalogram characteristic extraction method mixing a wavelet and a common spatial pattern, and belongs to the technical field of electroencephalogram identification control. In the method, the wavelet and the common spatial pattern algorithm are mixed to process a left-right hand motor imagery electroencephalogram, and time-frequency-space characteristics capable of representing the left-right hand motor imagery electroencephalogram can be extracted. The left-right hand motor imagery electroencephalogram characteristic extraction method specially comprises the following steps: 1) decomposing the left-right hand motor imagery electroencephalogram by wavelet transform to obtain a wavelet coefficient capable of reflecting the time-frequency characteristics of the left-right hand motor imagery electroencephalogram; 2) analyzing the wavelet coefficient D2 capable of reflecting the time-frequency characteristics of the left-right hand motor imagery electroencephalogram by a CSP (Common Spatial Pattern) algorithm to obtain an optimal spatial filter of the wavelet coefficient; 3) extracting a characteristic value capable of reflecting the time-frequency-space characteristics of the left-right hand motor imagery electroencephalogram by the optimal spatial filter. According to the method, the problem that the time-frequency characteristics and the space-domain characteristics of the electroencephalogram cannot be simultaneously extracted by an electroencephalogram extraction method in the prior art can be solved.

Description

technical field [0001] The invention belongs to the technical field of electroencephalogram signal identification and control, and relates to a method for extracting features of electroencephalogram signals of left and right hand motor imagery by mixing wavelet and common space mode. Background technique [0002] Brain-computer interface (BCI) is a communication system established between the human brain and a computer or external equipment independent of the peripheral nerve and muscle systems of the brain. It can provide a new means of external information exchange for patients with physical disabilities but normal thinking, and has broad application prospects in the fields of rehabilitation of the disabled, auxiliary control of normal people, and entertainment. [0003] Feature extraction is one of the key technologies in BCI research. The commonly used methods include FFT, AR, AAR, wavelet transform, Common Spatial Pattern (CSP) and other methods. FFT, AR and AAR transf...

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): A61B5/0476
CPCA61B5/72A61B5/316A61B5/369
Inventor 张毅罗元刘想德林海波徐晓东胡豁生
Owner CHONGQING UNIV OF POSTS & TELECOMM
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