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

Method for removing ocular artifacts in brain-electrical signal

A technology of oculoelectric artifacts and EEG signals, applied in the field of bioinformatics, to achieve the effect of easy recognition

Inactive Publication Date: 2009-07-08
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF0 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is a component selection problem in PCA and ICA methods, that is, to specifically select those components as oculoelectric artifact components and remove them.
At present, such algorithms usually require human judgment

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 removing ocular artifacts in brain-electrical signal
  • Method for removing ocular artifacts in brain-electrical signal
  • Method for removing ocular artifacts in brain-electrical signal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] The present invention will be further described below in conjunction with the accompanying drawings.

[0033]In order to illustrate the process and effect of a method for removing electrooculogram artifacts in EEG signals mentioned in the present invention, a section of real 128-lead EEG signal Y containing electrooculogram artifacts will be used, wherein each lead The signal of is denoted as y i , i=1~128, such as figure 2 shown. It can be seen from the figure that there are obvious electroocular artifacts at the time of 1000ms to 1400ms. Decompose the principal components of Y to obtain the time-domain waveforms of the first three principal components after decomposition, such as image 3 As shown, according to the characteristics of the electro-oculogram artifact, it can be concluded that the first principal component is the electro-oculogram artifact component P, and the spatial distribution of the first principal component can be obtained through principal comp...

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 method for removing eye electrical artifact in EEG signals, which belongs to the technical field of biological information, relates to the technology of EEG signal collection and pretreatment, and is mainly applied to the pretreatment process of the EEG signal acquisition. The method comprises that principal component analysis is carried out on EEG data containing eye electrical artifact; the components of the eye electrical artifact are determined; 1-8Hz of wave filtering is carried out on the time domain waveform of artifact components; attenuation factors of the eye electrical components in each electrode are calculated by combining regression algorithm and using the time domain waveform of artifact components; the attenuation factors are used for regulating the spatial distribution of the eye electrical artifact components; the regulated spatial distribution of the artifact components is used for removing the eye electrical artifact. The method solves the problems that in the traditional method for removing the eye electrical artifact based on principal constituent decomposition, the principal constituent decomposition is incomplete, and the decomposed eye electrical artifact components contain EEG components. The regulation of the attenuation factors causes that the components containing eye electrical are more easily distinguished.

Description

technical field [0001] The invention relates to the technical field of biological information, in particular to the collection and preprocessing technology of electroencephalogram signals. Background technique [0002] EEG plays an important role in the research and diagnosis of brain function because of its non-invasive, high temporal resolution, and ability to reflect large-scale neural electrical activities. However, since EEG signals are only at the microvolt level, they are particularly susceptible to interference from ECG, EMG, and EoG signals (EoE artifacts). Among these interfering signals, the oculoelectric signal is the main signal source of interfering EEG. The oculoelectric signal can change the head surface potential distribution of the EEG and destroy the actual EEG, especially the EEG signal characteristics of the area near the eyes. This makes reading and analyzing EEG signals very difficult. Oculograph artifact removal in EEG signals is not only a concern ...

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): A61B5/0476G06F19/00
Inventor 刘铁军尧德中
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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