Method for removing ocular artifacts in EEG signals

A technology of ophthalmic artifact and EEG signal, applied in medical science, sensor, diagnostic recording/measurement, etc., can solve problems such as loss of EEG information, achieve good denoising effect, improve signal-to-noise ratio, and reduce signal The effect of mean squared error

Active Publication Date: 2015-06-10
杭州瑞尔唯康科技有限公司
View PDF6 Cites 25 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it is not advisable to directly remove MIMFs related to oculoelectr

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 EEG signals
  • Method for removing ocular artifacts in EEG signals
  • Method for removing ocular artifacts in EEG signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] The present invention is described in detail below in conjunction with accompanying drawing.

[0019] refer to figure 1 , a method for removing electrooculometric artifacts in EEG signals, comprising the following steps:

[0020] Step 1. Perform MEMD processing on the EEG signal X(t) containing oculoelectric artifacts. Compared with the empirical mode decomposition (empirical mode decomposition, EMD) method, MEMD can simultaneously process multi-channel EEG signals, which can Make the signals of all channels in each MIMF produced be in the same frequency band, so as to carry out subsequent processing in the same frequency band, set the EEG signal X(t)=[x 1 (t),x 2 (t),...,x n (t)] T , where n represents the number of channels of the EEG signal, t represents the time, T represents the transposition of the matrix, and the EEG signal is decomposed by MEMD to generate m MIMFs, namely where each MIMF i They are all n-channel signals, and the signals of each channel ar...

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 removing ocular artifacts in EEG signals. The two methods of ICA and MEMD are combined, the MEMD is used for extracting ocular artifacts from the EEG signals completely and retaining part of EEG information, so as to avoid the loss of the part of EEG information when the ocular artifacts are removed; the ICA is used for separating the ocular artifacts from the EEG signals, judging the artifacts through calculating a fourth-order cumulant of independent components, and then removing the electro-oculogram. The method for removing ocular artifacts in EEG signals can not only identify and remove the ocular artifacts automatically, but also retains a large number of EEG information, thereby providing a new idea for EEG de-noising; the method can not only remove the ocular artifacts effectively, but also retains a large number of useful EEG information; compared with the independent ICA method, the IMEMD method has better de-noising effect, can further improve the signal to noise ratio and reduces the mean-square error of signals.

Description

technical field [0001] The invention relates to a method for preprocessing EEG signals, in particular to a method for removing electrooculogram artifacts in EEG signals, which is mainly applied to brain working memory, EEG signal feature extraction, and auxiliary disease diagnosis and treatment. Background technique [0002] EEG signals are produced by brain nerve cells and reflect biological electrical signals of brain activity. Because EEG has the characteristics of easy acquisition, non-invasiveness, and high temporal resolution, EEG plays an increasingly important role in scientific research and disease diagnosis. However, the EEG signal is very weak, the amplitude is small, and the randomness is strong. During the signal acquisition process, it is interfered by various noises, such as: eye electricity, myoelectricity, electrocardiogram, power frequency and so on. Therefore, the collected EEG signals contain various artifacts. As a common artifact, the amplitude of eye...

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
CPCA61B5/7203A61B5/316A61B5/369
Inventor 王刚滕超淋闫相国任都甜
Owner 杭州瑞尔唯康科技有限公司
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