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Method of automatically removing ocular artifacts from electroencephalogram signal without setting threshold value

A technology for setting thresholds of EEG signals, applied in the field of bioinformatics, can solve problems such as time-consuming, labor-intensive, and heavy workload

Inactive Publication Date: 2012-12-26
BEIJING UNIV OF TECH
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  • Abstract
  • Description
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Problems solved by technology

[0017] The present invention aims at the defects of manual identification of electrooculogram artifacts in traditional EEG signals, time-consuming, laborious and heavy workload, and proposes a method for automatic removal of electrooculogram artifacts

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  • Method of automatically removing ocular artifacts from electroencephalogram signal without setting threshold value
  • Method of automatically removing ocular artifacts from electroencephalogram signal without setting threshold value
  • Method of automatically removing ocular artifacts from electroencephalogram signal without setting threshold value

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Embodiment Construction

[0089] The present invention proposes an automatic removal method of EEG artifacts in EEG signals without manually setting thresholds. The complete algorithm flow includes the following four (1.2.3.4) parts. Among them, the first part is the existing method, and the characteristics of the application of the present invention include three (2.3.4) parts:

[0090] The complete algorithm flow is as follows figure 1 shown.

[0091] 1 independent component decomposition

[0092] The present invention adopts the fastICA algorithm, which has the following advantages: 1. the convergence speed is faster than batch processing and adaptive processing; 2. the effect of negative entropy as a Gaussian measure is better than that of cumulative quantity; 3. the Newton iterative method is adopted, and the convergence is guaranteed;

[0093] Its basic model expression is:

[0094] x ( t ) = As (...

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Abstract

The invention provides a method of automatically removing ocular artifacts from an electroencephalogram signal without setting a threshold value, belongs to the field of biological information technology, and is mainly applied to the preprocessing process of the electroencephalogram signal. The method particularly comprises the following steps: performing an independent component decomposition to a captured electroencephalogram signal containing the ocular artifacts; gaining the kurtosis, the sequence renyi entropy and the sample entropy of each independent component as feature vectors, so as to automatically recognize an independent component containing the ocular artifacts by k-means cluster analysis, and setting the independent component to be zero and other components to be constant, reconstructing the signal, and obtaining a pure electroencephalogram signal. The method provided by the invention solves the problems that the artifacts are identified by means of manual work during the traditional process for removing the ocular artifacts, so that time and labors are wasted and the workload is heavy. In addition, the method provided by the invention can realize the purposes of automatically identifying and removing the ocular artifacts without setting the threshold value by manual work, so that the shortcoming in the existing method that a researcher is required to have definite future knowledges and strong subjectivity during the setting of the the threshold value is overcame.

Description

Technical field: [0001] The present invention relates to the field of biological information technology, in particular to electroencephalogram (Electroenc- [0002] ephalogram, EEG) preprocessing technology. Specifically, it relates to an automatic removal technology of Ocular Artifact (OA) in EEG signals without manual threshold setting. technical background: [0003] EEG signal is a weak electrophysiological signal, which contains a lot of physiological and disease information, and plays an important role in clinical medicine, cognitive psychology and other research fields. The method of recording EEG on the surface of the scalp is the most important signal acquisition method used in the research of EEG signals at present. The recording technology of this method is simple and easy to operate, but the signal is easily interfered by noise. EEG interference has caused great difficulties in the interpretation and analysis of EEG signals. Therefore, it is of great significan...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476G06F19/00
Inventor 李明爱李骧张译帆崔燕乔俊飞杨金福郝冬梅
Owner BEIJING UNIV OF TECH
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