Multi-channel electroencephalogram signal eye artifact automatic removal method and storage medium

A technology of eye electrical artifacts and electroencephalogram signals, applied in the field of electroencephalogram signals, can solve the problems of affecting the effect of artifact removal, waste of energy, and difficulty in recognizing artifact components, and achieve the effect of improving the recognition accuracy.

Pending Publication Date: 2022-03-15
中国人民解放军火箭军工程大学
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Problems solved by technology

However, the traditional ICA method needs to manually identify the components containing electrooculogram artifacts, which is very energy-consuming, and there are relatively large subjective factors, which affect the effect of artifact removal; in addition, ICA cannot completely separate the source signal, and the identified electrooculogram artifacts The trace components will contain some useful EEG information. If these artifact components are directly removed, a large amount of useful information will be lost.
[0004] The automatic removal of oculograph artifacts needs to set the thre

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  • Multi-channel electroencephalogram signal eye artifact automatic removal method and storage medium
  • Multi-channel electroencephalogram signal eye artifact automatic removal method and storage medium
  • Multi-channel electroencephalogram signal eye artifact automatic removal method and storage medium

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Embodiment 1

[0060] See figure 1 , figure 2 , figure 1 It is a schematic flow chart of a method for automatically removing electro-oculogram artifacts of multi-channel EEG signals provided by an embodiment of the present invention, figure 2 It is a schematic flowchart of another method for automatically removing electro-oculogram artifacts of multi-channel EEG signals provided by an embodiment of the present invention. An embodiment of the present invention provides a method for automatically removing electro-oculogram artifacts of multi-channel EEG signals, including steps S1 to S3, wherein:

[0061] S1. Using FastICA (Independent Component Analysis, independent component analysis) and differential evolution algorithm to process the original EEG signal to obtain several independent components, wherein the several independent components include independent components containing electrooculogram artifacts and those without electrooculogram artifacts independent components of .

[0062...

Embodiment 2

[0107] Yet another embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0108] S1. Using FastICA and differential evolution algorithm to process the original EEG signal to obtain several independent components, wherein the several independent components include independent components containing electro-oculogram artifacts and independent components not containing electro-oculogram artifacts;

[0109] S2. Using wavelet transform and the differential evolution algorithm to process the independent components containing electro-oculogram artifacts to obtain electro-oculogram artifact components;

[0110] S3. Based on the wavelet reconstruction and inverse transformation, obtain the EEG signal with the electrooculopathy artifact removed according to the electrooculogram artifact component.

[0111] The computer-readable s...

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Abstract

The invention relates to a multi-channel electroencephalogram signal eye artifact automatic removal method and a storage medium, and the method comprises the steps: S1, processing an original EEG signal through FastICA and a differential evolution algorithm, so as to obtain a plurality of independent components; s2, processing the independent component containing the ocular artifacts by using wavelet transform and the differential evolution algorithm to obtain an ocular artifact component; and S3, based on wavelet reconstruction and inverse transformation, according to the ocular artifact component, obtaining an EEG signal without ocular artifacts. The invention relates to a method for automatically removing ocular artifacts by combining a differential evolution algorithm, FastICA and wavelet transform. According to the method, wavelet decomposition is adopted to decompose artifact components in FastICA, artifacts can be further separated out, useful information in EEG signals is reserved to the maximum extent, and the problem that the useful information is lost in the automatic artifact removing process is solved.

Description

technical field [0001] The invention belongs to the technical field of electroencephalogram signals, and in particular relates to a method for automatically removing electrooculogram artifacts of multi-channel electroencephalogram signals and a storage medium. Background technique [0002] Electroencephalogram (Electroencephalogram, EEG) technology is a relatively mature and typical non-invasive brain-computer interface (Brain-computer Interface, BCI) technology, and it is also a hot research field of BCI technology. EEG signals contain a wealth of information about brain activity and behavioral cognition, and are often used in brain activity analysis and disease diagnosis. However, EEG signals are easily polluted by various artifacts during the acquisition process. The pollution of artifacts is the most serious, which leads to the distortion of the collected EEG signals, which will reduce the accuracy of signal analysis and identification. Therefore, it is very important to...

Claims

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Application Information

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IPC IPC(8): A61B5/369A61B5/00
CPCA61B5/369A61B5/7203A61B5/726A61B5/7267
Inventor 蔡艳平陈万杨梅枝李爱华齐啸姜柯苏延召韩德帅
Owner 中国人民解放军火箭军工程大学
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