ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method

A technology of electrical interference and automatic eye, applied in the fields of electrical digital data processing, medical science, special data processing applications, etc., can solve problems affecting EEG signal analysis, deformation of EEG signal segments, and inability to realize automatic removal, etc.

Inactive Publication Date: 2014-04-02
HARBIN INST OF TECH
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Problems solved by technology

After the PCA-based method removes the EOG interference, the EEG signal segment without EOG interference will be deformed, thus affecting the analysis of the EEG signal
The ICA-based method cannot automatically remove the independent component (Independent Component, IC) containing EOG interference, and because the IC decomposition process is an estimation process, the IC decomposed is not accurate, and some high-frequency EEG components removed, thereby affecting the analysis of the EEG signal

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  • ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method
  • ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method
  • ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method

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Embodiment 1

[0047] According to the technical solution of the present invention, combined with the two parts included in HHT: EMD and HSA, respectively in the application of trend item feature extraction and instantaneous frequency calculation, it is realized that after the original EEG signal is passed through ICA, which components contain EOG and which components are automatically judged Which segment contains EOG, and minimize the impact of the EOG removal operation on the part that does not contain EOG, provides a new method for removing EOG from EEG signals. The concrete implementation method of invention is as follows:

[0048] Step 1: Decompose the original EEG signal into several ICs by ICA. It is generally believed that as many leads are used when collecting EEG data, ICA will decompose it into as many ICs.

[0049] Step 2: Segment and window all ICs. The choice of segment length should be moderate, too short is not conducive to the extraction of subsequent statistical features...

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Abstract

The invention discloses an ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method. The method includes: firstly, decomposing an acquired electroencephalogram signal containing an electrooculogram signal into a plurality of independent components by independent component analysis; then extracting trend terms of each independent component by empirical mode decomposition, calculating statistical characteristics so as to determine the independent component containing the electrooculogram signal, utilizing Hilbert spectrum analysis to reserve high-frequency components, not belonging to the electrooculogram signal, in the independent components and eliminate low-frequency components belonging to the electrooculogram signal simultaneously. The Hilbert-Huang transform includes the empirical mode decomposition and the Hilbert spectrum analysis. By the method, frequency bands in the electroencephalogram signal not containing the electrooculogram signal are unaffected, and after the electrooculogram signal is eliminated, the region without the electrooculogram signal is closer to the original electroencephalogram signal.

Description

technical field [0001] The invention specifically relates to an automatic oculoelectric interference removal method based on fusion of ICA and HHT. Background technique [0002] In the past few decades, the analysis and research on the electroencephalogram (Electroencephalogram, EEG) signal has played an important role in the fields of neuroscience, psychology and biomedicine. However, because the voltage of the EEG signal is very small, usually only about 50 microvolts, it is often disturbed by interference sources during the recording process, resulting in some artifacts, which often hinder the analysis and research of brain waves. Among the artifacts, the electrooculogram (EOG) signal is the most important interference, which will randomly appear in the EEG signal and has a large amplitude. EOG is divided into horizontal EOG and vertical EOG. Horizontal EOG is caused by the movement of the eyes with the attention target, which can be reduced or even eliminated by reducin...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476G06F19/00
Inventor 高畅李海峰李嵩马琳薄洪剑吴明权张玮杨大易房春英
Owner HARBIN INST OF TECH
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