Practical method for removing artifacts from online electroencephalograph

An artifact and EEG technology, applied in the field of biomedical information processing, to achieve the effect of strong super Gaussian, efficient automatic identification and elimination, and large kurtosis

Inactive Publication Date: 2017-10-20
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0009] The present invention provides a practical online EEG artifact removal method combining DWT, ICA and HC, that is, the DWICAC method, to solve the problem that various conventional EEG artifacts cannot be detected in the current motor imagery EEG preprocessing algorithm. In the case of a single channel, problems that are automatically identified and eliminated online

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  • Practical method for removing artifacts from online electroencephalograph
  • Practical method for removing artifacts from online electroencephalograph
  • Practical method for removing artifacts from online electroencephalograph

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Embodiment 1

[0049] Embodiment 1: as Figure 1-11 As shown, a practical online EEG artifact removal method, the experimental design and data description are as follows:

[0050] The preprocessing method proposed in this paper was tested on the left and right hand motor imagery EEG of 10 healthy subjects, including 6 males and 4 females; all of them are right-handed, age range: 19 to 25 years old; Master's degree, no medical history or EEG collection experience affecting brain function, all subjects signed the informed consent for the experimental research before the experiment.

[0051] The data acquisition equipment for this experiment is a 16-lead EEG amplifier (Mipower-UC, EEG Collection V2, Neural Engineering Laboratory of Tsinghua University), 0Hz-250Hz signal frequency band, sampling frequency 1000Hz, 24-bit A / D converter, no Power frequency notch; 16-lead EEG cap (Ag-AgCL powder electrode, Wuhan Greentech Technology Co., Ltd.) customized by the international standard lead 10-20 sys...

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Abstract

The invention relates to a practical method for removing artifacts from online electroencephalograph, and belongs to the technical field of biomedical information processing. The method corrects a down sampling of the reduced channel real-time electroencephalograph signals, a power frequency notch wave and a linear drift, the discrete wavelet transform is used for decomposing the down sampling of the reduced channel electroencephalograph signals into 7 layers, and single channel electroencephalograph signals are converted to multiple channels. The wavelet coefficients are reconstructed and used as inputs to ICA. Fast acquisition of independent components is implemented using Fast ICA algorithm. According to the characteristics of time domain, frequency domain and ordinal correlation of each artifact in the independent component, which is different from the normal electroencephalograph component, hierarchical clustering algorithm is introduced to cluster each independent component, the categories of artifacts are automatically recognized, the artifacts are reconstructed after the zero artifact is zero, and the reconstructed electroencephalograph signals are obtained. The method solves the problem that the prior method cannot automatically identify and remove a variety of conventional electroencephalograph artifacts in the absence of reduced channel.

Description

technical field [0001] The invention relates to a practical online EEG artifact removal method, which belongs to the technical field of biomedical information processing. Background technique [0002] Electroencephalography (EEG) contains a large amount of psychological, physiological and pathological information, and is currently widely used in many research fields such as brain disease diagnosis and brain-computer interface (BCI). Normal EEG signals are mainly distributed in the five frequency ranges of delta frequency band (0-4Hz), theta frequency band (4-8Hz), alpha frequency band (8-13Hz), beta frequency band (13-20Hz), and gamma frequency band (30-80Hz) However, the amplitude of EEG is very weak, and it is easily interfered by various artifacts such as electrooculogram (EOG, EOG), electromyogram (EMG), 50Hz power frequency, and linear drift. The existence of these artifacts seriously affects the BCI. performance. [0003] In some previous artifact removal methods, ar...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476A61B5/00
CPCA61B5/7203A61B5/7235A61B5/7253A61B5/316A61B5/369
Inventor 陈健熊馨伏云发刘琳琳
Owner KUNMING UNIV OF SCI & TECH
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