Method for rapidly and automatically identifying and removing ocular artifacts in electroencephalogram signal
An electroencephalogram signal and oculoelectric artifact technology, which is applied in the fields of electrical digital data processing, medical science, special data processing applications, etc., can solve problems such as the inability to automatically identify oculoelectric artifacts
Inactive Publication Date: 2012-10-03
BEIJING UNIV OF TECH
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[0014] Aiming at the two shortcomings of independent component analysis ICA when removing electro-oculogram artifacts in EEG, the separation effect and speed of the algorithm are affected by the interference of various noises, and the electro-oculogram artifacts cannot be automatically identified, the present invention proposes An automatic removal method of EEG artifacts in EEG signals based on discrete wavel
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[0080] The specific implementation of the present invention will be further described below in conjunction with the accompanying drawings. This embodiment is carried out under the simulation environment of matlab.
[0081] 1. see figure 2 According to the international standard lead 10-20 system, electrodes were placed at C3 and C4, and 2-lead EEG signals were collected x 1 (t) and x 2 (t), in addition, a guide eye electrical signal x was collected synchronously at F7 3 (t), a total of 3 guide signals were collected x(t)=[x 1 (t),x 2 (t),x 3 (t)] T , the reference electrodes are placed at A1 and A2. The sampling frequency of the signal is 250Hz, and the analog filtering range is 0.1~100Hz. Each EEG recording time is 10s, and the number of sampling points is 2500.
[0082] see Figure 4 , which is the waveform of EEG signals collected from 2 leads and 1-lead EEG signal. It can be seen that the EEG signals have different influences on each lead EEG, forming electro-oc...
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The invention provides a method for rapidly and automatically identifying and removing ocular artifacts in an electroencephalogram signal and belongs to the technical field of biological information and the method is mainly applied to a process of acquiring and preprocessing the electroencephalogram signal. The method comprises the following specific steps of: carrying out discrete wavelet transformation on an acquired multi-channel electroencephalogram signal and an electro-oculogram signal to obtain multi-scale wavelet coefficients; using the wavelet coefficients connected in series as an input for analyzing an independent component, and rapidly acquiring the independent component by using a negative entropy criterion-based Fast ICA (Independent Component Analysis) algorithm; identifying the ocular artifacts through a cosine method, performing zero resetting on the independent component, and projecting the other components through ICA inverse transformation and returning to all electrodes of an original signal; and finally obtaining the electroencephalogram signal for removing the ocular artifacts through inversion of the wavelet transformation. By utilizing the method for rapidly and automatically identifying and removing the ocular artifacts in the electroencephalogram signal, the problems that an ICA method is poor in discrete effect and low in convergence rate when beingapplied to noisy electroencephalogram signals are solved, and the function of rapidly and automatically identifying and removing the ocular artifacts in the electroencephalogram signal is realized.
Description
Technical field: [0001] The invention belongs to the technical field of electroencephalography (Electroencephalography, EEG) acquisition and preprocessing. Specifically, it relates to a fast automatic removal method of electrooculogram artifacts in EEG signals based on discrete wavelet transform (Discrete Wavelet Transform, DWT) and independent component analysis (Independent Component Analysis, ICA). Background technique [0002] EEG signal is a kind of bioelectrical signal that reflects brain activity, and plays an increasingly important role in the process of studying human brain function and diseases. However, EEG signals are very weak and have high time-varying sensitivity, and are easily interfered by irrelevant noise during acquisition, thus forming various EEG artifacts. These artifacts bring great difficulties to the analysis and processing of EEG signals. Electro-oculogram (EOG) is one of the most important interference components in EEG signals, it will randomly...
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Login to view more IPC IPC(8): A61B5/0476G06F19/00
Inventor 李明爱崔燕李骧杨金福郝冬梅马建勇陆婵婵
Owner BEIJING UNIV OF TECH
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