Method for removing ocular artifacts in brain-electrical signal

Abstract

The invention relates to a method for removing eye electrical artifact in EEG signals, which belongs to the technical field of biological information, relates to the technology of EEG signal collection and pretreatment, and is mainly applied to the pretreatment process of the EEG signal acquisition. The method comprises that principal component analysis is carried out on EEG data containing eye electrical artifact; the components of the eye electrical artifact are determined; 1-8Hz of wave filtering is carried out on the time domain waveform of artifact components; attenuation factors of the eye electrical components in each electrode are calculated by combining regression algorithm and using the time domain waveform of artifact components; the attenuation factors are used for regulating the spatial distribution of the eye electrical artifact components; the regulated spatial distribution of the artifact components is used for removing the eye electrical artifact. The method solves the problems that in the traditional method for removing the eye electrical artifact based on principal constituent decomposition, the principal constituent decomposition is incomplete, and the decomposed eye electrical artifact components contain EEG components. The regulation of the attenuation factors causes that the components containing eye electrical are more easily distinguished.

Description

technical field [0001] The invention relates to the technical field of biological information, in particular to the collection and preprocessing technology of electroencephalogram signals. Background technique [0002] EEG plays an important role in the research and diagnosis of brain function because of its non-invasive, high temporal resolution, and ability to reflect large-scale neural electrical activities. However, since EEG signals are only at the microvolt level, they are particularly susceptible to interference from ECG, EMG, and EoG signals (EoE artifacts). Among these interfering signals, the oculoelectric signal is the main signal source of interfering EEG. The oculoelectric signal can change the head surface potential distribution of the EEG and destroy the actual EEG, especially the EEG signal characteristics of the area near the eyes. This makes reading and analyzing EEG signals very difficult. Oculograph artifact removal in EEG signals is not only a concern ...

AI Technical Summary

Problems solved by technology

However, there is a component selection problem in PCA and ICA methods, that is, to specifically select those components as oculoelectric artifact components and remove them.

At present, such algorithms usually require human judgment

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