Methods for Processing Physiological Artifacts in Single/Few-Channel EEG Signals

VernacularTitle:单通道/少通道脑电信号生理伪迹处理方法
Author: Guojing WANG ^{1
,

2} ; Hongyun LIU ; Weidong WANG ; Hongyan KANG
Author Information

1. 北京航空航天大学生物与医学工程学院,北京市,100191
2. 中国人民解放军总医院医学创新研究部,北京市,100853
Keywords: single/few-channel EEG; artifact; mixed method; machine learning
From: Chinese Journal of Medical Instrumentation 2024;48(3):298-305
CountryChina
Language:Chinese
Abstract: Electroencephalogram(EEG)is a non-invasive measurement method of brain electrical activity.In recent years,single/few-channel EEG has been used more and more,but various types of physiological artifacts seriously affect the analysis and wide application of single/few-channel EEG.In this paper,the regression and filtering methods,decomposition methods,blind source separation methods and machine learning methods involved in the various physiological artifacts in single/few-channel EEG are reviewed.According to the characteristics of single/few-channel EEG signals,hybrid EEG artifact removal methods for different scenarios are analyzed and summarized,mainly including single-artifact/multi-artifact scenes and online/offline scenes.In addition,the methods and metrics for validating the performance of the algorithm on semi-simulated and real EEG data are also reviewed.Finally,the development trend of single/few-channel EEG application and physiological artifact processing is briefly described.