单通道/少通道脑电信号生理伪迹处理方法  

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

作　　者：王国静 刘洪运[2] 王卫东[2] 康红艳[1] WANG Guojing;LIU Hongyun;WANG Weidong;KANG Hongyan(School of Biological Science and Medical Engineering,Beihang University,Beijing,100191;Medical Innovation Research Division,Chinese PLA General Hospital,Beijing,100853)

机构地区：[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

出　　处：《中国医疗器械杂志》2024年第3期298-305,共8页Chinese Journal of Medical Instrumentation

基　　金：北京市自然科学基金资助项目(7222308)。

摘　　要：脑电图是一种非侵入式的脑电活动测量方式,近年来单通道/少通道的脑电应用越来越多,而多种类型的生理伪迹信号严重影响单通道/少通道脑电的分析和广泛应用。该文针对单通道/少通道脑电中存在的多种生理伪迹,综述了涉及的回归和滤波方法、分解方法、盲源分离方法和机器学习方法。针对单通道/少通道脑电信号的特点,分析总结了用于不同场景的脑电生理伪迹去除的混合方法,主要包括单伪迹/多伪迹场景和在线/离线场景。另外,该文还回顾了在半模拟和真实脑电数据下的验证算法性能的方法和指标。最后,简述了单通道/少通道脑电应用及生理伪迹处理的发展趋势。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.

关 键 词：单通道/少通道脑电 伪迹 混合方法 机器学习 

分 类 号：R318[医药卫生—生物医学工程]