一种基于EWT-ICEEMDAN的单通道脑电信号眼电伪迹去除算法  

An EWT-ICEEMDAN-Based Method to Remove Electrooculogram Artifacts in Single-Channel EEG Signals

作　　者：宋婷 舒智林[1,2] 孙玉波 韩建达 于宁波[1,2] SONG Ting;SHU Zhilin;SUN Yubo;HAN Jianda;YU Ningbo(College of Artificial Intelligence,Nankai University,Tianjin 300350,China;Tianjin Key Laboratory of Intelligent Robotics,Nankai University,Tianjin 300350,China)

机构地区：[1]南开大学人工智能学院,天津300350 [2]南开大学天津市智能机器人技术重点实验室,天津300350

出　　处：《传感技术学报》2023年第10期1584-1592,共9页Chinese Journal of Sensors and Actuators

基　　金：国家自然科学基金项目(U1913208,61873135);中央高校基本科研业务费。

摘　　要：脑电信号和眼电信号存在频谱混叠,目前的单通道脑电信号中眼电伪迹去除方法容易造成脑电信号失真。提出一种基于经验小波变换(EWT)和改进的自适应噪声完备经验模态分解(ICEEMDAN)的单通道脑电信号眼电伪迹去除算法。首先使用EWT将单通道脑电信号分解为δ频段和高频段信号,再用ICEEMDAN将δ频段信号自适应分解为多维本征模态函数(IMFs),设置样本熵阈值自动去除眼电伪迹信号,最后重构得到滤波后的脑电信号。基于半模拟脑电数据和真实脑电数据开展实验,结果表明所提算法相比于已有算法能够在去除眼电伪迹的同时更好地保留原始脑电信息。There is spectrum aliasing between electroencephalogram(EEG)and electrooculogram(EOG)signals,and existing EOG artifacts removing methods for single-channel EEG signals lead to the loss of useful EEG information.A novel EOG artifacts removal method for single-channel EEG signals is proposed based on empirical wavelet transform(EWT)and improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN).Firstly,the EOG artifacts that contaminate single-channel EEG signals are decomposed intoδrhythm and high rhythm sub￣signals by EWT,and then theδrhythm sub-signal is adaptively decomposed into multi-dimensional intrinsic mode functions(IMFs)by ICEEMDAN.Finally,the sample entropy threshold is set,IMFs with EOG artifacts are automatically removed,and the EEG signals are reconstructed.Experiments are performed on semi-simulated EEG data and actual EEG data.The results demonstrate that,compared with existing methods,the proposed method can effectively remove the EOG artifacts and retain the original EEG information with better performance.

关 键 词：单通道脑电信号 眼电伪迹 经验小波变换 完备经验模态分解 

分 类 号：TN911.7[电子电信—通信与信息系统] R318[电子电信—信息与通信工程]