薛定谔滤波结合阈值算法在核磁脑电梯度伪迹去噪的应用  

Application of schrodinger filtering combining threshold algorithm for gradient artifact removal in EEG-fMRI

作　　者：黄海 李文杰[1,2] 邹凌 Huang Hai;Li Wenjie;Zou Ling(School of Microelectronics and Control Engineering,Changzhou University,Changzhou 213164,China;Changzhou Key Laboratory of Biomedical Information Technology,Changzhou 213164,China)

机构地区：[1]常州大学微电子与控制工程学院,常州213164 [2]常州市生物医学信息技术重点实验室,常州213164

出　　处：《电子测量技术》2023年第13期155-162,共8页Electronic Measurement Technology

基　　金：江苏省重点研发计划项目(BE2021012-2,BE2021012-5);常州市科技计划(CE20225034);江苏省研究生科研与实践创新计划(KYCX22_3050)项目资助

摘　　要：基于功能磁共振(fMRI)同步采集的脑电图(EEG),在使用平均模板相减法(AAS)预处理之后,仍存在梯度残留尖峰伪迹。需要更准确地去除残留尖峰,以减少基于频率的活动推断的干扰,降低时间序列之间的虚假相关性。本文针对EEG数据中尖峰伪迹的特性,先使用薛定谔滤波方法分解并识别包含尖峰的EEG数据,自动减去与EEG幅度相差较大的大部分尖峰成分,然后使用幅度阈值方法,通过逆补余误差定位与EEG幅度相当的残留尖峰,实现对尖峰伪迹的定位与去除。对于模拟信号,该方法得到的信号幅值误差(Er)较薛定谔滤波方法平均提高24.95%,信噪比(SNR)较薛定谔滤波方法提高27.13%;对于真实信号,本文方法得到皮尔逊相关系数明显小于另外4种方法,去噪效果较薛定谔滤波方法提升11.42%。无论是尖峰位于波形波谷,还是高频波动幅度与峰值相当的情况下,薛定谔滤波结合阈值算法较其他方法尖峰识别精度和去噪效果明显提高。此去噪方法为EEG-fMRI的融合研究提供了强有力的支持。In electroencephalography(EEG)data acquired in synchronization with functional magnetic resonance(fMRI),gradient residual spiking artifacts persisted after preprocessing using average template subtraction(AAS).There is a need for more accurate removal of residual spikes,so as to decrease the interference from frequency-based activity inferences,and less spurious correlations between time series.Aiming at the characteristics of spike artifacts in EEG data,this paper first uses the Schrödinger method to decompose and identify the EEG data containing spikes,automatically subtracts most of the spike components with a large amplitude difference from the EEG,and then uses the amplitude threshold method to compensate the error by inverse compensation.Residual spikes with the same amplitude as the EEG are located to realize the location and removal of spike artifacts.For simulated signals,the signal amplitude error(Er)obtained by this method is 24.95%higher than that of the Schrödinger method on average,and the signal-to-noise ratio(SNR)is 27.13%higher than that of the Schrödinger method.For real signals,the Pearson correlation coefficient obtained by this method is significantly less than For the other four methods,the denoising effect is 11.42%higher than that of the Schrodinger method.Compared with other methods,the use of Schrodinger combined with threshold algorithm,significantly improved the peak recognition accuracy and the denoising effect,whether the peak is located in the trough of the waveform,or the high-frequency fluctuation amplitude is comparable to the peak.This denoising method provides strong support for the fusion study of EEG-fMRI.

关 键 词：脑电 功能磁共振 梯度场伪迹 薛定谔滤波 幅度阈值 

分 类 号：R318[医药卫生—生物医学工程]