单通道脑电信号中眼电干扰的检测及去除方法
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摘要
针对脑电信号(EEG)中眼电(EOG)干扰的问题,提出一种单通道脑电信号中眼电干扰的检测及去除方法。首先,根据多窗口一阶导数求和(MSDW)的特点,提出了单通道脑电信号中眼电干扰的检测方法;然后,使用小波变换(WT)对眼电干扰进行估计;最后,从原始脑电信号中减去估计的眼电信号,得到纯净的脑电信号。实验结果表明,对于不同通道的脑电信号,该方法均能有效地检测及去除眼电干扰;此外,该方法不需要使用多个脑电信号通道和专门的眼电信号通道。
To solve the ElectroOculoGram( EOG) artifact problem in ElectroEncephaloGram( EEG), an EOG detection and removal method for single channel EEG signal was proposed. According to the characteristics of Multi-window Summation of first Derivatives in a sliding Window( MSDW), a method to detect EOG artifacts from a single channel was proposed.Then, EOG artifacts were estimated using Wavelet Transform( WT). Finally, EOG artifacts were eliminated by subtracting the estimated EOG signals from raw EEG signal. Experimental results show that the method can effectively detect and remove EOG artifacts from EEG signal in different channels. In addition, data from multiple EEG signal channels and special EOG signal channel were not required in our method.
To solve the ElectroOculoGram( EOG) artifact problem in ElectroEncephaloGram( EEG), an EOG detection and removal method for single channel EEG signal was proposed. According to the characteristics of Multi-window Summation of first Derivatives in a sliding Window( MSDW), a method to detect EOG artifacts from a single channel was proposed.Then, EOG artifacts were estimated using Wavelet Transform( WT). Finally, EOG artifacts were eliminated by subtracting the estimated EOG signals from raw EEG signal. Experimental results show that the method can effectively detect and remove EOG artifacts from EEG signal in different channels. In addition, data from multiple EEG signal channels and special EOG signal channel were not required in our method.
引文
[1]罗志增,曹铭.基于最大信噪比盲源分离的脑电信号伪迹滤波算法[J].电子学报,2011,39(12):2926-2931.
[2]NAQVI S A A,BADRUDDIN N,JATOI M A,et al.EEG based time and frequency dynamics analysis of visually induced motion sickness(VIMS)[J].Australasian Physical&Engineering Sciences in Medicine,2015,38(4):721-729.
[3]FERNANDES A S,FEINER S K.Combating VR sickness through subtle dynamic field-of-view modification[C]//Proceedings of the11th IEEE Symposium on 3D User Interfaces.Piscataway:IEEE,2016.201-210.
[4]DIELS C,HOWARTH P A.Frequency characteristics of visually induced motion sickness[J].Human Factors:The Journal of the Human Factors and Ergonomics Society,2013,55(3):595-604.
[5]TEIXEIRA A R,TOMA M,LANG E W,et al.Automatic removal of high-amplitude artefacts from single-channel electroencephalograms[J].Computer Methods and Programs in Biomedicine,2006,83(2):125-138.
[6]吴明权,李海峰,马琳.单通道脑电信号中眼电干扰的自动分离方法[J].电子与信息学报,2015,37(2):367-372.
[7]计瑜,沈继忠,施锦河.一种基于盲源分离的眼电伪迹自动去除方法[J].浙江大学学报(工学版),2013,47(3):415-421.
[8]CROFT R J,BARRY R J.Removal of ocular artifact from the EEG:a review[J].Neurophysiologie Clinique/Clinical Neurophysiology,2000,30(1):5-19.
[9]NAGA R,CHANDRALINGAM S,ANJANEYULU T,et al.Denoising EOG signal using stationary wavelet transform[J].Measurement Science Review,2012,12(2):46-51.
[10]王星,彭承琳,赵德春,等.基于VLSI无线代能通信系统耦合线圈实验[J].仪器仪表学报,2009,30(11):2428-2432.
[11]CHANG W D,CHA H S,KIM K,et al.Detection of eye blink artifacts from single prefrontal channel electroencephalogram[J].Computer Methods and Programs in Biomedicine,2015,124(C):19-30.
[12]NGUYEN H A T,MUSSON J,LI F,et al.EOG artifact removal using a wavelet neural network[J].Neurocomputing,2012,97(1):374-389.
[13]BENEDETTO S,PEDROTTI M,MININ L,et al.Driver workload and eye blink duration[J].Transportation Research Part F:Traffic Psychology and Behaviour,2011,14(3):199-208.
[14]SCHLEICHER R,GALLEY N,BRIEST S,et al.Blinks and saccades as indicators of fatigue in sleepiness warnings:looking tired?[J].Ergonomics,2008.51(7):982-1010.
[15]BULLING A,WARD J A,GELLERSEN H,et al.Eye movement analysis for activity recognition using electrooculography[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(4):741-753.
[2]NAQVI S A A,BADRUDDIN N,JATOI M A,et al.EEG based time and frequency dynamics analysis of visually induced motion sickness(VIMS)[J].Australasian Physical&Engineering Sciences in Medicine,2015,38(4):721-729.
[3]FERNANDES A S,FEINER S K.Combating VR sickness through subtle dynamic field-of-view modification[C]//Proceedings of the11th IEEE Symposium on 3D User Interfaces.Piscataway:IEEE,2016.201-210.
[4]DIELS C,HOWARTH P A.Frequency characteristics of visually induced motion sickness[J].Human Factors:The Journal of the Human Factors and Ergonomics Society,2013,55(3):595-604.
[5]TEIXEIRA A R,TOMA M,LANG E W,et al.Automatic removal of high-amplitude artefacts from single-channel electroencephalograms[J].Computer Methods and Programs in Biomedicine,2006,83(2):125-138.
[6]吴明权,李海峰,马琳.单通道脑电信号中眼电干扰的自动分离方法[J].电子与信息学报,2015,37(2):367-372.
[7]计瑜,沈继忠,施锦河.一种基于盲源分离的眼电伪迹自动去除方法[J].浙江大学学报(工学版),2013,47(3):415-421.
[8]CROFT R J,BARRY R J.Removal of ocular artifact from the EEG:a review[J].Neurophysiologie Clinique/Clinical Neurophysiology,2000,30(1):5-19.
[9]NAGA R,CHANDRALINGAM S,ANJANEYULU T,et al.Denoising EOG signal using stationary wavelet transform[J].Measurement Science Review,2012,12(2):46-51.
[10]王星,彭承琳,赵德春,等.基于VLSI无线代能通信系统耦合线圈实验[J].仪器仪表学报,2009,30(11):2428-2432.
[11]CHANG W D,CHA H S,KIM K,et al.Detection of eye blink artifacts from single prefrontal channel electroencephalogram[J].Computer Methods and Programs in Biomedicine,2015,124(C):19-30.
[12]NGUYEN H A T,MUSSON J,LI F,et al.EOG artifact removal using a wavelet neural network[J].Neurocomputing,2012,97(1):374-389.
[13]BENEDETTO S,PEDROTTI M,MININ L,et al.Driver workload and eye blink duration[J].Transportation Research Part F:Traffic Psychology and Behaviour,2011,14(3):199-208.
[14]SCHLEICHER R,GALLEY N,BRIEST S,et al.Blinks and saccades as indicators of fatigue in sleepiness warnings:looking tired?[J].Ergonomics,2008.51(7):982-1010.
[15]BULLING A,WARD J A,GELLERSEN H,et al.Eye movement analysis for activity recognition using electrooculography[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(4):741-753.