单通道脑电信号眼电伪迹去除算法研究
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摘要
由眨眼和眼动产生的眼电伪迹(Electrooculography,EOG)信号是脑电信号(Electroencephalography,EEG)中的主要噪声信号之一.目前,多通道脑电信号中眼电伪迹的去除算法已经较为成熟.而在单通道脑电信号的眼电伪迹去除中,由于采集通道数量较少且缺乏参考眼电信号,目前尚无十分有效的去除方法.本文提出一种基于小波变换(Wavelet transform,WT)、集合经验模态分解(Ensemble empirical mode decomposition,EEMD)和独立成分分析(Independent component analysis,ICA)的WT-EEMD-ICA单通道脑电信号眼电伪迹去除算法.实验表明:WT-EEMD-ICA算法有效地解决了单通道WT-ICA算法中的超完备问题,能够有效去除单通道脑电信号中的眼电伪迹,并且分离出的眼电伪迹成分与参考通道采集的眼电信号相关性较强.
Electrooculography(EOG) artifacts generated by eye movements and blinks are the major artifacts in electroencephalography(EEG). There are many common effective methods for removing the multi-channel EEG artifacts.However, due to the limitation of input channel number and the lack of reference EOG signal, there is no very effective artifact removing method for single-channel EEG signal. In the present study, a novel EOG artifact removing algorithm WT-EEMD-ICA for single-channel EEG signal is proposed based on wavelet transform(WT), ensemble empirical mode decomposition(EEMD) and independent component analysis(ICA) technologies. The result shows that the WT-EEMDICA method, which successfully solves the overcomplete problem of WT-ICA in single channel artifact removal, can separate the EOG and EEG successfully only from one single-channel EEG, and that the useful information involved in original EEG signal can be greatly saved.
Electrooculography(EOG) artifacts generated by eye movements and blinks are the major artifacts in electroencephalography(EEG). There are many common effective methods for removing the multi-channel EEG artifacts.However, due to the limitation of input channel number and the lack of reference EOG signal, there is no very effective artifact removing method for single-channel EEG signal. In the present study, a novel EOG artifact removing algorithm WT-EEMD-ICA for single-channel EEG signal is proposed based on wavelet transform(WT), ensemble empirical mode decomposition(EEMD) and independent component analysis(ICA) technologies. The result shows that the WT-EEMDICA method, which successfully solves the overcomplete problem of WT-ICA in single channel artifact removal, can separate the EOG and EEG successfully only from one single-channel EEG, and that the useful information involved in original EEG signal can be greatly saved.
引文
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2 Hu Jin,Hou Zeng-Guang,Chen Yi-Xiong,Zhang Feng,Wang Wei-Qun.Lower limb rehabilitation robots and interactive control methods.Acta Automatica Sinica,2014,40(11):2377-2390(胡进,侯增广,陈翼雄,张峰,王卫群.下肢康复机器人及其交互控制方法.自动化学报,2014,40(11):2377-2390)
3 Zeng H,Song A G,Yan R Q,Qin H Y.EOG artifact correction from EEG recording using stationary subspace analysis and empirical mode decomposition.Sensors,2013,13(11):14839-14859
4 Wang Xing-Yu,Jin Jing,Zhang Yu,Wang Bei.Brain control:human-computer integration control based on braincomputer interface.Acta Automatica Sinica,2013,39(3):208-221(王行愚,金晶,张宇,王蓓.脑控:基于脑-机接口的人机融合控制.自动化学报,2013,39(3):208-221)
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6 Daly I,Scherer R,Billinger M,M¨uller-Putz G.FORCe:fully online and automated artifact removal for brain-computer interfacing.IEEE Transactions on Neural Systems and Rehabilitation Engineering,2015,23(5):725-736
7 Mannan M M N,Jeong M Y,Kamran M A.Hybrid ICA-regression:automatic identification and removal of ocular artifacts from electroencephalographic signals.Frontiers in Human Neuroscience,2016,10:193-193
8 Qi W.EOG artifacts removal in EEG measurements for affective interaction with brain computer interface.In:Proceedings of the 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing.Piraeus-Athens,Greece:IEEE,2012.471-475
9 Chang W D,Cha H S,Kim K,Im C H.Detection of eye blink artifacts from single prefrontal channel electroencephalogram.Computer Methods and Programs in Biomedicine,2016,124:19-30
10 Vigon L,Saatchi M R,Mayhew J E W,Fernandes R.Quantitative evaluation of techniques for ocular artefact filtering of EEG waveforms.IEE Proceedings-Science Measurement and Technology,2000,147(5):219-229
11 Fatourechi M,Bashashatia A,Ward R K,Birch G E.EMGand EOG artifacts in brain computer interface systems:a survey.Clinical Neurophysiology,2007,118(3):480-494
12 Gomez-Herrero G,Clercq W D,Anwar H,Kara O,Egiazarian K,van Huffel S,van Paesschen W.Automatic removal of ocular artifacts in the EEG without an EOG reference channel.In:Proceedings of the 7th Nordic Signal Processing Symposium.Reykjavik,Iceland:IEEE,2006.130-133
13 Chen Yong-Qiang,Wang Hong-Xia.A method for underdetermined blind source separation based on new mixture model.Acta Automatica Sinica,2014,40(7):1412-1420(陈永强,王宏霞.基于新型混合模型的欠定盲分离方法.自动化学报,2014,40(7):1412-1420)
14 Jung T P,Makeig S,Westerfield M,Townsend J,Courchesne E,Sejnowski T J.Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects.Clinical Neurophysiology,2000,111(10):1745-1758
15 del R Millan J,Mourino J,Franze M,Cincotti F,Varsta M,Heikkonen J,Babiloni F.A local neural classifier for the recognition of EEG patterns associated to mental tasks.IEEE Transactions on Neural Networks,2002,13(3):678-686
16 Croft R J,Barry R J.Removal of ocular artifact from the EEG:a review.Neurophysiologie Clinique,2000,30(1):5-19
17 Zhou W D,Gotman J.Removing eye-movement artifacts from the EEG during the intracarotid amobarbital procedure.Epilepsia,2005,46(3):409-414
18 Sarossy M G,Lee M H A,Bach M.A fast automated method for calculating the EOG arden ratio.Documenta Ophthalmologica,2014,128(3):169-178
19 Wu Ming-Quan,Li Hai-Feng,Ma Lin.Automatic electrooculogram separation method for single channel electroencephalogram signals.Journal of Electronics and Information Technology,2015,37(2):367-372(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.电子与信息学报,2015,37(2):367-372)
20 James C J,Lowe D.Single channel analysis of electromagnetic brain signals through ICA in a dynamical systems framework.In:Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Istanbul,Turkey:IEEE,2001.1974-1977
21 Davies M E,James C J.Source separation using single channel ICA.Signal Processing,2007,87(8):1819-1832
22 Mammone N,La Foresta F,Morabito F C.Automatic artifact rejection from multichannel scalp EEG by wavelet ICA.IEEE Sensors Journal,2012,12(3):533-542
23 Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise-assisted data analysis method.Advances in Adaptive Data Analysis,2009,1(1):1-41
24 Tang Y,Li J P,Wu H.A simple and accurate ICA algorithm for separating mixtures of up to four independent components.Acta Automatica Sinica,2011,37(7):794-799
25 Li H Q,Feng X L,Cao L,Li E B,Liang H A,Chen X L.A new ECG signal classification based on WPD and Ap En feature extraction.Circuits Systems and Processing,2016,35(1):339-352
26 Li M A,Yang L B,Yang J F.Separation of EOG artifacts from EEG signals using Hilbert-Huang transform.In:Proceedings of the 2011 International Conference on Electric Information and Control Engineering.Wuhan,China:IEEE,2011.4453-4456
2 Hu Jin,Hou Zeng-Guang,Chen Yi-Xiong,Zhang Feng,Wang Wei-Qun.Lower limb rehabilitation robots and interactive control methods.Acta Automatica Sinica,2014,40(11):2377-2390(胡进,侯增广,陈翼雄,张峰,王卫群.下肢康复机器人及其交互控制方法.自动化学报,2014,40(11):2377-2390)
3 Zeng H,Song A G,Yan R Q,Qin H Y.EOG artifact correction from EEG recording using stationary subspace analysis and empirical mode decomposition.Sensors,2013,13(11):14839-14859
4 Wang Xing-Yu,Jin Jing,Zhang Yu,Wang Bei.Brain control:human-computer integration control based on braincomputer interface.Acta Automatica Sinica,2013,39(3):208-221(王行愚,金晶,张宇,王蓓.脑控:基于脑-机接口的人机融合控制.自动化学报,2013,39(3):208-221)
5 Jie D,Tao W,Zhang A T,Dai H Y.The removal of blink and saccade artifact in EEG recordings by independent component analysis.In:Proceedings of the 3rd International Conference on Biomedical Engineering and Informatics.Yantai,China:IEEE,2010,3:1071-1075
6 Daly I,Scherer R,Billinger M,M¨uller-Putz G.FORCe:fully online and automated artifact removal for brain-computer interfacing.IEEE Transactions on Neural Systems and Rehabilitation Engineering,2015,23(5):725-736
7 Mannan M M N,Jeong M Y,Kamran M A.Hybrid ICA-regression:automatic identification and removal of ocular artifacts from electroencephalographic signals.Frontiers in Human Neuroscience,2016,10:193-193
8 Qi W.EOG artifacts removal in EEG measurements for affective interaction with brain computer interface.In:Proceedings of the 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing.Piraeus-Athens,Greece:IEEE,2012.471-475
9 Chang W D,Cha H S,Kim K,Im C H.Detection of eye blink artifacts from single prefrontal channel electroencephalogram.Computer Methods and Programs in Biomedicine,2016,124:19-30
10 Vigon L,Saatchi M R,Mayhew J E W,Fernandes R.Quantitative evaluation of techniques for ocular artefact filtering of EEG waveforms.IEE Proceedings-Science Measurement and Technology,2000,147(5):219-229
11 Fatourechi M,Bashashatia A,Ward R K,Birch G E.EMGand EOG artifacts in brain computer interface systems:a survey.Clinical Neurophysiology,2007,118(3):480-494
12 Gomez-Herrero G,Clercq W D,Anwar H,Kara O,Egiazarian K,van Huffel S,van Paesschen W.Automatic removal of ocular artifacts in the EEG without an EOG reference channel.In:Proceedings of the 7th Nordic Signal Processing Symposium.Reykjavik,Iceland:IEEE,2006.130-133
13 Chen Yong-Qiang,Wang Hong-Xia.A method for underdetermined blind source separation based on new mixture model.Acta Automatica Sinica,2014,40(7):1412-1420(陈永强,王宏霞.基于新型混合模型的欠定盲分离方法.自动化学报,2014,40(7):1412-1420)
14 Jung T P,Makeig S,Westerfield M,Townsend J,Courchesne E,Sejnowski T J.Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects.Clinical Neurophysiology,2000,111(10):1745-1758
15 del R Millan J,Mourino J,Franze M,Cincotti F,Varsta M,Heikkonen J,Babiloni F.A local neural classifier for the recognition of EEG patterns associated to mental tasks.IEEE Transactions on Neural Networks,2002,13(3):678-686
16 Croft R J,Barry R J.Removal of ocular artifact from the EEG:a review.Neurophysiologie Clinique,2000,30(1):5-19
17 Zhou W D,Gotman J.Removing eye-movement artifacts from the EEG during the intracarotid amobarbital procedure.Epilepsia,2005,46(3):409-414
18 Sarossy M G,Lee M H A,Bach M.A fast automated method for calculating the EOG arden ratio.Documenta Ophthalmologica,2014,128(3):169-178
19 Wu Ming-Quan,Li Hai-Feng,Ma Lin.Automatic electrooculogram separation method for single channel electroencephalogram signals.Journal of Electronics and Information Technology,2015,37(2):367-372(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.电子与信息学报,2015,37(2):367-372)
20 James C J,Lowe D.Single channel analysis of electromagnetic brain signals through ICA in a dynamical systems framework.In:Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Istanbul,Turkey:IEEE,2001.1974-1977
21 Davies M E,James C J.Source separation using single channel ICA.Signal Processing,2007,87(8):1819-1832
22 Mammone N,La Foresta F,Morabito F C.Automatic artifact rejection from multichannel scalp EEG by wavelet ICA.IEEE Sensors Journal,2012,12(3):533-542
23 Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise-assisted data analysis method.Advances in Adaptive Data Analysis,2009,1(1):1-41
24 Tang Y,Li J P,Wu H.A simple and accurate ICA algorithm for separating mixtures of up to four independent components.Acta Automatica Sinica,2011,37(7):794-799
25 Li H Q,Feng X L,Cao L,Li E B,Liang H A,Chen X L.A new ECG signal classification based on WPD and Ap En feature extraction.Circuits Systems and Processing,2016,35(1):339-352
26 Li M A,Yang L B,Yang J F.Separation of EOG artifacts from EEG signals using Hilbert-Huang transform.In:Proceedings of the 2011 International Conference on Electric Information and Control Engineering.Wuhan,China:IEEE,2011.4453-4456