An Improved Adaptive Filtering Approach for Removing Artifact from the Electroencephalogram
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[1] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.
[2] R. Sameni,et al. An iterative subspace denoising algorithm for removing electroencephalogram ocular artifacts , 2014, Journal of Neuroscience Methods.
[3] Murielle Kirkove,et al. Comparative evaluation of existing and new methods for correcting ocular artifacts in electroencephalographic recordings , 2014, Signal Process..
[4] Marina Schmid,et al. An Introduction To The Event Related Potential Technique , 2016 .
[5] ELECTRICAL POTENTIALS FROM THE INTACT HUMAN BRAIN. , 1968, Science.
[6] P. Berg,et al. A fast method for forward computation of multiple-shell spherical head models. , 1994, Electroencephalography and clinical neurophysiology.
[7] R. Srinivasan,et al. Removal of ocular artifacts from EEG using an efficient neural network based adaptive filtering technique , 1999, IEEE Signal Processing Letters.
[8] R. B. Reilly,et al. FASTER: Fully Automated Statistical Thresholding for EEG artifact Rejection , 2010, Journal of Neuroscience Methods.
[9] R. Ward,et al. EMG and EOG artifacts in brain computer interface systems: A survey , 2007, Clinical Neurophysiology.
[10] G. Pfurtscheller,et al. A fully automated correction method of EOG artifacts in EEG recordings , 2007, Clinical Neurophysiology.
[11] Eric Moulines,et al. A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..
[12] R. Kass,et al. Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods. , 2004, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[13] J. Wolpaw,et al. Brain-Computer Interfaces: Principles and Practice , 2012 .
[14] Glenn F. Wilson,et al. Performance and Psychophysiological Measures of Fatigue Effects on Aviation Related Tasks of Varying Difficulty , 2007 .
[15] Tzyy-Ping Jung,et al. Real-World Neuroimaging Technologies , 2013, IEEE Access.
[16] Patrick Berg,et al. Artifact Correction of the Ongoing EEG Using Spatial Filters Based on Artifact and Brain Signal Topographies , 2002, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[17] Robert E Kass,et al. An Implementation of Bayesian Adaptive Regression Splines (BARS) in C with S and R Wrappers. , 2008, Journal of statistical software.
[18] E. Whitham,et al. Scalp electrical recording during paralysis: Quantitative evidence that EEG frequencies above 20Hz are contaminated by EMG , 2007, Clinical Neurophysiology.
[19] H. Semlitsch,et al. A solution for reliable and valid reduction of ocular artifacts, applied to the P300 ERP. , 1986, Psychophysiology.
[20] B. Rockstroh,et al. Removal of ocular artifacts from the EEG--a biophysical approach to the EOG. , 1985, Electroencephalography and clinical neurophysiology.
[21] F. Matsuo,et al. Electrical phenomena associated with movements of the eyelid. , 1975, Electroencephalography and clinical neurophysiology.
[22] Dorothy V. M. Bishop,et al. Journal of Neuroscience Methods , 2015 .
[23] James C. Christensen,et al. Coadaptive Aiding and Automation Enhance Operator Performance , 2013, Hum. Factors.
[24] Arnaud Delorme,et al. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.
[25] Eric L. Miller,et al. Nonlocal Means Denoising of ECG Signals , 2012, IEEE Transactions on Biomedical Engineering.
[26] R. Barry,et al. Removal of ocular artifact from the EEG: a review , 2000, Neurophysiologie Clinique/Clinical Neurophysiology.
[27] Tharmalingam Ratnarajah,et al. Robust adaptive techniques for minimization of EOG artefacts from EEG signals , 2006, Signal Process..
[28] Jean-Michel Morel,et al. A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[29] R. Barry,et al. EOG correction of blinks with saccade coefficients: a test and revision of the aligned-artefact average solution , 2000, Clinical Neurophysiology.
[30] Tzyy-Ping Jung,et al. Imaging brain dynamics using independent component analysis , 2001, Proc. IEEE.
[31] S. Luck,et al. The effects of electrode impedance on data quality and statistical significance in ERP recordings. , 2010, Psychophysiology.
[32] J. C. Woestenburg,et al. The removal of the eye-movement artifact from the EEG by regression analysis in the frequency domain , 1983, Biological Psychology.
[33] Tobias S. Andersen,et al. Classification of independent components of EEG into multiple artifact classes. , 2015, Psychophysiology.
[34] Erkki Oja,et al. One-unit Learning Rules for Independent Component Analysis , 1996, NIPS.
[35] Ricardo Nuno Vig. Extraction of' ocular artefacts from EEG using independent component analysis , 1997 .
[36] Junshui Ma,et al. High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection , 2011, Journal of Neuroscience Methods.
[37] R. Barry,et al. EOG correction: which regression should we use? , 2000, Psychophysiology.
[38] Tzyy-Ping Jung,et al. Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.
[39] Pierrick Coupé,et al. An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images , 2008, IEEE Transactions on Medical Imaging.
[40] H. Berger,et al. Über das Elektrenkephalogramm des Menschen , 1937, Archiv für Psychiatrie und Nervenkrankheiten.
[41] R. Barry,et al. EOG correction: a new aligned-artifact average solution. , 1998, Electroencephalography and clinical neurophysiology.
[42] V. A. Makarov,et al. Recovering EEG brain signals: Artifact suppression with wavelet enhanced independent component analysis , 2006, Journal of Neuroscience Methods.
[43] Martin J. McKeown,et al. Removing electroencephalographic artifacts: comparison between ICA and PCA , 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).
[44] T. Gasser,et al. Correction of EOG artifacts in event-related potentials of the EEG: aspects of reliability and validity. , 1982, Psychophysiology.
[45] J. Fermaglich. Electric Fields of the Brain: The Neurophysics of EEG , 1982 .
[46] Jan W. M. Bergmans,et al. Using an Eye Tracker for Accurate Eye Movement Artifact Correction , 2007, IEEE Transactions on Biomedical Engineering.
[47] T. Gasser,et al. The transfer of EOG activity into the EEG for eyes open and closed. , 1985, Electroencephalography and clinical neurophysiology.
[48] M.T. Hagan,et al. Multireference adaptive noise canceling applied to the EEG , 1997, IEEE Transactions on Biomedical Engineering.
[49] Richard J. Davidson,et al. Electromyogenic artifacts and electroencephalographic inferences revisited , 2011, NeuroImage.
[50] R. Barry,et al. EOG correction: a new perspective. , 1998, Electroencephalography and clinical neurophysiology.
[51] T. Åkerstedt,et al. Subjective and objective sleepiness in the active individual. , 1990, The International journal of neuroscience.
[52] D. Overton,et al. Distribution of eye movement and eyeblink potentials over the scalp. , 1969, Electroencephalography and clinical neurophysiology.
[53] Gary E. Birch,et al. Online Removal of Eye Movement and Blink EEG Artifacts Using a High-Speed Eye Tracker , 2012, IEEE Transactions on Biomedical Engineering.
[54] C.W. Anderson,et al. Geometric subspace methods and time-delay embedding for EEG artifact removal and classification , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[55] T. Gasser,et al. The correction of EOG artifacts by frequency dependent and frequency independent methods. , 1986, Psychophysiology.
[56] Glenn F. Wilson,et al. Performance Enhancement in an Uninhabited Air Vehicle Task Using Psychophysiologically Determined Adaptive Aiding , 2007, Hum. Factors.
[57] Scott Makeig,et al. BCILAB: a platform for brain–computer interface development , 2013, Journal of neural engineering.
[58] F. Gibbs,et al. THE ELECTRO-ENCEPHALOGRAM IN EPILEPSY AND IN CONDITIONS OF IMPAIRED CONSCIOUSNESS , 1935 .
[59] J. Polich,et al. P300 and blink instructions , 2000, Clinical Neurophysiology.
[60] J. Kamiya,et al. A simple on-line technique for removing eye movement artifacts from the EEG. , 1973, Electroencephalography and clinical neurophysiology.
[61] Elsa Andrea Kirchner,et al. Effects of eye artifact removal methods on single trial P300 detection, a comparative study , 2014, Journal of Neuroscience Methods.
[62] James C. Christensen,et al. Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload , 2015, Front. Neurosci..
[63] P. Berg,et al. Ocular artifacts in EEG and event-related potentials I: Scalp topography , 2005, Brain Topography.
[64] Terrence J. Sejnowski,et al. Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis , 2007, NeuroImage.
[65] D. Chakrabarti,et al. A fast fixed - point algorithm for independent component analysis , 1997 .
[66] B. Widrow,et al. Adaptive noise cancelling: Principles and applications , 1975 .
[67] Richard J. Davidson,et al. Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG , 2010, NeuroImage.
[68] Yu-Tai Tsai,et al. The Removal of Ocular Artifacts from EEG Signals Using Adaptive Filters Based on Ocular Source Components , 2010, Annals of Biomedical Engineering.
[69] Glenn F. Wilson,et al. Removal of ocular artifacts from the EEG: a comparison between time-domain regression method and adaptive filtering method using simulated data , 2007, Medical & Biological Engineering & Computing.
[70] J. Gotman,et al. A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification , 2006, Clinical Neurophysiology.
[71] Tom Eichele,et al. Semi-automatic identification of independent components representing EEG artifact , 2009, Clinical Neurophysiology.
[72] José V. Manjón,et al. MRI denoising using Non-Local Means , 2008, Medical Image Anal..
[73] C. Joyce,et al. Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. , 2004, Psychophysiology.
[74] S. Hillyard,et al. Eye movement artifact in the CNV. , 1970, Electroencephalography and clinical neurophysiology.
[75] T. Sejnowski,et al. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects , 2000, Clinical Neurophysiology.
[76] Lucas C. Parra,et al. Blind Source Separation via Generalized Eigenvalue Decomposition , 2003, J. Mach. Learn. Res..
[77] Tzyy-Ping Jung,et al. Extended ICA Removes Artifacts from Electroencephalographic Recordings , 1997, NIPS.
[78] Terence W. Picton,et al. Ocular artifacts in recording EEGs and event-related potentials II: Source dipoles and source components , 2005, Brain Topography.
[79] P. Berg,et al. Dipole models of eye movements and blinks. , 1991, Electroencephalography and clinical neurophysiology.
[80] E Donchin,et al. A new method for off-line removal of ocular artifact. , 1983, Electroencephalography and clinical neurophysiology.
[81] D. Lykken,et al. Two-year retest stability of eye tracking performance and a comparison of electro-oculographic and infrared recording techniques: evidence of EEG in the electro-oculogram. , 1981, Psychophysiology.
[82] G. Gratton. Dealing with artifacts: The EOG contamination of the event-related brain potential , 1998 .
[83] Xi Chen,et al. A Robust and Fast Non-Local Means Algorithm for Image Denoising , 2008, Journal of Computer Science and Technology.
[84] P Berg,et al. A multiple source approach to the correction of eye artifacts. , 1994, Electroencephalography and clinical neurophysiology.
[85] S. Makeig,et al. Imaging human EEG dynamics using independent component analysis , 2006, Neuroscience & Biobehavioral Reviews.
[86] T. Ratnarajah,et al. H/sup /spl infin// adaptive filters for eye blink artifact minimization from electroencephalogram , 2005, IEEE Signal Processing Letters.
[87] Dimitri Van De Ville,et al. SURE-Based Non-Local Means , 2009, IEEE Signal Processing Letters.
[88] Jean-Michel Morel,et al. A Review of Image Denoising Algorithms, with a New One , 2005, Multiscale Model. Simul..
[89] T. Sejnowski,et al. Removing electroencephalographic artifacts by blind source separation. , 2000, Psychophysiology.
[90] R. Oostenveld,et al. Independent EEG Sources Are Dipolar , 2012, PloS one.
[91] P. Nunez,et al. Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease , 2014, Brain Research.
[92] S. Luck. An Introduction to the Event-Related Potential Technique , 2005 .
[93] A. S. Gevins,et al. Ocular Artifact Minimization by Adaptive Filtering , 1994, IEEE Seventh SP Workshop on Statistical Signal and Array Processing.
[94] P. König,et al. Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data , 2012, Front. Hum. Neurosci..
[95] P Berg,et al. Dipole modelling of eye activity and its application to the removal of eye artefacts from the EEG and MEG. , 1991, Clinical physics and physiological measurement : an official journal of the Hospital Physicists' Association, Deutsche Gesellschaft fur Medizinische Physik and the European Federation of Organisations for Medical Physics.
[96] E. Adrian,et al. THE BERGER RHYTHM: POTENTIAL CHANGES FROM THE OCCIPITAL LOBES IN MAN , 1934 .
[97] G Pfurtscheller,et al. Frequency dependence of the transmission of the EEG from cortex to scalp. , 1975, Electroencephalography and clinical neurophysiology.
[98] R. Kass,et al. Bayesian curve-fitting with free-knot splines , 2001 .
[99] Benjamin Friedlander,et al. Least squares algorithms for adaptive linear-phase filtering , 1982 .
[100] Panagiotis D. Bamidis,et al. REG-ICA: A hybrid methodology combining Blind Source Separation and regression techniques for the rejection of ocular artifacts , 2011, Biomed. Signal Process. Control..
[101] S. Romero,et al. Ocular Reduction in EEG Signals Based on Adaptive Filtering, Regression and Blind Source Separation , 2008, Annals of Biomedical Engineering.
[102] W BARRY,et al. INFLUENCE OF EYE LID MOVEMENT UPON ELECTRO-OCULOGRAPHIC RECORDING OF VERTICAL EYE MOVEMENTS. , 1965, Aerospace medicine.
[103] Joep J. M. Kierkels,et al. A model-based objective evaluation of eye movement correction in EEG recordings , 2006, IEEE Transactions on Biomedical Engineering.
[104] Andreas Ziehe,et al. Automated ocular artifact removal: comparing regression and component-based methods , 2009 .
[105] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[106] G. Wilson,et al. Removal of ocular artifacts from electro-encephalogram by adaptive filtering , 2004, Medical and Biological Engineering and Computing.
[107] A. Mognon,et al. ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features. , 2011, Psychophysiology.