2 Preprocessing of EEG
33
102. E.M. ter Braack, B. de Jonge, M.J. van Putten, Reduction of TMS induced artifacts in EEG
using principal component analysis. IEEE Trans. Neural Syst. Rehab. Eng. 21, 376–382 (2013)
103. K. Ting, P. Fung, C. Chang, F. Chan, Automatic correction of artifact from single-trial eventrelated potentials by blind source separation using second order statistics only. Med. Eng.
Phys. 28, 780–794 (2006)
104. J.A. Urigüen, B. Garcia-Zapirain, EEG artifact removal—state-of-the-art and guidelines. J.
Neural Eng. 12, 031001 (2015)
105. A. Van Boxtel, Optimal signal bandwidth for the recording of surface EMG activity of facial,
jaw, oral, and neck muscles. Psychophysiology 38, 22–34 (2001)
106. R. VanRullen, Four common conceptual fallacies in mapping the time course of recognition.
Front. Psychol. 2, 365 (2011)
107. G.L. Wallstrom, R.E. Kass, A. Miller, J.F. Cohn, N.A. Fox, Automatic correction of ocular
artifacts in the EEG: a comparison of regression-based and component-based methods. Int.
J. Psychophysiol. 53, 105–119 (2004)
108. G. Wang, C. Teng, K. Li, Z. Zhang, X. Yan, The removal of EOG artifacts from EEG signals
using independent component analysis and multivariate empirical mode decomposition. IEEE
J. Biomed. Health Inform. 20, 1301–1308 (2016)
109. I. Winkler, S. Brandl, F. Horn, E. Waldburger, C. Allefeld, M. Tangermann, Robust artifactual
independent component classification for BCI practitioners. J. Neural Eng. 11, 035013 (2014)
110. I. Winkler, S. Debener, K.-R. Müller, M. Tangermann, On the influence of high-pass filtering
on ICA-based artifact reduction in EEG-ERP, in Abstracts of the Engineering in Medicine
and Biology Society, EMBC, 37th Annual International Conference of the IEEE (2015)
111. I. Winkler, S. Haufe, M. Tangermann, Automatic classification of artifactual ICA-components
for artifact removal in EEG signals. Behav. Brain Funct. 7, 30 (2011)
112. D. Wu, J.-T. King, C.-H. Chuang, C.-T. Lin, T.-P. Jung, Spatial filtering for EEG-based
regression problems in brain-computer interface (BCI). IEEE Trans. Fuzzy Syst. (2017)
113. D. Yao, A method to standardize a reference of scalp EEG recordings to a point at infinity.
Physiol. Meas. 22, 693 (2001)
114. D. Yao, L. Wang, R. Oostenveld, K.D. Nielsen, L. Arendt-Nielsen, A.C. Chen, A comparative
study of different references for EEG spectral mapping: the issue of the neutral reference and
the use of the infinity reference. Physiol. Meas. 26, 173 (2005)
115. H. Zeng, A. Song, R. Yan, H. Qin, EOG artifact correction from EEG recording using stationary subspace analysis and empirical mode decomposition. Sensors 13, 14839–14859 (2013)
116. K. Zeng, D. Chen, G. Ouyang, L. Wang, X. Liu, X. Li, An EEMD-ICA approach to enhancing
artifact rejection for noisy multivariate neural data. IEEE Trans. Neural Syst. Rehab. Eng. 24,
630–638 (2016)
117. C. Zhang, J. Yang, Y. Lei, F. Ye, Single channel blind source separation by combining slope
ensemble empirical mode decomposition and independent component analysis. J. Comput.
Inf. Syst. 8, 3117–3126 (2012)
118. C. Zhao, T. Qiu, An automatic ocular artifacts removal method based on wavelet-enhanced
canonical correlation analysis, in Abstracts of the Engineering in Medicine and Biology Society, EMBC, Annual International Conference of the IEEE (2011)
119. Y. Zou, V. Nathan, R. Jafari, Automatic identification of artifact-related independent components for artifact removal in EEG recordings. IEEE J. Biomed. Health Inf. 20, 73–81 (2016)
33
102. E.M. ter Braack, B. de Jonge, M.J. van Putten, Reduction of TMS induced artifacts in EEG
using principal component analysis. IEEE Trans. Neural Syst. Rehab. Eng. 21, 376–382 (2013)
103. K. Ting, P. Fung, C. Chang, F. Chan, Automatic correction of artifact from single-trial eventrelated potentials by blind source separation using second order statistics only. Med. Eng.
Phys. 28, 780–794 (2006)
104. J.A. Urigüen, B. Garcia-Zapirain, EEG artifact removal—state-of-the-art and guidelines. J.
Neural Eng. 12, 031001 (2015)
105. A. Van Boxtel, Optimal signal bandwidth for the recording of surface EMG activity of facial,
jaw, oral, and neck muscles. Psychophysiology 38, 22–34 (2001)
106. R. VanRullen, Four common conceptual fallacies in mapping the time course of recognition.
Front. Psychol. 2, 365 (2011)
107. G.L. Wallstrom, R.E. Kass, A. Miller, J.F. Cohn, N.A. Fox, Automatic correction of ocular
artifacts in the EEG: a comparison of regression-based and component-based methods. Int.
J. Psychophysiol. 53, 105–119 (2004)
108. G. Wang, C. Teng, K. Li, Z. Zhang, X. Yan, The removal of EOG artifacts from EEG signals
using independent component analysis and multivariate empirical mode decomposition. IEEE
J. Biomed. Health Inform. 20, 1301–1308 (2016)
109. I. Winkler, S. Brandl, F. Horn, E. Waldburger, C. Allefeld, M. Tangermann, Robust artifactual
independent component classification for BCI practitioners. J. Neural Eng. 11, 035013 (2014)
110. I. Winkler, S. Debener, K.-R. Müller, M. Tangermann, On the influence of high-pass filtering
on ICA-based artifact reduction in EEG-ERP, in Abstracts of the Engineering in Medicine
and Biology Society, EMBC, 37th Annual International Conference of the IEEE (2015)
111. I. Winkler, S. Haufe, M. Tangermann, Automatic classification of artifactual ICA-components
for artifact removal in EEG signals. Behav. Brain Funct. 7, 30 (2011)
112. D. Wu, J.-T. King, C.-H. Chuang, C.-T. Lin, T.-P. Jung, Spatial filtering for EEG-based
regression problems in brain-computer interface (BCI). IEEE Trans. Fuzzy Syst. (2017)
113. D. Yao, A method to standardize a reference of scalp EEG recordings to a point at infinity.
Physiol. Meas. 22, 693 (2001)
114. D. Yao, L. Wang, R. Oostenveld, K.D. Nielsen, L. Arendt-Nielsen, A.C. Chen, A comparative
study of different references for EEG spectral mapping: the issue of the neutral reference and
the use of the infinity reference. Physiol. Meas. 26, 173 (2005)
115. H. Zeng, A. Song, R. Yan, H. Qin, EOG artifact correction from EEG recording using stationary subspace analysis and empirical mode decomposition. Sensors 13, 14839–14859 (2013)
116. K. Zeng, D. Chen, G. Ouyang, L. Wang, X. Liu, X. Li, An EEMD-ICA approach to enhancing
artifact rejection for noisy multivariate neural data. IEEE Trans. Neural Syst. Rehab. Eng. 24,
630–638 (2016)
117. C. Zhang, J. Yang, Y. Lei, F. Ye, Single channel blind source separation by combining slope
ensemble empirical mode decomposition and independent component analysis. J. Comput.
Inf. Syst. 8, 3117–3126 (2012)
118. C. Zhao, T. Qiu, An automatic ocular artifacts removal method based on wavelet-enhanced
canonical correlation analysis, in Abstracts of the Engineering in Medicine and Biology Society, EMBC, Annual International Conference of the IEEE (2011)
119. Y. Zou, V. Nathan, R. Jafari, Automatic identification of artifact-related independent components for artifact removal in EEG recordings. IEEE J. Biomed. Health Inf. 20, 73–81 (2016)