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Ronald Phlypo, Paul Boon, Yves D'Asseler, Ignace Lemahieu, "Removing Ocular Movement Artefacts by a Joint Smoothened Subspace Estimator", Computational Intelligence and Neuroscience, vol. 2007, Article ID 075079, 13 pages, 2007. https://doi.org/10.1155/2007/75079
Removing Ocular Movement Artefacts by a Joint Smoothened Subspace Estimator
To cope with the severe masking of background cerebral activity in the electroencephalogram (EEG) by ocular movement artefacts, we present a method which combines lower-order, short-term and higher-order, long-term statistics. The joint smoothened subspace estimator (JSSE) calculates the joint information in both statistical models, subject to the constraint that the resulting estimated source should be sufficiently smooth in the time domain (i.e., has a large autocorrelation or self predictive power). It is shown that the JSSE is able to estimate a component from simulated data that is superior with respect to methodological artefact suppression to those of FastICA, SOBI, pSVD, or JADE/COM1 algorithms used for blind source separation (BSS). Interference and distortion suppression are of comparable order when compared with the above-mentioned methods. Results on patient data demonstrate that the method is able to suppress blinking and saccade artefacts in a fully automated way.
- A. Lutz, L. L. Greischar, N. B. Rawlings, M. Ricard, and R. J. Davidson, “Long-term meditators self-induce high-amplitude gamma synchrony during mental practice,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 46, pp. 16369–16373, 2004.
- A. Gunji, R. Ishii, W. Chau, R. Kakigi, and C. Pantev, “Rhythmic brain activities related to singing in humans,” NeuroImage, vol. 34, no. 1, pp. 426–434, 2007.
- W. de Clercq, A. Vergult, B. Vanrumste, W. van Paesschen, and S. van Huffel, “Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 12, part 1, pp. 2583–2587, 2006.
- T. C. Weerts and P. J. Lang, “The effects of eye fixation and stimulus and response location on the contingent negative variation (CNV),” Biological Psychology, vol. 1, no. 1, pp. 1–19, 1973.
- R. Verleger, “The instruction to refrain from blinking affects auditory P3 and N1 amplitudes,” Electroencephalography and Clinical Neurophysiology, vol. 78, no. 3, pp. 240–251, 1991.
- C. J. Ochoa and J. Polich, “P300 and blink instructions,” Clinical Neurophysiology, vol. 111, no. 1, pp. 93–98, 2000.
- M. Iwasaki, C. Kellinghaus, A. V. Alexopoulos et al., “Effects of eyelid closure, blinks, and eye movements on the electroencephalogram,” Clinical Neurophysiology, vol. 116, no. 4, pp. 878–885, 2005.
- H. Hallez, A. Vergult, R. Phlypo et al., “Muscle and eye movement artifact removal prior to EEG source localization,” in Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '06), pp. 1002–1005, New York, NY, USA, August-September 2006.
- S. A. Hillyard and R. Galambos, “Eye movement artifact in the CNV,” Electroencephalography and Clinical Neurophysiology, vol. 28, no. 2, pp. 173–182, 1970.
- R. J. Somsen and B. van Beek, “Ocular artifacts in children's EEG: selection is better than correction,” Biological Psychology, vol. 48, no. 3, pp. 281–300, 1998.
- M. Fatourechi, A. Bashashati, R. K. Ward, and G. E. Birch, “EMG and EOG artifacts in brain computer interface systems: a survey,” Clinical Neurophysiology, vol. 118, no. 3, pp. 480–494, 2007.
- R. J. Croft and R. J. Barry, “Removal of ocular artifact from the EEG: a review,” Neurophysiologie Clinique, vol. 30, no. 1, pp. 5–19, 2000.
- A. Schlögl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, and G. Pfurtscheller, “A fully automated correction method of EOG artifacts in EEG recordings,” Clinical Neurophysiology, vol. 118, no. 1, pp. 98–104, 2007.
- S. Makeig, A. J. Bell, T.-P. Jung, and T. J. Sejnowski, “Independent component analysis of electroencephalographic data,” in Advances in Neural Information Processing Systems, vol. 8, pp. 145–151, MIT Press, Cambridge, Mass, USA, 1996.
- R. N. Vigário, “Extraction of ocular artefacts from EEG using independent component analysis,” Electroencephalography and Clinical Neurophysiology, vol. 103, no. 3, pp. 395–404, 1997.
- G. L. Wallstrom, R. E. Kass, A. Miller, J. F. Cohn, and N. A. Fox, “Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods,” International Journal of Psychophysiology, vol. 53, no. 2, pp. 105–119, 2004.
- G. Wallstrom, R. Kass, A. Miller, J. Cohn, and N. Fox, “Correction of ocular artifacts in the EEG using Bayesian adaptive regression splines,” in Bayesian Statistics, vol. 6, pp. 351–366, Springer, New York, NY, USA, 2002.
- O. G. Lins, T. W. Picton, P. Berg, and M. Scherg, “Ocular artifacts in recording EEGs and event-related potentials II: source dipoles and source components,” Brain Topography, vol. 6, no. 1, pp. 65–78, 1993.
- S. Casarotto, A. M. Bianchi, S. Cerutti, and G. A. Chiarenza, “Principal component analysis for reduction of ocular artefacts in event-related potentials of normal and dyslexic children,” Clinical Neurophysiology, vol. 115, no. 3, pp. 609–619, 2004.
- R. Phlypo, P. van Hese, H. Hallez et al., “PSVD: a method for robust, real time eye movement artifact rejection from the EEG,” in Proceedings of the 3rd IET International Conference on Advances in Medical, Signal and Information Processing (MEDSIP '06), p. 4, Glasgow, Scotland, July 2006.
- A. Hyvärinen and E. Oja, “A fast fixed-point algorithm for independent component analysis,” Neural Computation, vol. 9, no. 7, pp. 1483–1492, 1997.
- T.-W. Lee, M. Girolami, and T. J. Sejnowski, “Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources,” Neural Computation, vol. 11, no. 2, pp. 417–441, 1999.
- A. Belouchrani, K. Abed-Meraim, J.-F. Cardoso, and E. Moulines, “A blind source separation technique using second-order statistics,” IEEE Transactions on Signal Processing, vol. 45, no. 2, pp. 434–444, 1997.
- P. Comon, “Independent component analysis. a new concept?” Signal Processing, vol. 36, no. 3, pp. 287–314, 1994.
- J.-F. Cardoso and A. Souloumiac, “Blind beamforming for non-Gaussian signals,” IEE Proceedings F, vol. 140, no. 6, pp. 362–370, 1993.
- M. Borga and H. Knutsson, “A canonical correlation approach to blind source separation,” Tech. Rep. LiU-IMT-EX-0062, Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 2001.
- V. Krishnaveni, S. Jayaraman, L. Anitha, and K. Ramadoss, “Removal of ocular artifacts from EEG using adaptive thresholding of wavelet coefficients,” Journal of Neural Engineering, vol. 3, no. 4, pp. 338–346, 2006.
- A. Erfanian and B. Mahmoudi, “Real-time ocular artifact suppression using recurrent neural network for electro-encephalogram based brain-computer interface,” Medical and Biological Engineering and Computing, vol. 43, no. 2, pp. 296–305, 2005.
- S. Puthusserypady and T. Ratnarajah, “Robust adaptive techniques for minimization of EOG artefacts from EEG signals,” Signal Processing, vol. 86, no. 9, pp. 2351–2363, 2006.
- R. Agarwal, T. Takeuchi, S. Laroche, and J. Gotman, “Detection of rapid-eye movements in sleep studies,” IEEE Transactions on Biomedical Engineering, vol. 52, no. 8, pp. 1390–1396, 2005.
- H. Hallez, P. van Hese, B. Vanrumste et al., “Dipole localization errors due to not incorporating compartments with anisotropic conductivities: simulation study in a spherical head model,” International Journal of Bioelectromagnetism, vol. 7, no. 1, pp. 134–137, 2005.
- M. Babaie-Zadeh and C. Jutten, “Semi-blind approaches for source separation and independent component analysis,” in Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN '06), pp. 301–312, Bruges, Belgium, April 2006.
- J. M. Stern and J. Engel Jr., Atlas of EEG Patterns, Lippincott Williams & Wilkins, Philadelphia, Pa, USA, 2004.
- G. H. Golub and C. F. van Loan, Matrix Computations, The Johns Hopkins University Press, Baltimore, Md, USA, 3rd edition, 1996.
- W. J. Freeman, “Origin, structure, and role of background EEG activity—part 2: analytic phase,” Clinical Neurophysiology, vol. 115, no. 9, pp. 2089–2107, 2004.
- A. Hyvärinen, J. Särelä, and R. Vigário, “Bumps and spikes: artifacts generated by independent component analysis with insufficient sample size,” in Proceedings of the 1st International Workshop on Independent Component Analysis and Blind Signal Separation (ICA '99), pp. 425–429, Aussois, France, January 1999.
- J.-F. Cardoso, “High-order contrasts for independent component analysis,” Neural Computation, vol. 11, no. 1, pp. 157–192, 1999.
- C. W. Hesse and C. J. James, “On semi-blind source separation using spatial constraints with applications in EEG analysis,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 12, part 1, pp. 2525–2534, 2006.
- W. Lu and J. C. Rajapakse, “ICA with reference,” in Proceedings of the 3rd International Conference on Independent Component Analysis and Blind Source Separation (ICA '01), pp. 120–125, San Diego, Calif, USA, December 2001.
- E. Vincent, R. Gribonval, and C. Févotte, “Performance measurement in blind audio source separation,” IEEE Transactions on Audio, Speech and Language Processing, vol. 14, no. 4, pp. 1462–1469, 2006.
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