A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis
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Peter Dayan | David S. Holder | Marzia De Lucia | Juan Fritschy | P. Dayan | D. Holder | M. D. Lucia | J. Fritschy | M. Lucia
[1] J. R. Hughes. EEG in Clinical Practice , 1982 .
[2] Tzyy-Ping Jung,et al. Imaging brain dynamics using independent component analysis , 2001, Proc. IEEE.
[3] J R Ives,et al. Automatic recognition of inter-ictal epileptic activity in prolonged EEG recordings. , 1979, Electroencephalography and clinical neurophysiology.
[4] Ricardo Nuno Vig. Extraction of' ocular artefacts from EEG using independent component analysis , 1997 .
[5] Dinh Tuan Pham,et al. Separation of a mixture of independent sources through a maximum likelihood approach , 1992 .
[6] V D Calhoun,et al. Spatial and temporal independent component analysis of functional MRI data containing a pair of task‐related waveforms , 2001, Human brain mapping.
[7] J. Gotman,et al. Systematic source estimation of spikes by a combination of independent component analysis and RAP-MUSIC I: Principles and simulation study , 2002, Clinical Neurophysiology.
[8] Bruce J. West,et al. Wavelet analysis of epileptic spikes. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[9] Saeid Sanei,et al. Removal of eye blinking artifact from the electro-encephalogram, incorporating a new constrained blind source separation algorithm , 2005, Medical and Biological Engineering and Computing.
[10] Aapo Hyvärinen,et al. Survey on Independent Component Analysis , 1999 .
[11] O Ozdamar,et al. Detection of spikes with artificial neural networks using raw EEG. , 1998, Computers and biomedical research, an international journal.
[12] Václav Hlavác,et al. Ten Lectures on Statistical and Structural Pattern Recognition , 2002, Computational Imaging and Vision.
[13] Peter Dayan,et al. The Classification of Spikes in EEG Recordings using Features Derived from ICA , 2006 .
[14] Nurettin Acir,et al. Automatic spike detection in EEG by a two-stage procedure based on support vector machines , 2004, Comput. Biol. Medicine.
[15] Scott B. Wilson,et al. Spike detection: a review and comparison of algorithms , 2002, Clinical Neurophysiology.
[16] C Faure,et al. Attributed strings for recognition of epileptic transients in EEG. , 1985, International journal of bio-medical computing.
[17] S Makeig,et al. Spatially independent activity patterns in functional MRI data during the stroop color-naming task. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[18] H. Jasper,et al. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.
[19] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[20] P J Bones,et al. Wavelet Analysis of Transient Biomedical Signals and its Application to Detection of Epileptiform Activity in the EEG , 2000, Clinical EEG.
[21] D. Chakrabarti,et al. A fast fixed - point algorithm for independent component analysis , 1997 .
[22] Ronald G. Emerson,et al. Spike detection II: automatic, perception-based detection and clustering , 1999, Clinical Neurophysiology.
[23] J. Gotman,et al. Isolation of epileptiform discharges from unaveraged EEG by independent component analysis , 1999, Clinical Neurophysiology.
[24] J. Gotman,et al. Automatic recognition and quantification of interictal epileptic activity in the human scalp EEG. , 1976, Electroencephalography and clinical neurophysiology.
[25] Luis Diambra,et al. Nonlinear models for detecting epileptic spikes , 1999 .
[26] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[27] W R Webber,et al. Practical detection of epileptiform discharges (EDs) in the EEG using an artificial neural network: a comparison of raw and parameterized EEG data. , 1994, Electroencephalography and clinical neurophysiology.
[28] Piotr J. Franaszczuk,et al. An autoregressive method for the measurement of synchronization of interictal and ictal EEG signals , 1999, Biological Cybernetics.
[29] C D Binnie,et al. EEG in Clinical Practice, 2nd edn , 1995 .
[30] Erkki Oja,et al. Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic Recordings , 1997, NIPS.
[31] Scott B. Wilson,et al. Seizure detection: evaluation of the Reveal algorithm , 2004, Clinical Neurophysiology.
[32] P. Rossini,et al. Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals , 2004, Clinical Neurophysiology.
[33] S Makeig,et al. Analysis of fMRI data by blind separation into independent spatial components , 1998, Human brain mapping.
[34] O. Ozdamar,et al. Wavelet preprocessing for automated neural network detection of EEG spikes , 1995 .
[35] Aapo Hyvärinen,et al. Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.
[36] P Y Ktonas,et al. An automated system for epileptogenic focus localization in the electroencephalogram. , 1999, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[37] P. Rappelsberger. EEG informatics. A didactic review of methods and applications of EEG data processing , 1978 .
[38] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[39] R H Bayford,et al. Using the GRID to improve the computation speed of electrical impedance tomography (EIT) reconstruction algorithms. , 2005, Physiological measurement.
[40] Richard H. Bayford,et al. Applications of GRID in Clinical Neurophysiology and Electrical Impedance Tomography of Brain Function , 2005, HealthGrid.
[41] S. Baillet,et al. Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering , 2004, Clinical Neurophysiology.
[42] T J Sejnowski,et al. Learning the higher-order structure of a natural sound. , 1996, Network.
[43] Jean Gotman,et al. Systematic source estimation of spikes by a combination of independent component analysis and RAP-MUSIC II: Preliminary clinical application , 2002, Clinical Neurophysiology.