Block term decomposition for modelling epileptic seizures

Tijdschrift voor Urologie

Volumn 2014, Issue 1, 2014, Pages 1-19

  Hunyadi, Borbála ^a,b   Camps, Daan ^a   Sorber, Laurent ^a,b   Paesschen, Wim Van ^c,d   Vos, Maarten De ^e   Huffel, Sabine Van ^a,b   Lathauwer, Lieven De ^a,b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b IMinds Medical IT   (Belgium)

^c UNIVERSITY HOSPITALS LEUVEN   (Belgium)

^d KU LEUVEN UNIVERSITY OF LEUVEN   (Belgium)

^e UNIVERSITY OF OLDENBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84919329838     PISSN: 22113037     EISSN: 22114718     Source Type: Journal    
DOI: 10.1186/1687-6180-2014-139     Document Type: Article

References (50)

1. De Boer HM, Mula M, Sander JW: The global burden and stigma of epilepsy.Epilepsy Behav 2008, 12:540–546. 10.1016/j.yebeh.2007.12.019
2. Panayiotopoulos CP: The Epilepsies: Seizures, Syndromes and Management. Bladon Medical Publishing, Oxfordshire; 2005.
3. Berg P, Scherg M: Dipole modelling of eye activity and its application to the removal of eye artefacts from the EEG and MEG.Clin. Phys. Physiol. Meas 1991, 12:49–54. 10.1088/0143-0815/12/A/010
4. Jung TP, Makeig S, Humphries C, Lee TW, McKeown MJ, Iragui V, Sejnowski TJ: Removing electroencephalographic artifacts by blind source separation.Psychophysiology 2000,37(2):163–178. 10.1016/S0167-8760(00)00088-X
5. Albera L, Kachenoura A, Comon P, Karfoul A, Wendling F, Senhadji L, Merlet I: ICA-based EEG denoising: a comparative analysis of fifteen methods.Data Mining Bioeng 2012,60(3):407–418.
6. Urrestarazu E, Iriarte J, Alegre M, Valencia M, Viteri C, Artieda J: Independent component analysis removing artifacts in ictal recordings.Epilepsia 2004,45(9):1071–1078. 10.1111/j.0013-9580.2004.12104.x
7. De Clercq W, Vergult A, Vanrumste B, Van Paesschen W, Van Huffel S: Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram.IEEE Trans. Biomed. Eng 2006,53(12):2583–2587.
8. Comon P: Independent component analysis, a new concept?Signal Process 1994,36(3):287–314. 10.1016/0165-1684(94)90029-9
9. Karfoul A, Kachenoura A, Albera L, Safieddine D, Paniscu A, Wendling F, Senhadji L, Merlet I: Muscle artifact removal in ictal scalp-EEG based on blind source separation. In MBEC 14, 6th European Conference of the International Federation for Medical and Biological Engineering. Dubrovnik, Croatia; 7–11 Sept 2014.
10. Hallez H, De Vos M, Vanrumste B, Van Hese P, Assecondi S, Van Laere K, Dupont P, Van Paesschen W, Van Huffel S, Lemahieu I: Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging.Clin. Neurophysiol 2009,120(7):1262–1272. 10.1016/j.clinph.2009.05.010
11. Acar E, Aykut-Bingol C, Bingol H, Bro R, Yener B: Multiway analysis of epilepsy tensors.Bioinformatics 2007,23(13):i10-i18. 10.1093/bioinformatics/btm210
12. Nam H, Yim TG, SK Han JBOh, Lee SK: Independent component analysis of ictal EEG in medial temporal lobe epilepsy.Epilepsia 2002,43(2):160–164. 10.1046/j.1528-1157.2002.23501.x
13. De Vos M, Vergult A, De Lathauwer L, De Clercq W, Van Huffel S, Dupont P, Palmini A, Van Paesschen W: Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone.NeuroImage 2007, 37:844–854. 10.1016/j.neuroimage.2007.04.041
14. De Vos M, De Lathauwer L, Vanrumste B, Van Huffel S, Van Paesschen W: Canonical decomposition of ictal scalp EEG and accurate source localisation: principles and simulation study.Intell. Neurosc 2007, 2007:11:1–11:8.
15. Becker H, Albera L, Comon P, Haardt M, Birot G, Wendling F, Gavaret M, Bénar C, Merlet I: {EEG} extended source localization: tensor-based vs.conventional methods.NeuroImage 2014,96(0):143–157.
16. Hesse C, James C: Tracking and detection of epileptiform activity in multichannel ictal EEG using signal subspace correlation of seizure source scalp topographies.Med. Biol. Eng. Comput 2007,45(10):909–916. 10.1007/s11517-006-0103-8
17. Martínez-Montes E, Márquez-Bocalandro Y, Lage-Castellanos A: EEG pattern recognition by multidimensional space-time-frequency analysis. In V Latin American Congress on Biomedical Engineering CLAIB 2011, May 16–21, 2011, Habana, Cuba, Volume 33 of IFMBE Proceedings. Springer, Berlin; 2013:1150–1153.
18. Kocyigit Y, Alkan A, Erol H: Classification of EEG recordings by using fast independent component analysis and artificial neural network.J. Med. Syst 2008, 32:17–20. 10.1007/s10916-007-9102-z
19. Subasi A, Gursoy MI: EEG signal classification using PCA, ICA, LDA and support vector machines.Expert Syst. Appl 2010,37(12):8659–8666. 10.1016/j.eswa.2010.06.065
20. Stern J, Engel J: An Atlas of EEG Patterns. Lippincott; 2004.
21. De Lathauwer L: Decompositions of a higher-order tensor in block terms - part I: lemmas for partitioned matrices.Siam J. Matrix Anal. Appl 2008,30(3):1022–1033. 10.1137/060661685
22. De Lathauwer L: Decompositions of a higher-order tensor in block terms - part II: definitions and uniqueness.Siam J. Matrix Anal. Appl 2008,30(3):1033–1066. 10.1137/070690729
23. Hunyadi B, Signoretto M, Debener S, Van Huffel S, De Vos M: Classification of structured EEG tensors using nuclear norm regularization: improving P300 classification. In International Workshop on Pattern Recognition in Neuroimaging (PRNI). Philadelphia, USA; 22–24 June 2013:98–101.
24. De Clercq W, Vanrumste B, Papy JM, Van Paesschen W, Van Huffel S: Modeling common dynamics in multichannel signals with applications to artifact and background removal in EEG recordings.IEEE Trans. Biomed. Eng 2005,52(12):2006–2015.
25. Franaszczuk P, Blinowska K: Linear model of brain electrical activity - EEG as a superposition of damped oscillatory modes.Biol. Cybern 1985, 53:19–25. 10.1007/BF00355687
26. Kung SY, Arun KS: DV Bhaskar Rao, State-space and singular-value decomposition-based approximation methods for the harmonic retrieval problem.J. Opt. Soc. Am 1983,73(12):1799–1811. 10.1364/JOSA.73.001799
27. r, 1) terms.Siam J. Matrix Anal. Appl 2011,32(4):1451–1474. 10.1137/100805510
28. Kruskal JB: Three-way arrays: rank and uniqueness of trilinear decompositions, with applications to arithmetic complexity and statistics.Psychometrika 1977, 18:95–138.
29. Domanov I, De Lathauwer L: On the uniqueness of the canonical polyadic decomposition-part I: basic results and uniqueness of one factor matrix.SIAM J. Matrix Anal. Appl 2013,34(3):855–875. 10.1137/120877234
30. Domanov I, De Lathauwer L: On the uniqueness of the canonical polyadic decomposition—part II: overall uniqueness.SIAM J. Matrix Anal. Appl 2013,34(3):876–903. 10.1137/120877258
31. Carroll JD, Chang JJ: Analysis of individual differences in multidimensional scaling via ann-way generalization of “Eckart-Young” decomposition.Psychometrika 1970,35(3):283–319. 10.1007/BF02310791
32. r, 1) terms and a new generalization.SIAM Journal on Optimization 2013,23(2):695–720. 10.1137/120868323
33. Sorber L, Van Barel M, De Lathauwer L: Tensorlab v2.0.http://www.tensorlab.net (2014) Accessed 1 Sept 2014
34. Mørup M, Hansen L, Hermann C, Parnas J, Arnfred SM: Parallel factor analysis as an exploratory tool for wavelet transformed event-related EEG.NeuroImage 2006,29(3):938–947. 10.1016/j.neuroimage.2005.08.005
35. Miwakeichi F, Martínez-Montes E, Valdés-Sosa PA, Nishiyama N, Mizuhara H, Yamaguchi Y: Decomposing {EEG} data into space-time-frequency components using parallel factor analysis.NeuroImage 2004,22(3):1035–1045. 10.1016/j.neuroimage.2004.03.039
36. Van Huffel S, Chen H, Decanniere C, Vanhecke P: Algorithm for time-domain NMR data fitting based on total least squares.J. Magn. Reson. A 1994,110(2):228–237. 10.1006/jmra.1994.1209
37. Bro R, Kiers HAL: A new efficient method for determining the number of components in PARAFAC models.J. Chemometrics 2003,17(5):274–286. 10.1002/cem.801
38. Mørup M, Hansen L: Automatic relevance determination for multi-way models.J. Chemometrics 2009,23(7–8):352–363.
39. Salu Y, Cohen L, Rose D, Sxato S, Kufta C, Hallett M: An improved method for localizing electric brain dipoles.IEEE Trans. Biomed. Eng 1990,37(7):699–705. 10.1109/10.55680
40. Oostendorp T, Delbeke J, Stegeman DF: The conductivity of the human skull: results of in vivo and in vitro measurements.IEEE Trans. Biomed. Eng 2000,47(11):1487–92. 10.1109/TBME.2000.880100
41. Cuffin BN, Cohen D, Yunokuchi K, Maniewski R, Purcell C, Cosgrove GR, Ives J, Kennedy J, Schomer D: Tests of EEG localization accuracy using implanted sources in the human brain.Ann. Neurol 1991,29(2):132–138. 10.1002/ana.410290204
42. Vergult A, De Clercq W, Palmini A, Vanrumste B, Dupont P, Van Huffel S, Van Paesschen W: Improving the interpretation of ictal scalp EEG: BSS-CCA algorithm for muscle artifact removal.Epilepsia 2007,48(5):950–958. 10.1111/j.1528-1167.2007.01031.x
43. Timmerman ME, Kiers HAL: Three-mode principal components analysis: choosing the numbers of components and sensitivity to local optima.Br. J. Math. Stat. Psychol 2000, 53:1–16. 10.1348/000711000159132
44. Kiers HAL: A der Kinderen, A fast method for choosing the numbers of components in Tucker3 analysis.Br. J. Math. Stat. Psychol 2003, 56:119–125. 10.1348/000711003321645386
45. Castellanos J, Gómez S, Guerra V: The triangle method for finding the corner of the L-curve.Appl. Numer. Math 2002,43(4):359–373. 10.1016/S0168-9274(01)00179-9
46. Tibshirani R, Walther G, Hastie T: Estimating the number of clusters in a data set via the gap statistic.J. Roy. Stat. Soc. B Stat. Meth 2001,63(2):411–423. 10.1111/1467-9868.00293
47. Kompany-Zareh M, Y Akhlaghi Y, Bro R: Tucker core consistency for validation of restricted Tucker3 models.Anal. Chim. Acta 2012,723(0):18–26.
48. Lee H, Kim YD, Cichocki A, Choi S: Nonnegative tensor factorization for continuous EEG classification.Int. J. Neural Syst 2007,17(04):305–317. 10.1142/S0129065707001159
49. Li J, Zhang L, Zhao Q: Pattern classification of visual evoked potentials based on parallel factor analysis. In Advances in Cognitive Neurodynamics ICCN 2007. Edited by: Wang R, Shen E, Gu F. Springer, Netherlands; 2008:571–575.
50. Vanderperren K, Mijović B, Novitskiy N, Vanrumste B, Stiers P, Van den Bergh B, Lagae L, Sunaert S, Wagemans J, Van Huffel S, De Vos M: Single trial ERP reading based on parallel factor analysis.Psychophysiology 2013,50(1):97–110. 10.1111/j.1469-8986.2012.01405.x