Detection of EEG transients in neonates and older children using a system based on dynamic time-warping template matching and spatial dipole clustering

NeuroImage

Volumn 48, Issue 1, 2009, Pages 50-62

  Aarabi, Ardalan ^a,b   Kazemi, Kamran ^c   Grebe, Reinhard ^b   Moghaddam, Hamid Abrishami ^d   Wallois, Fabrice ^b  

^a AMIENS UNIVERSITY HOSPITAL   (France)

^b UNIVERSITÉ DE PICARDIE JULES VERNE   (France)

^c SHIRAZ UNIVERSITY OF TECHNOLOGY   (Iran)

^d K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Children; EEG; Event; Event detection; Neonates; Sharp wave; Source localization; Spatial clustering; Spike

Indexed keywords

ADOLESCENT; ARTICLE; ARTIFACT; BRAIN DISEASE; CHILD; CLINICAL ARTICLE; CONTROLLED STUDY; DIPOLE; ELECTROENCEPHALOGRAPHY; EPILEPSY; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE RECONSTRUCTION; MEDICAL ASSESSMENT; NEWBORN; PRESCHOOL CHILD; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SCHOOL CHILD; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; SPIKE WAVE; TIME;

ADOLESCENT; AGING; BRAIN; BRAIN MAPPING; CHILD; CHILD, PRESCHOOL; CLUSTER ANALYSIS; ELECTROENCEPHALOGRAPHY; HUMANS; INFANT; MAGNETIC RESONANCE IMAGING; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 67949091007     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2009.06.057     Document Type: Article

References (54)

1. Aso K., Scher M.S., and Barmada M.A. Neonatal electroencephalography and neuropathology. J. Clin. Neurophysiol. 6 (1989) 103-123
2. Acir N., Oztura I., Kuntalp M., Baklan B., and Guzelis C. Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. IEEE Trans. Biomed. Eng. 52 (2005) 30-40
3. Awada K.A., Jackson D.R., Baumann S.B., Williams J.T., Wilton D.R., Fink P.W., and Prasky B.R. Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Trans. Biomed. Eng. 45 (1998) 1135-1145
4. Bankman I.N., Johnson K.O., and Schneider W. Optimal detection, classification, and superposition resolution in neural waveform recordings. IEEE Trans. Biomed. Eng. 40 (1993) 836-841
5. Calinski R., and Harabasz J. A dendrite method for cluster analysis. Commun. Stat. 3 (1974) 1-27
6. Capowski J.J. The spike program: a computer system for analysis of neurophysiological action potentials. In: Brown P. (Ed). Computer Technology in Neuroscience (1976), Hemisphere, Washington DC 237-251
7. Cooper R., Winter A.L., Crow H.J., and Walter W.G. Comparison of subcortical, cortical and scalp activity using chronically indwelling electrodes in man. Electroencephalogr. Clin. Neurophysiol. 18 (1965) 217-228
8. Dingle A.A., Jones R.D., Carroll G.J., and Fright W.R. A multistage system to detect epileptiform activity in the EEG. IEEE Trans. Biomed. Eng. 40 (1993) 1260-1268
9. Dunn J.C. Well separated clusters and optimal fuzzy partitions. J. Cybern. 4 (1974) 95-104
10. Ebersole J.S. Defining epileptogenic foci: past, present, future. J. Clin. Neurophysiol. 14 (1997) 470-483
11. Edwards, A.L., 1976. The Correlation Coefficient. Ch. 4 in An Introduction to Linear Regression and Correlation. San Francisco, CA: W. H. Freeman, pp. 33-46.
12. Flanagan D., Agarwal R., and Gotman J. Computer-aided spatial classification of epileptic spikes. J. Clin. Neurophysiol. 19 (2002) 125-135
13. Gabor A.J., and Seyal M. Automated interictal EEG spike detection using artificial neural networks. Electroenceph. clin. Neurophysiol. 83 (1992) 271-280
14. Glover R., Raghavan N., Ktonas P.Y., and Frost J.D. Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives. IEEE Trans. Biomed. Eng. 36 (1989) 519-527
15. Gotman J. Automatic detection of seizures and spikes. J. Clin. Neurophysiol. 16 (1999) 130-140
16. Gotman J., and Gloor P. Automatic recognition and quantification of interictal epileptic activity in the human scalp EEG. Electroenceph. Clin. Neurophysiol. 41 (1976) 513-529
17. Gotman J., and Wang L.Y. State-dependent spike detection: concepts and preliminary results. Electroenceph. Clin. Neurophysiol. 79 (1991) 11-19
18. Grieve P.G., Emerson R.G., Isler J.R., and Stark R.I. Quantitative analysis of spatial sampling error in the infant and adult electroencephalogram. NeuroImage 21 (2004) 1260-1274
19. Hamalainen M.S., and Sarvas J. Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data. IEEE Trans. Biomed. Eng. 36 (1989) 165-171
20. Hartigan J.A. Statistical theory in clustering. J. Classification. 2 (1985) 63-76
21. Hellmann G. Multifold features determine linear equation for automatic spike detection applying neural nin interictal EcoG. Clin. Neurophysiol. 110 (1999) 887-894
22. IFSECN. A glossary of terms most commonly used by clinical electroencephalographers. Electroenceph. Clin. Neurophysiol. 37 (1974) 538-548
23. James C.J., Jones R.D., Bones P.J., and Carroll G.J. Detection of epileptiform discharges in the EEG by a hybrid system comprising mimetic, self-organized artificial neural network, and fuzzy logic stages. Clin. Neurophysiol. 110 (1999) 2049-2063
24. Kazemi K., Grebe R., Abrishami Moghaddam H., Lagadec P., Gondry-Jouet C., Wallois F. (2007): "Design of a Digital Phantom of the Neonatal Brain", Proceeding of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBS) 5509-5512.
25. Khan Y.U., and Gotman J. Wavelet based automatic seizure detection in intracerebral electroencephalogram. Clin. Neurophysiol. 114 (2003) 898-908
26. Ko C.W., and Chung H.W. Automatic spike detection via an artificial neural network using raw EEG data: effects of data preparation and implications in the limitations of online recognition. Clin. Neurophysiol. 111 (2000) 477-481
27. Ktonas P.Y., and Smith J.R. Quantification of abnormal EEG spike characteristics. Comput. Biol. Med. 4 (1974) 157-163
28. Lamblin M.D., Andre M., Challamel M.J., Curzi-Dascalova L., d'Allest A.M., De Giovanni E., Moussalli-Salefranque F., Navelet Y., Plouin P., Radvanyi-Bouvet M.F., Samson-Dollfus D., and Vecchierini-Blineau M.F. Electroencephalography of the premature and term newborn. Maturational aspects and glossary. Neurophysiol. Clin. 29 (1999) 123-219
29. Lantz G., Grave de Peralta R., Spinelli L., Seeck M., and Michel C.M. Epileptic source localization with high density EEG: how many electrodes are needed?. Clin. Neurophysiol. 114 (2003) 63-69
30. Law S.K., Nenez P.L., and Wijesinghe R.S. High resolution EEG using spline generated surface Laplacians on spherical and ellipsoildal surfaces. IEEE Trans. Biomed. Eng. 40 (1993) 145-152
31. Lombroso C.T. Neonatal polygraphy in full-term and premature infants: a review of normal and abnormal findings. J. Clin. Neurophysiol. 2 (1985) 105-155
32. MacQueen J.B. Some Methods for Classification and Analysis of Multivariate Observations, Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability 1 (1967), University of California Press, Berkeley 281-297
33. Mardia K.V., Kent J.T., and Bibby J.M. Multivariate Analysis (1979), Academic Press, San Diego
34. Myers C.S., and Rabiner L.R. A comparative study of several dynamic time-warping algorithms for connected word recognition. Bell Syst. Tech. J. 60 7 (1981) 1389-1409
35. Michel C.M., Murray M.M., Lantz G., Gonzalez S., Spinelli L., and Grave de Peralta R. EEG source imaging. Clin. Neurophysiol. 115 (2004) 2195-2222
36. Millecchia R., and McIntyre R. Automatic nerve impulse identification and separation. Comput. Biomed. Res. 11 (1978) 459-468
37. Motulsky H.J. (1999): Analyzing data with GraphPad Prism. From http://www.graphpad.com/articles/interpret/Analyzing_two_groups/wilcoxon_matched_pairs.htm.
38. Ossadtchi A., Baillet S., Mosher J.C., Thyerlei D., Sutherling W., and Leahy R.M. Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering. Clin. Neurophysiol. 115 (2004) 508-522
39. Pohlmeier R., Buchner H., Knoll G., Rienacker A., Beckmann R., and Pesch J. The influence of skull-conductivity misspecification on inverse source localization in realistically shaped finite element head models. Brain Topogr. 9 (1997) 157-162
40. Roche-Labarbe N., Aarabi A., Kongolo G., Gondry-Jouet C., Dümpelmann M., Grebe R., and Wallois F. High resolution EEG and source localization in neonates. Hum. Brain Mapp. 29 2 (2008) 167-176
41. Ryynanen O.R., Hyttinen J.A., and Malmivuo J.A. Effect of measurement noise and electrode density on the spatial resolution of cortical potential distribution with different resistivity values for the skull. IEEE Trans. Biomed. Eng. 53 (2006) 1851-1858
42. Scherg M. Fundamentals of dipole source potential analysis. In: Grandori F., Hoke M., and Romani G.L. (Eds). Auditory Evoked Electric and Magnetic Fields (Advances in Audiology 6) (1990), Karger, Basel 40-69
43. Sorgi L., Kostas D. (2004): Normalized Cross-Correlation for Spherical Images. Springer Berlin Heidelberg Computer Vision - ECCV 3022.
44. Tarassenko L., Khan Y.U., and Holt M.R.G. Identification of inter-ictal spikes in the EEG using neural network analysis. Inst. Elect. Eng. Proc. Sci. Meas. Technol. 145 (1998) 270-278
45. Tibshirani R., Walther G., Hastie T. (2000): Estimating the number of clusters in a dataset via the gap statistic. Dept of Statistics, Stanford University, Technical Report 208.
46. Van Hese P., Vanrumste B., Hallez H., Carroll G.J., Vonck K., Jones R.D., Bones P.J., D'Asseler Y., and Lemahieu I. Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering. Clin. Neurophysiol. 119 8 (2008) 1756-1770
47. Vanrumste B., Van Hoey G., Van de Walle R., D'Have M., Lemahieu I., and Boon P. Dipole location errors in electroencephalogram source analysis due to volume conductor model errors. Med. Biol. Eng. Comput. 38 (2000) 528-534
48. Vaughan H.G. The analysis of scalp-recorded brain potentials. Bioelectric Recording Techniques (1974), Academic Press, New York
49. Walter D.O., Muller H.F., and Jell R.M. Semiautomatic quantification of sharpness of EEG phenomenon. IEEE Trans. Biomed. Eng. 20 (1973) 53-54
50. Webber W.R.S., Litt B., Lesser R.P., Fisher R.S., and Bankman I. Automatic EEG spike detection: what should be computer imitate?. Electroenceph. Clin. Neurophys. 87 (1993) 364-373
51. Weber R., Litt B., Wilson K., and Lesser R. Practical detection of epileptiform discharges (Eds) in the EEG using an artificial neural network: a comparison of raw and parameterized EEG data. Electroenceph. Clin. Neurophysiol. 91 (1994) 194-204
52. Wilson S., and Emerson R. Event detection: a review and comparison of algorithms. Clin. Neurophisiol. 113 (2002) 1873-1883
53. Wilson S.B., Turner C.A., Emerson R.G., and Scheuer M.L. Spike detection. Clin. Neurophysiol. 110 (1999) 404-411
54. Zanow F., and Knoesche T.R. SA - advanced source analysis of continuous and event-related EEG/MEG signals. Brain Topogr. 16 4 (2004) 287-290