Classification of long-term EEG recordings

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3337, Issue , 2004, Pages 322-332

  Kosar, Karel ^a   Lhotska, Lenka ^a   Krajca, Vladimir ^b  

^a CZECH TECHNICAL UNIVERSITY IN PRAGUE   (Czech Republic)

^b UNIVERSITY HOSPITAL BULOVKA   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; NEAREST NEIGHBOR SEARCH; SIGNAL DETECTION;

ADAPTIVE SEGMENTATION; AUTOMATIC PROCESSING; AUTOMATIC SEARCHES; CHARACTERISTIC SHAPES; COMPUTER ASSISTED; DISCRIMINATIVE FEATURES; K-NEAREST NEIGHBOURS; LEARNING CLASSIFIERS;

BIOMEDICAL SIGNAL PROCESSING;

EID: 35048871126     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30547-7_33     Document Type: Article

References (16)

1. Davey B.L.K. et al., 1989, "Expert system approach to detection of epileptifoim activity in the EEG", Med. Biol. Eng. Comput. 27(4), pp. 365-370
2. Gotman J., 1982, "Automatic recognition of epileptic seizure in the EEG", Electroencephalogr. Clin. Neurophysiol. 83, pp. 271-280
3. Qu H.; Gotman J., 1993, "Improvement in seizure detection performance by automatic adaptation to the EEG of each patient", Electroencephalogr. Clin. Neurophysiol. 86, pp. 79-87
4. Mayer-Kress G., 1994, "Localized measures for nonstationary time-series of physiological data", Integrative Physiological Behav. Sci. 29 (3), pp. 205-210
5. Petrosian A.; Homan R.W.; Pemmaraju S.; Mitra S., 1995, "Wavet-based texture analysis of EEG signal for prediction of epileptic seizure", SPIE Proceedings on Wavelet Applications in Signal and Image Processing, Vol. 2569, San Diego, CA, pp. 189-194
6. Weng W.; Khorasani K., 1996, "An adaptive structure neural networks with application to EEG automatic seizure detection", Neural Networks 9(7), pp. 1223-1240
7. Homero R., Espino P., Alonso A., Lopez M.: Estimating Complexity from EEG Background Activity of Epileptic Patients. IEEE Engineering in Medicine and Biology, Nov./Dec. 1999, pp. 73-79
8. Smith S.W., 1997, "Digital Signal Processing", California Technical Publishing, San Diego, CA, USA
9. Bodenstein G.; Praetorius H.M., 1977, "Feature extraction from the electroencephalogram by adaptive segmentation", Proc. IEEE, 65, pp. 642-652
10. Krajca V.; Petranek S.; Ondruska V.; Doruzkova L; Pecharova D., 1992, "Multichannel adaptive segmentation - basis for EEG record pre-processing", Lekar a technika, 2,23, pp. 28-34 (in Czech)
11. Varri A. Digital Processing of the EEG in Epilepsy. Tampere University of Technology, 1988.
12. Krajca V., Petranek S., Patakova I., Varri A. Automatic identification of significant graphoelements in multichannel EEG recordings by adaptive segmentation and fuzzy clustering. Int. Journal Biomed. Comput., 1991, 28, pp. 71-89.
13. Agarwal R., Gotman J., Flanagan D., Rosenblan B. Automatic EEG analysis during longterm monitoring in the ICU. Electroencephalography and Clinical Neurophysiology. 1998, Vol. 107, Issue 1, pp. 44-58.
14. Plotkin E.I., Swamy M.N.S. Nonlinear signal processing based on parameter invariant moving average modeling. In Proceedings CCECE '21. September 1992, Toronto, Canada, pp.TM3.11.1-TM3.11.4.
15. Cover T.M., Hart P.E. Nearest neighbour pattern classification. IEEE Transaction Inform. Theory. January 1967, vol. IT-13, pp. 21-27.
16. Keller J. M., Gray M. R., Givens J. A. A Fuzzy K-Nearest Neighbor Algorithm. IEEE Transactions on systems, man. and cybernetics. July/August 1985, vol. SMC-15, no. 4, pp. 580-585.