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Volumn 36, Issue 3 PART 2, 2009, Pages 6780-6789

Features for analysis of electrocardiographic changes in partial epileptic patients

Author keywords

Eigenvector methods; Electrocardiogram (ECG) signals; Lyapunov exponents; Modified mixture of experts; Partial epilepsy; Post ictal heart rate oscillations; Wavelet coefficients

Indexed keywords

DIFFERENTIAL EQUATIONS; EIGENVALUES AND EIGENFUNCTIONS; ELECTROCARDIOGRAPHY; HEART; LYAPUNOV FUNCTIONS; LYAPUNOV METHODS; MIXTURES; NEUROLOGY; POWER SPECTRAL DENSITY; SPECTRAL DENSITY; WAVELET TRANSFORMS;

EID: 58349087622     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.08.009     Document Type: Article
Times cited : (8)

References (38)
  • 1
    • 0001731208 scopus 로고
    • Lyapunov exponents in chaotic systems: Their importance and their evaluation using observed data
    • Abarbanel H.D.I., Brown R., and Kennel M.B. Lyapunov exponents in chaotic systems: Their importance and their evaluation using observed data. International Journal of Modern Physics B 5 9 (1991) 1347-1375
    • (1991) International Journal of Modern Physics B , vol.5 , Issue.9 , pp. 1347-1375
    • Abarbanel, H.D.I.1    Brown, R.2    Kennel, M.B.3
  • 3
    • 33644765907 scopus 로고    scopus 로고
    • A support vector machine classifier algorithm based on a perturbation method and its application to ECG beat recognition systems
    • Aci{dotless}r N. A support vector machine classifier algorithm based on a perturbation method and its application to ECG beat recognition systems. Expert Systems with Applications 31 (2006) 150-158
    • (2006) Expert Systems with Applications , vol.31 , pp. 150-158
    • Acir, N.1
  • 7
    • 0018989294 scopus 로고
    • Lyapunov characteristic exponents for smooth dynamical systems and for Hamiltonian systems; a method for computing all of them
    • Benettin G., Galgani L., Giorgilli A., and Strelcyn J.-M. Lyapunov characteristic exponents for smooth dynamical systems and for Hamiltonian systems; a method for computing all of them. Meccanica 15 1 (1980) 9-30
    • (1980) Meccanica , vol.15 , Issue.1 , pp. 9-30
    • Benettin, G.1    Galgani, L.2    Giorgilli, A.3    Strelcyn, J.-M.4
  • 8
    • 0031257121 scopus 로고    scopus 로고
    • Estimation of Lyapunov exponents of ECG time series - The influence of parameters
    • Casaleggio A., and Braiotta S. Estimation of Lyapunov exponents of ECG time series - The influence of parameters. Chaos, Solitons and Fractals 8 10 (1997) 1591-1599
    • (1997) Chaos, Solitons and Fractals , vol.8 , Issue.10 , pp. 1591-1599
    • Casaleggio, A.1    Braiotta, S.2
  • 9
    • 45149144372 scopus 로고
    • Nonlinear prediction of chaotic time series
    • Casdagli M. Nonlinear prediction of chaotic time series. Physica D 35 3 (1989) 335-356
    • (1989) Physica D , vol.35 , Issue.3 , pp. 335-356
    • Casdagli, M.1
  • 10
    • 0032066455 scopus 로고    scopus 로고
    • A connectionist method for pattern classification with diverse features
    • Chen K. A connectionist method for pattern classification with diverse features. Pattern Recognition Letters 19 7 (1998) 545-558
    • (1998) Pattern Recognition Letters , vol.19 , Issue.7 , pp. 545-558
    • Chen, K.1
  • 11
    • 0032876594 scopus 로고    scopus 로고
    • Improved learning algorithms for mixture of experts in multiclass classification
    • Chen K., Xu L., and Chi H. Improved learning algorithms for mixture of experts in multiclass classification. Neural Networks 12 9 (1999) 1229-1252
    • (1999) Neural Networks , vol.12 , Issue.9 , pp. 1229-1252
    • Chen, K.1    Xu, L.2    Chi, H.3
  • 12
    • 0025482241 scopus 로고
    • The wavelet transform, time-frequency localization and signal analysis
    • Daubechies I. The wavelet transform, time-frequency localization and signal analysis. IEEE Transactions on Information Theory 36 5 (1990) 961-1005
    • (1990) IEEE Transactions on Information Theory , vol.36 , Issue.5 , pp. 961-1005
    • Daubechies, I.1
  • 14
    • 0034201185 scopus 로고    scopus 로고
    • Nonlinear analysis of continuous ECG during sleep II. Dynamical measures
    • Fell J., Mann K., Röschke J., and Gopinathan M.S. Nonlinear analysis of continuous ECG during sleep II. Dynamical measures. Biological Cybernetics 82 (2000) 485-491
    • (2000) Biological Cybernetics , vol.82 , pp. 485-491
    • Fell, J.1    Mann, K.2    Röschke, J.3    Gopinathan, M.S.4
  • 16
    • 0000670820 scopus 로고    scopus 로고
    • On the evidence of deterministic chaos in ECG: Surrogate and predictability analysis
    • Govindan R.B., Narayanan K., and Gopinathan M.S. On the evidence of deterministic chaos in ECG: Surrogate and predictability analysis. Chaos 8 2 (1998) 495-502
    • (1998) Chaos , vol.8 , Issue.2 , pp. 495-502
    • Govindan, R.B.1    Narayanan, K.2    Gopinathan, M.S.3
  • 17
    • 33745184412 scopus 로고    scopus 로고
    • An expert system for detection of electrocardiographic changes in patients with partial epilepsy using wavelet-based neural networks
    • Güler I., and Übeyli E.D. An expert system for detection of electrocardiographic changes in patients with partial epilepsy using wavelet-based neural networks. Expert Systems 22 2 (2005) 62-71
    • (2005) Expert Systems , vol.22 , Issue.2 , pp. 62-71
    • Güler, I.1    Übeyli, E.D.2
  • 18
    • 0029191714 scopus 로고
    • Detection of signals in chaos
    • Haykin S., and Li X.B. Detection of signals in chaos. Proceedings of the IEEE 83 1 (1995) 95-122
    • (1995) Proceedings of the IEEE , vol.83 , Issue.1 , pp. 95-122
    • Haykin, S.1    Li, X.B.2
  • 19
    • 0036170354 scopus 로고    scopus 로고
    • A mixture of experts network structure construction algorithm for modelling and control
    • Hong X., and Harris C.J. A mixture of experts network structure construction algorithm for modelling and control. Applied Intelligence 16 1 (2002) 59-69
    • (2002) Applied Intelligence , vol.16 , Issue.1 , pp. 59-69
    • Hong, X.1    Harris, C.J.2
  • 21
    • 0000262562 scopus 로고
    • Hierarchical mixture of experts and the EM algorithm
    • Jordan M.I., and Jacobs R.A. Hierarchical mixture of experts and the EM algorithm. Neural Computation 6 2 (1994) 181-214
    • (1994) Neural Computation , vol.6 , Issue.2 , pp. 181-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 23
    • 34547901071 scopus 로고    scopus 로고
    • Development of entropy based algorithm for cardiac beat detection in 12-lead electrocardiogram
    • Mehta S.S., and Lingayat N.S. Development of entropy based algorithm for cardiac beat detection in 12-lead electrocardiogram. Signal Processing 87 (2007) 3190-3201
    • (2007) Signal Processing , vol.87 , pp. 3190-3201
    • Mehta, S.S.1    Lingayat, N.S.2
  • 24
    • 58349112024 scopus 로고    scopus 로고
    • MIT-BIH Database (2003). Available from Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room E25-505A, Cambridge, MA 02139, USA.
    • MIT-BIH Database (2003). Available from Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room E25-505A, Cambridge, MA 02139, USA.
  • 25
    • 1642265037 scopus 로고    scopus 로고
    • Support vector machine-based expert system for reliable heartbeat recognition
    • Osowski S., Hoai L.T., and Markiewicz T. Support vector machine-based expert system for reliable heartbeat recognition. IEEE Transactions on Biomedical Engineering 51 4 (2004) 582-589
    • (2004) IEEE Transactions on Biomedical Engineering , vol.51 , Issue.4 , pp. 582-589
    • Osowski, S.1    Hoai, L.T.2    Markiewicz, T.3
  • 26
    • 0036083108 scopus 로고    scopus 로고
    • Study of features based on nonlinear dynamical modeling in ECG arrhytmia detection and classification
    • Owis M.I., Abou-Zied A.H., Youssef A.-B.M., and Kadah Y.M. Study of features based on nonlinear dynamical modeling in ECG arrhytmia detection and classification. IEEE Transactions on Biomedical Engineering 49 7 (2002) 733-736
    • (2002) IEEE Transactions on Biomedical Engineering , vol.49 , Issue.7 , pp. 733-736
    • Owis, M.I.1    Abou-Zied, A.H.2    Youssef, A.-B.M.3    Kadah, Y.M.4
  • 28
    • 0037318986 scopus 로고    scopus 로고
    • Cardiac asystole in epilepsy: Clinical and neurophysiologic features
    • Rocamora R., Kurthen M., Lickfett L., von Oertzen J., and Elger C.E. Cardiac asystole in epilepsy: Clinical and neurophysiologic features. Epilepsia 44 2 (2003) 179-185
    • (2003) Epilepsia , vol.44 , Issue.2 , pp. 179-185
    • Rocamora, R.1    Kurthen, M.2    Lickfett, L.3    von Oertzen, J.4    Elger, C.E.5
  • 29
    • 0001394076 scopus 로고
    • Measurement of the Lyapunov spectrum from a chaotic time series
    • Sano M., and Sawada Y. Measurement of the Lyapunov spectrum from a chaotic time series. Physical Review Letters 55 10 (1985) 1082-1085
    • (1985) Physical Review Letters , vol.55 , Issue.10 , pp. 1082-1085
    • Sano, M.1    Sawada, Y.2
  • 30
    • 0037145626 scopus 로고    scopus 로고
    • Feature extraction from ECG signals using wavelet transforms for disease diagnostics
    • Saxena S.C., Kumar V., and Hamde S.T. Feature extraction from ECG signals using wavelet transforms for disease diagnostics. International Journal of Systems Science 33 13 (2002) 1073-1085
    • (2002) International Journal of Systems Science , vol.33 , Issue.13 , pp. 1073-1085
    • Saxena, S.C.1    Kumar, V.2    Hamde, S.T.3
  • 32
    • 34047269242 scopus 로고    scopus 로고
    • ECG beats classification using multiclass support vector machines with error correcting output codes
    • Übeyli E.D. ECG beats classification using multiclass support vector machines with error correcting output codes. Digital Signal Processing 17 3 (2007) 675-684
    • (2007) Digital Signal Processing , vol.17 , Issue.3 , pp. 675-684
    • Übeyli, E.D.1
  • 33
    • 37349024109 scopus 로고    scopus 로고
    • Wavelet/mixture of experts network structure for EEG signals classification
    • Übeyli E.D. Wavelet/mixture of experts network structure for EEG signals classification. Expert Systems with Applications 34 3 (2008) 1954-1962
    • (2008) Expert Systems with Applications , vol.34 , Issue.3 , pp. 1954-1962
    • Übeyli, E.D.1
  • 34
    • 37049007663 scopus 로고    scopus 로고
    • Analysis of EEG signals by combining eigenvector methods and multiclass support vector machines
    • Übeyli E.D. Analysis of EEG signals by combining eigenvector methods and multiclass support vector machines. Computers in Biology and Medicine 38 1 (2008) 14-22
    • (2008) Computers in Biology and Medicine , vol.38 , Issue.1 , pp. 14-22
    • Übeyli, E.D.1
  • 35
    • 5444236357 scopus 로고    scopus 로고
    • Detection of electrocardiographic changes in partial epileptic patients using Lyapunov exponents with multilayer perceptron neural networks
    • Übeyli E.D., and Güler I. Detection of electrocardiographic changes in partial epileptic patients using Lyapunov exponents with multilayer perceptron neural networks. Engineering Applications of Artificial Intelligence 17 6 (2004) 567-576
    • (2004) Engineering Applications of Artificial Intelligence , vol.17 , Issue.6 , pp. 567-576
    • Übeyli, E.D.1    Güler, I.2
  • 36
    • 0008494528 scopus 로고
    • Determining Lyapunov exponents from a time series
    • Wolf A., Swift J.B., Swinney H.L., and Vastano J.A. Determining Lyapunov exponents from a time series. Physica D 16 3 (1985) 285-317
    • (1985) Physica D , vol.16 , Issue.3 , pp. 285-317
    • Wolf, A.1    Swift, J.B.2    Swinney, H.L.3    Vastano, J.A.4
  • 38
    • 0036337999 scopus 로고    scopus 로고
    • Heart rate changes and ECG abnormalities during epileptic seizures: Prevalence and definition of an objective clinical sign
    • Zijlmans M., Flanagan D., and Gotman J. Heart rate changes and ECG abnormalities during epileptic seizures: Prevalence and definition of an objective clinical sign. Epilepsia 43 8 (2002) 847-854
    • (2002) Epilepsia , vol.43 , Issue.8 , pp. 847-854
    • Zijlmans, M.1    Flanagan, D.2    Gotman, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.