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Volumn 9, Issue 1, 2014, Pages 1-5

Classification of ictal and seizure-free EEG signals using fractional linear prediction

Author keywords

Electroencephalogram (EEG) signal; Epileptic seizure classification; Fractional linear prediction (FLP); Support vector machine (SVM)

Indexed keywords

CALCULATIONS; ELECTROENCEPHALOGRAPHY; FORECASTING; SUPPORT VECTOR MACHINES;

EID: 84886528449     PISSN: 17468094     EISSN: 17468108     Source Type: Journal    
DOI: 10.1016/j.bspc.2013.08.006     Document Type: Article
Times cited : (249)

References (33)
  • 2
    • 77951208271 scopus 로고    scopus 로고
    • Epileptic EEG detection using the linear prediction error energy
    • S. Altunay, Z. Telatar, and O. Erogul Epileptic EEG detection using the linear prediction error energy Expert Systems with Applications 37 August (8) 2010 5661 5665
    • (2010) Expert Systems with Applications , vol.37 , Issue.AUGUST 8 , pp. 5661-5665
    • Altunay, S.1    Telatar, Z.2    Erogul, O.3
  • 4
    • 24044474732 scopus 로고    scopus 로고
    • Artificial neural network based epileptic detection using time-domain and frequency-domain features
    • DOI 10.1007/s10916-005-6133-1
    • V. Srinivasan, C. Eswaran, and N. Sriraam Artificial neural network based epileptic detection using time-domain and frequency-domain features Journal of Medical Systems 29 December (6) 2005 647 660 (Pubitemid 41225146)
    • (2005) Journal of Medical Systems , vol.29 , Issue.6 , pp. 647-660
    • Srinivasan, V.1    Eswaran, C.2    Sriraam, A.N.3
  • 5
    • 34247217946 scopus 로고    scopus 로고
    • Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform
    • DOI 10.1016/j.amc.2006.09.022, PII S0096300306012380
    • K. Polat, and S. Güneş Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform Applied Mathematics and Computation 187 April (2) 2007 1017 1026 (Pubitemid 46627890)
    • (2007) Applied Mathematics and Computation , vol.187 , Issue.2 , pp. 1017-1026
    • Polat, K.1    Gunes, S.2
  • 7
    • 35248825924 scopus 로고    scopus 로고
    • EEG signal analysis using FB expansion and second-order linear TVAR process
    • DOI 10.1016/j.sigpro.2007.07.022, PII S0165168407002708
    • R.B. Pachori, and P. Sircar EEG signal analysis using FB expansion and second-order linear TVAR process Signal Processing 88 February (2) 2008 415 420 (Pubitemid 47562112)
    • (2008) Signal Processing , vol.88 , Issue.2 , pp. 415-420
    • Pachori, R.B.1    Sircar, P.2
  • 8
    • 0037441741 scopus 로고    scopus 로고
    • Analysis of EEG records in an epileptic patient using wavelet transform
    • DOI 10.1016/S0165-0270(02)00340-0, PII S0165027002003400
    • H. Adeli, Z. Zhou, and N. Dadmehr Analysis of EEG records in an epileptic patient using wavelet transform Journal of Neuroscience Methods 123 February (1) 2003 69 87 (Pubitemid 36173654)
    • (2003) Journal of Neuroscience Methods , vol.123 , Issue.1 , pp. 69-87
    • Adeli, H.1    Zhou, Z.2    Dadmehr, N.3
  • 9
    • 0038398958 scopus 로고    scopus 로고
    • Wavelet based automatic seizure detection in intracerebral electroencephalogram
    • DOI 10.1016/S1388-2457(03)00035-X
    • Y.U. Khan, and J. Gotman Wavelet based automatic seizure detection in intracerebral electroencephalogram Clinical Neurophysiology 114 May (5) 2003 898 908 (Pubitemid 36556101)
    • (2003) Clinical Neurophysiology , vol.114 , Issue.5 , pp. 898-908
    • Khan, Y.U.1    Gotman, J.2
  • 10
    • 38749083808 scopus 로고    scopus 로고
    • Automatic seizure detection based on time-frequency analysis and artificial neural networks
    • Article ID 80510
    • A.T. Tzallas, M.G. Tsipouras, and D.I. Fotiadis Automatic seizure detection based on time-frequency analysis and artificial neural networks Computational Intelligence and Neuroscience 2007 2007 13 Article ID 80510
    • (2007) Computational Intelligence and Neuroscience , vol.2007 , pp. 13
    • Tzallas, A.T.1    Tsipouras, M.G.2    Fotiadis, D.I.3
  • 12
    • 34547573516 scopus 로고    scopus 로고
    • Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection
    • DOI 10.1109/TBME.2007.891945
    • S. Ghosh-Dastidar, H. Adeli, and N. Dadmehr Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection IEEE Transactions on Biomedical Engineering 54 September (9) 2007 1545 1551 (Pubitemid 47301028)
    • (2007) IEEE Transactions on Biomedical Engineering , vol.54 , Issue.9 , pp. 1545-1551
    • Ghosh-Dastidar, S.1    Adeli, H.2    Dadmehr, N.3
  • 13
    • 41249099701 scopus 로고    scopus 로고
    • Optimal classification of epileptic seizures in EEG using wavelet analysis and genetic algorithm
    • H. Ocak Optimal classification of epileptic seizures in EEG using wavelet analysis and genetic algorithm Signal Processing 7 July 2008 1858 1867
    • (2008) Signal Processing , vol.7 , Issue.JULY , pp. 1858-1867
    • Ocak, H.1
  • 14
    • 77957685691 scopus 로고    scopus 로고
    • Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks
    • L. Guo, D. Rivero, and A. Pazos Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks Journal of Neuroscience Methods 193 October (1) 2010 156 163
    • (2010) Journal of Neuroscience Methods , vol.193 , Issue.OCTOBER 1 , pp. 156-163
    • Guo, L.1    Rivero, D.2    Pazos, A.3
  • 16
    • 84878512713 scopus 로고    scopus 로고
    • Epileptic seizure detection in EEG signals using multifractal analysis and wavelet transform
    • R. Uthayakumar, and D. Easwaramoorthy Epileptic seizure detection in EEG signals using multifractal analysis and wavelet transform Fractals 21 June (2) 2013
    • (2013) Fractals , vol.21 , Issue.JUNE 2
    • Uthayakumar, R.1    Easwaramoorthy, D.2
  • 17
    • 84871148149 scopus 로고    scopus 로고
    • Multifractal-wavelet based denoising in the classification of healthy and epileptic EEG signals
    • R. Uthayakumar, and D. Easwaramoorthy Multifractal-wavelet based denoising in the classification of healthy and epileptic EEG signals Fluctuation and Noise Letters 11 December (4) 2012
    • (2012) Fluctuation and Noise Letters , vol.11 , Issue.DECEMBER 4
    • Uthayakumar, R.1    Easwaramoorthy, D.2
  • 18
    • 79953108190 scopus 로고    scopus 로고
    • Improved generalized fractal dimensions in the discrimination between healthy and epileptic EEG signals
    • D. Easwaramoorthy, and R. Uthayakumar Improved generalized fractal dimensions in the discrimination between healthy and epileptic EEG signals Journal of Computational Science 01 March 2011 31 38
    • (2011) Journal of Computational Science , vol.1 , Issue.MARCH , pp. 31-38
    • Easwaramoorthy, D.1    Uthayakumar, R.2
  • 19
    • 84865980798 scopus 로고    scopus 로고
    • Classification of seizure and nonseizure EEG signals using empirical mode decomposition
    • V. Bajaj, and R.B. Pachori Classification of seizure and nonseizure EEG signals using empirical mode decomposition IEEE Transactions on Information Technology in Biomedicine 6 November 2012 1135 1142
    • (2012) IEEE Transactions on Information Technology in Biomedicine , vol.6 , Issue.NOVEMBER , pp. 1135-1142
    • Bajaj, V.1    Pachori, R.B.2
  • 20
    • 80655124711 scopus 로고    scopus 로고
    • Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition
    • R.B. Pachori, and V. Bajaj Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition Computer Methods and Programs in Biomedicine 3 December 2011 373 381
    • (2011) Computer Methods and Programs in Biomedicine , vol.3 , Issue.DECEMBER , pp. 373-381
    • Pachori, R.B.1    Bajaj, V.2
  • 21
    • 78549254986 scopus 로고    scopus 로고
    • Discrimination between ictal and seizure-free EEG signals using empirical mode decomposition
    • Article ID 293056
    • R.B. Pachori Discrimination between ictal and seizure-free EEG signals using empirical mode decomposition Research Letters in Signal Processing 2008 2008 5 Article ID 293056
    • (2008) Research Letters in Signal Processing , vol.2008 , pp. 5
    • Pachori, R.B.1
  • 22
    • 79956288045 scopus 로고    scopus 로고
    • Seizure classification in EEG signals utilizing Hilbert-Huang transform
    • R.J. Oweis, and E.W. Abdulhay Seizure classification in EEG signals utilizing Hilbert-Huang transform BioMedical Engineering OnLine 10 May 2011
    • (2011) BioMedical Engineering OnLine , vol.10 , Issue.MAY
    • Oweis, R.J.1    Abdulhay, E.W.2
  • 24
    • 84880995411 scopus 로고    scopus 로고
    • Epileptic seizure detection based on the instantaneous area of analytic intrinsic mode functions of EEG signals
    • V. Bajaj, and R.B. Pachori Epileptic seizure detection based on the instantaneous area of analytic intrinsic mode functions of EEG signals Biomedical Engineering Letters 1 March 2013 17 21
    • (2013) Biomedical Engineering Letters , vol.1 , Issue.MARCH , pp. 17-21
    • Bajaj, V.1    Pachori, R.B.2
  • 25
    • 29744467968 scopus 로고    scopus 로고
    • Comparison of subspace-based methods with AR parametric methods in epileptic seizure detection
    • DOI 10.1016/j.compbiomed.2004.11.001, PII S0010482504001441
    • A. Subasi, E. Erçelebi, A. Alkan, and E. Koklukaya Comparison of subspace-based methods with AR parametric methods in epileptic seizure detection Computers in Biology and Medicine 36 February (2) 2006 195 208 (Pubitemid 43028493)
    • (2006) Computers in Biology and Medicine , vol.36 , Issue.2 , pp. 195-208
    • Subasi, A.1    Ercelebi, E.2    Alkan, A.3    Koklukaya, E.4
  • 31
    • 45749124824 scopus 로고    scopus 로고
    • A fault diagnosis approach for gears based on IMF AR model and SVM
    • Article ID 647135
    • J. Cheng, D. Yu, and Y. Yang A fault diagnosis approach for gears based on IMF AR model and SVM EURASIP Journal on Advances in Signal Processing 2008 2008 7 Article ID 647135
    • (2008) EURASIP Journal on Advances in Signal Processing , vol.2008 , pp. 7
    • Cheng, J.1    Yu, D.2    Yang, Y.3
  • 32
    • 37249031426 scopus 로고    scopus 로고
    • Wavelet-based feature extraction for support vector machines for screening balance impairments in the elderly
    • DOI 10.1109/TNSRE.2007.906961
    • A.H. Khandoker, D.T.H. Lai, R.K. Begg, and M. Palaniswami Wavelet-based feature extraction for support vector machines for screening balance impairments in the elderly IEEE Transactions on Neural Systems and Rehabilitation Engineering 15 December (4) 2007 587 597 (Pubitemid 350274170)
    • (2007) IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol.15 , Issue.4 , pp. 587-597
    • Khandoker, A.H.1    Lai, D.T.H.2    Begg, R.K.3    Palaniswami, M.4
  • 33
    • 0035682573 scopus 로고    scopus 로고
    • Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
    • Article ID 061907
    • R.G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David, and C.E. Elger Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state Physical Review E 64 6 2001 Article ID 061907
    • (2001) Physical Review e , vol.64 , Issue.6
    • Andrzejak, R.G.1    Lehnertz, K.2    Mormann, F.3    Rieke, C.4    David, P.5    Elger, C.E.6


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