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Volumn 227, Issue 3, 2013, Pages 234-244

Automated diagnosis of epileptic electroencephalogram using independent component analysis and discrete wavelet transform for different electroencephalogram durations

Author keywords

Classifier; Discrete wavelet transform; Electroencephalogram; Epilepsy; Ictal; Independent component analysis; Interictal

Indexed keywords

ELECTROENCEPHALOGRAM DATA; ELECTROENCEPHALOGRAM SIGNALS; EPILEPSY; ICTAL; INTERICTAL; PROBABILISTIC NEURAL NETWORKS; RADIAL BASIS FUNCTION KERNELS; SUPPORT VECTOR MACHINE CLASSIFIERS;

EID: 84877839633     PISSN: 09544119     EISSN: 20413033     Source Type: Journal    
DOI: 10.1177/0954411912467883     Document Type: Article
Times cited : (36)

References (43)
  • 1
    • 0030938880 scopus 로고    scopus 로고
    • Patients' experiences of injury as a result of epilepsy
    • DOI 10.1111/j.1528-1157.1997.tb01733.x
    • Buck D, Baker GA, Jacoby A, et al. Patients' experiences of injury as a result of epilepsy. Epilepsia 1997; 38: 439-444. (Pubitemid 27172024)
    • (1997) Epilepsia , vol.38 , Issue.4 , pp. 439-444
    • Buck, D.1    Baker, G.A.2    Jacoby, A.3    Smith, D.F.4    Chadwick, D.W.5
  • 3
    • 84877799445 scopus 로고    scopus 로고
    • (accessed March 2012)
    • Epilepsy. http://www.news-medical.net/health/What-is-Epilepsy.aspx (accessed March 2012).
    • Epilepsy
  • 4
    • 79960803523 scopus 로고    scopus 로고
    • Improving the separability of multiple EEG features for a BCI by neural-time-series-prediction-preprocessing
    • Coyle D, McGinnity TM and Prasad G. Improving the separability of multiple EEG features for a BCI by neural-time-series-prediction-preprocessing. Biomed Signal Proces 2010; 5(3): 196-204.
    • (2010) Biomed Signal Proces , vol.5 , Issue.3 , pp. 196-204
    • Coyle, D.1    McGinnity, T.M.2    Prasad, G.3
  • 5
    • 67650221411 scopus 로고    scopus 로고
    • Adapting subject specific motor imagery EEG patterns in space-time-frequency for a brain computer interface
    • Ince NF, Goksu F, Tewfik AH, et al. Adapting subject specific motor imagery EEG patterns in space-time-frequency for a brain computer interface. Biomed Signal Proces 2009; 4(3): 236-246.
    • (2009) Biomed Signal Proces , vol.4 , Issue.3 , pp. 236-246
    • Ince, N.F.1    Goksu, F.2    Tewfik, A.H.3
  • 6
    • 78651351193 scopus 로고    scopus 로고
    • EEG montage analysis in the blind source separation framework
    • Ruiz RAS, Ranta R and Louis-Dorr V. EEG montage analysis in the Blind Source Separation framework. Biomed Signal Proces 2010; 6(1): 77-84.
    • (2010) Biomed Signal Proces , vol.6 , Issue.1 , pp. 77-84
    • Ruiz, R.A.S.1    Ranta, R.2    Louis-Dorr, V.3
  • 7
    • 0029868488 scopus 로고    scopus 로고
    • Beyond mapping: Estimating complexity of multichannel EEG recordings
    • Wackermann J. Beyond mapping: estimating complexity of multi-channel EEG recordings. Acta Neurobiol Exp 1996; 56(1): 197-208. (Pubitemid 26126140)
    • (1996) Acta Neurobiologiae Experimentalis , vol.56 , Issue.1 , pp. 197-208
    • Wackermann, J.1
  • 8
    • 0032171718 scopus 로고    scopus 로고
    • Stochastic complexity measures for physiological signal analysis
    • DOI 10.1109/10.709563
    • Rezek IA and Roberts SJ. Stochastic complexity measures for physiological signal analysis. IEEE Trans Biomed Eng 1998; 45(9): 1186-1191. (Pubitemid 28385739)
    • (1998) IEEE Transactions on Biomedical Engineering , vol.45 , Issue.9 , pp. 1186-1191
    • Rezek, I.A.1    Roberts, S.J.2
  • 9
    • 0032714280 scopus 로고    scopus 로고
    • The performance of electroencephalogram bispectral index and auditory evoked potential index to predict loss of consciousness during propofol infusion
    • Schraag S, Bothner U, Gajraj R, et al. The performance of electroencephalogram bispectral index and auditory evoked potential index to predict loss of consciousness during propofol infusion. Anesth Analg 1999; 89(5): 1311-1315. (Pubitemid 29521962)
    • (1999) Anesthesia and Analgesia , vol.89 , Issue.5 , pp. 1311-1315
    • Schraag, S.1    Bothner, U.2    Gajraj, R.3    Kenny, G.N.C.4    Georgieff, M.5
  • 11
    • 77953952237 scopus 로고    scopus 로고
    • EEG signal processing: A survey
    • Subha DP, Joseph KP, Acharya UR, et al. EEG signal processing: a survey. J Med Syst 2010; 34(2): 195-212.
    • (2010) J Med Syst , vol.34 , Issue.2 , pp. 195-212
    • Subha, D.P.1    Joseph, K.P.2    Acharya, U.R.3
  • 12
    • 0026462367 scopus 로고
    • Complex dynamics underlying the human electroencephalogram
    • Ravelli F and Antolini R. Complex dynamics underlying the human electroencephalogram. Biol Cybern 1992; 67: 57-65.
    • (1992) Biol Cybern , vol.67 , pp. 57-65
    • Ravelli, F.1    Antolini, R.2
  • 13
    • 0035682573 scopus 로고    scopus 로고
    • Indications of nonlinear deterministic and finitedimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
    • Andrzejak RG, Lehnertz K, Rieke Mormann F, et al. Indications of nonlinear deterministic and finitedimensional structures in time series of brain electrical activity: dependence on recording region and brain state. Phys Rev E 2001; 64: 558 061907.
    • (2001) Phys Rev e , vol.64 , Issue.558 , pp. 061907
    • Andrzejak, R.G.1    Lehnertz, K.2    Rieke Mormann, F.3
  • 14
    • 0026922952 scopus 로고
    • Wavelet and filter banks: Theory and design
    • Vitterli M. Wavelet and filter banks: theory and design. IEEE T Signal Proces 1992; 40(9): 2207-2232.
    • (1992) IEEE T Signal Proces , vol.40 , Issue.9 , pp. 2207-2232
    • Vitterli, M.1
  • 16
    • 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
    • Adeli H, Zhou Z and Dadmehr N. Analysis of EEG records in an epileptic patient using wavelet transform. J Neurosci Methods 2003; 123(1): 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
  • 17
    • 77957830692 scopus 로고    scopus 로고
    • EEG signal classification using PCA, ICA, LDA and support vector machines
    • Subasi A and Gursoy MI. EEG signal classification using PCA, ICA, LDA and support vector machines. Expert Syst Appl 2010; 37: 8659-8666.
    • (2010) Expert Syst Appl , vol.37 , pp. 8659-8666
    • Subasi, A.1    Gursoy, M.I.2
  • 20
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: Algorithms and applications
    • DOI 10.1016/S0893-6080(00)00026-5, PII S0893608000000265
    • Hyvärinen A and Oja E. Independent component analysis: algorithms and applications. Neural Netw 2000; 13(4-5): 411-430. (Pubitemid 30447427)
    • (2000) Neural Networks , vol.13 , Issue.4-5 , pp. 411-430
    • Hyvarinen, A.1    Oja, E.2
  • 25
    • 33747866964 scopus 로고    scopus 로고
    • Seizure anticipation: Are neurophenomenological approaches able to detect preictal symptoms?
    • DOI 10.1016/j.yebeh.2006.05.013, PII S1525505006002071
    • Petitmengin C, Baulac M and Navarro V. Seizure anticipation: are neurophenomenological approaches able to detect preictal symptoms? Epilepsy Behav 2006; 9(2): 298-306. (Pubitemid 44283808)
    • (2006) Epilepsy and Behavior , vol.9 , Issue.2 , pp. 298-306
    • Petitmengin, C.1    Baulac, M.2    Navarro, V.3
  • 26
    • 84856227784 scopus 로고    scopus 로고
    • Application of higher order spectra to identify epileptic EEG
    • Chua CK, Chandran V, Acharya UR, et al. Application of higher order spectra to identify epileptic EEG. J Med Syst 2011; 35(6): 1563-1571.
    • (2011) J Med Syst , vol.35 , Issue.6 , pp. 1563-1571
    • Chua, C.K.1    Chandran, V.2    Acharya, U.R.3
  • 28
    • 0001649501 scopus 로고
    • Can epileptic seizures be predicted? Evidence from nonlinear time series analyses of brain electrical activity
    • Lehnertz K and Elger CE. Can epileptic seizures be predicted? Evidence from nonlinear time series analyses of brain electrical activity. Phys Rev Lett 1988; 80: 5019-5023.
    • (1988) Phys Rev Lett , vol.80 , pp. 5019-5023
    • Lehnertz, K.1    Elger, C.E.2
  • 29
    • 0031721738 scopus 로고    scopus 로고
    • Can epileptic crisis be anticipated?
    • Martinerie J, Adam C, Le van Quyen M, et al. Can epileptic crisis be anticipated? Nat Med 1998; 4: 1173-1176.
    • (1998) Nat Med , vol.4 , pp. 1173-1176
    • Martinerie, J.1    Adam, C.2    Le Van Quyen, M.3
  • 30
    • 24144470790 scopus 로고    scopus 로고
    • Recurrent neural networks employing Lyapunov exponents for EEG signals classification
    • DOI 10.1016/j.eswa.2005.04.011, PII S0957417405000679
    • Guler NF, Ubey ED and Guler I. Recurrent neural network employing Lyapunov exponents for EEG signals classification. Expert Syst Appl 2005; 29(3): 506-514. (Pubitemid 41230775)
    • (2005) Expert Systems with Applications , vol.29 , Issue.3 , pp. 506-514
    • Guler, N.F.1    Ubeyli, E.D.2    Guler, I.3
  • 31
    • 34547597104 scopus 로고    scopus 로고
    • Improved spiking neural networks for EEG classification and epilepsy and seizure detection
    • Ghosh-Dastidar S and Adeli H. Improved spiking neural networks for EEG classification and epilepsy and seizure detection. Integr Comput-Aid E 2007; 14(3): 187-212. (Pubitemid 47191475)
    • (2007) Integrated Computer-Aided Engineering , vol.14 , Issue.3 , pp. 187-212
    • Ghosh-Dastidar, S.1    Adeli, H.2
  • 32
    • 34547573516 scopus 로고    scopus 로고
    • Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection
    • DOI 10.1109/TBME.2007.891945
    • Ghosh-Dastidar S, Adeli H and Dadmehr N. Mixed band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection. IEEE Trans Biomed Eng 2007; 54(9): 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
  • 33
    • 38349123053 scopus 로고    scopus 로고
    • Principal component analysis enhanced cosine radial basis function neural network for robust epilepsy and seizure detection
    • Ghosh-Dastidar S, Adeli H and Dadmehr N. Principal component analysis enhanced cosine radial basis function neural network for robust epilepsy and seizure detection. IEEE Trans Biomed Eng 2008; 55(2): 512-518.
    • (2008) IEEE Trans Biomed Eng , vol.55 , Issue.2 , pp. 512-518
    • Ghosh-Dastidar, S.1    Adeli, H.2    Dadmehr, N.3
  • 34
    • 71049128082 scopus 로고    scopus 로고
    • A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection
    • Ghosh-Dastidar S and Adeli H. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection. Neural Netw 2009; 22(10): 1419-1431.
    • (2009) Neural Netw , vol.22 , Issue.10 , pp. 1419-1431
    • Ghosh-Dastidar, S.1    Adeli, H.2
  • 36
    • 76449108621 scopus 로고    scopus 로고
    • Automatic identification of epileptic EEG signals using nonlinear parameters
    • Acharya UR, Chua KC, Lim TC, et al. Automatic identification of epileptic EEG signals using nonlinear parameters. J Mech Med Biol 2009; 9(4): 539-553.
    • (2009) J Mech Med Biol , vol.9 , Issue.4 , pp. 539-553
    • Acharya, U.R.1    Chua, K.C.2    Lim, T.C.3
  • 37
    • 77951577412 scopus 로고    scopus 로고
    • Automatic identification of epileptic and background EEG signals using frequency domain parameters
    • Faust O, Acharya UR, Lim CM, et al. Automatic identification of epileptic and background EEG signals using frequency domain parameters. Int J Neural Syst 2010; 20(2): 159-176.
    • (2010) Int J Neural Syst , vol.20 , Issue.2 , pp. 159-176
    • Faust, O.1    Acharya, U.R.2    Lim, C.M.3
  • 38
    • 79960037752 scopus 로고    scopus 로고
    • Application of recurrence quantification analysis for the automated identification of epileptic EEG signals
    • Acharya UR, Sree SV, Chattopadhyay S, et al. Application of recurrence quantification analysis for the automated identification of epileptic EEG signals. Int J Neural Syst 2011; 21(3): 199-211.
    • (2011) Int J Neural Syst , vol.21 , Issue.3 , pp. 199-211
    • Acharya, U.R.1    Sree, S.V.2    Chattopadhyay, S.3
  • 39
    • 80053348045 scopus 로고    scopus 로고
    • Automatic detection of epileptic EEG signals using higher order cumulant features
    • Acharya UR, Sree SV and Suri JS. Automatic detection of epileptic EEG signals using higher order cumulant features. Int J Neural Syst 2011; 21(5): 1-12.
    • (2011) Int J Neural Syst , vol.21 , Issue.5 , pp. 1-12
    • Acharya, U.R.1    Sree, S.V.2    Suri, J.S.3
  • 40
    • 84859212205 scopus 로고    scopus 로고
    • Automated diagnosis of epileptic EEG using entropies
    • Acharya UR, Molinari F, Sree SV, et al. Automated diagnosis of epileptic EEG using entropies. Biomed Signal Proces 2012; 7(4): 401-408.
    • (2012) Biomed Signal Proces , vol.7 , Issue.4 , pp. 401-408
    • Acharya, U.R.1    Molinari, F.2    Sree, S.V.3
  • 41
    • 84877838003 scopus 로고    scopus 로고
    • Use of principal component analysis for automatic detection of epileptic EEG activities
    • Acharya UR, Sree SV and Suri JS. Use of principal component analysis for automatic detection of epileptic EEG activities. Expert Syst Appl 2012; 30(10): 9072-9078.
    • (2012) Expert Syst Appl , vol.30 , Issue.10 , pp. 9072-9078
    • Acharya, U.R.1    Sree, S.V.2    Suri, J.S.3
  • 42
    • 84870547200 scopus 로고    scopus 로고
    • Application of empirical mode decomposition (EMD) for automated detection of epilepsy using EEG signals
    • DOI: 10.1142/S012906571250027
    • Martis RJ, Acharya UR, Jen TH, et al. Application of empirical mode decomposition (EMD) for automated detection of epilepsy using EEG signals. Int J Neural Syst. 2012. DOI: 10.1142/S012906571250027.
    • (2012) Int J Neural Syst
    • Martis, R.J.1    Acharya, U.R.2    Jen, T.H.3
  • 43
    • 84859351360 scopus 로고    scopus 로고
    • Application of non linear and wavelet based features for the automated identification of epileptic EEG signals
    • Acharya UR, Sree SV, Alvin APC, et al. Application of non linear and wavelet based features for the automated identification of epileptic EEG signals. Int J Neural Syst 2012; 22: 1250002.
    • (2012) Int J Neural Syst , vol.22 , pp. 1250002
    • Acharya, U.R.1    Sree, S.V.2    Alvin, A.P.C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.