메뉴 건너뛰기




Volumn , Issue , 2007, Pages 135-140

A time-frequency based method for the detection of epileptic seizures in EEG recordings

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; NEURAL NETWORKS; PROBLEM SOLVING;

EID: 34748829073     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMS.2007.17     Document Type: Conference Paper
Times cited : (24)

References (26)
  • 1
    • 33846638294 scopus 로고    scopus 로고
    • Seizure Prediction: The long and the winding road
    • F. Mormann, R.G. Andrzejak, CE. Elger, and K. Lenhnertz, "Seizure Prediction: the long and the winding road," Brain, vol. 130 (2), 2007, pp. 314-33.
    • (2007) Brain , vol.130 , Issue.2 , pp. 314-333
    • Mormann, F.1    Andrzejak, R.G.2    Elger, C.E.3    Lenhnertz, K.4
  • 2
    • 0032962246 scopus 로고    scopus 로고
    • Automatic detection of seizures and spikes
    • J. Gorman, "Automatic detection of seizures and spikes," J. Clin. Neurophysiol, vol. 16 (2), 1999, pp. 130-40.
    • (1999) J. Clin. Neurophysiol , vol.16 , Issue.2 , pp. 130-140
    • Gorman, J.1
  • 3
    • 0015693158 scopus 로고
    • An EEG device for monitoring seizure discharges
    • P.F. Prior, R.S.M. Virden, and D.E. Maynard, "An EEG device for monitoring seizure discharges," Epilepsia, vol. 14(4), 1973, pp. 367-72.
    • (1973) Epilepsia , vol.14 , Issue.4 , pp. 367-372
    • Prior, P.F.1    Virden, R.S.M.2    Maynard, D.E.3
  • 5
    • 0027199942 scopus 로고
    • An automated seizure monitoring system for patients with indwelling recording electrodes
    • G.W. Harding, "An automated seizure monitoring system for patients with indwelling recording electrodes", Electroenceph. Clin. Neurophysiol., vol. 86 (6), 1993, pp. 428-37.
    • (1993) Electroenceph. Clin. Neurophysiol , vol.86 , Issue.6 , pp. 428-437
    • Harding, G.W.1
  • 6
    • 24044474732 scopus 로고    scopus 로고
    • Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency Domain Features
    • V. Srinivasan, C. Eswaran, and N. Sriraam, "Artificial Neural Network Based Epileptic Detection Using Time-Domain and Frequency Domain Features", J. Med. Syst., vol.29 (6), 2005, pp. 647-60.
    • (2005) J. Med. Syst , vol.29 , Issue.6 , pp. 647-660
    • Srinivasan, V.1    Eswaran, C.2    Sriraam, N.3
  • 7
    • 0842310823 scopus 로고    scopus 로고
    • A neural-network-based detection of epilepsy
    • V.P. Nigam, and D. Graupe, "A neural-network-based detection of epilepsy", Neurol. Res., vol. 26 (6), 2004, pp. 55-60.
    • (2004) Neurol. Res , vol.26 , Issue.6 , pp. 55-60
    • Nigam, V.P.1    Graupe, D.2
  • 8
    • 33750457954 scopus 로고    scopus 로고
    • Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform
    • K. Polat, and S. Güneş, "Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform", Appl. Math. Comput., vol. 32 (2), 2007, pp 625-31.
    • (2007) Appl. Math. Comput , vol.32 , Issue.2 , pp. 625-631
    • Polat, K.1    Güneş, S.2
  • 10
    • 0037441741 scopus 로고    scopus 로고
    • Analysis of EEG records in an epileptic patient using wavelet transform
    • H. Adeli, Z. Zhou, and N. Dadmehr, "Analysis of EEG records in an epileptic patient using wavelet transform", J. Neurosc. Meth., vol. 123 (1), 2003, pp. 69-87.
    • (2003) J. Neurosc. Meth , vol.123 , Issue.1 , pp. 69-87
    • Adeli, H.1    Zhou, Z.2    Dadmehr, N.3
  • 11
    • 33751396389 scopus 로고    scopus 로고
    • Signal classification using wavelet feature extraction and a mixture of expert model
    • A. Subasi, "Signal classification using wavelet feature extraction and a mixture of expert model", Exp. Syst. Appl., vol. 32 (4), 2007, pp. 1084-93.
    • (2007) Exp. Syst. Appl , vol.32 , Issue.4 , pp. 1084-1093
    • Subasi, A.1
  • 13
    • 26944458497 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients
    • I. Güler and E.D. Übeyli, "Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients", J. Neurosc. Meth., vol. 148 (2), 2005, pp 113-21.
    • (2005) J. Neurosc. Meth , vol.148 , Issue.2 , pp. 113-121
    • Güler, I.1    Übeyli, E.D.2
  • 14
    • 34748884414 scopus 로고    scopus 로고
    • I. Güler, and E.D. Übeyli, Multiclass Support Vector Machines for EEG Signals Classification, IEEE Trans. Inform. Techn. Biomed., in Press.
    • I. Güler, and E.D. Übeyli, "Multiclass Support Vector Machines for EEG Signals Classification", IEEE Trans. Inform. Techn. Biomed., in Press.
  • 15
    • 0027731517 scopus 로고
    • A Multistage System to Detect Epileptiform Activity in the EEG
    • A.A. Dingle, R.D. Jones, G.J. Caroll, and W.R. Fright, "A Multistage System to Detect Epileptiform Activity in the EEG", IEEE Trans. Biomed. Eng., vol. 40 (12), 1993, pp. 1260-68.
    • (1993) IEEE Trans. Biomed. Eng , vol.40 , Issue.12 , pp. 1260-1268
    • Dingle, A.A.1    Jones, R.D.2    Caroll, G.J.3    Fright, W.R.4
  • 16
    • 33746913071 scopus 로고    scopus 로고
    • 3: An effective system for automated detection of epileptiform events in long-term EEG based on context information
    • 3: an effective system for automated detection of epileptiform events in long-term EEG based on context information", Med. Biol. Eng. Comput., vol. 44 (6), 2006, pp. 459-70.
    • (2006) Med. Biol. Eng. Comput , vol.44 , Issue.6 , pp. 459-470
    • Argoud, F.I.1    De Azevedo, F.M.2    Neto, J.M.3    Grillo, E.4
  • 19
    • 22244454103 scopus 로고    scopus 로고
    • Monitoring changing dynamics with correlation integrals: Case study of an epileptic seizure
    • D.E. Lemer, "Monitoring changing dynamics with correlation integrals: case study of an epileptic seizure", Physica D, vol. 97 (4), 1996, pp. 563-76.
    • (1996) Physica D , vol.97 , Issue.4 , pp. 563-576
    • Lemer, D.E.1
  • 20
    • 24144470790 scopus 로고    scopus 로고
    • Recurrent neural networks employing Lyapunov exponents for EEG signals classification
    • N.F. Güler, E.D. Übeyli, and I. Güler, "Recurrent neural networks employing Lyapunov exponents for EEG signals classification", Exp. Syst. Appl., vol. 29 (3), 2005, pp. 506-14.
    • (2005) Exp. Syst. Appl , vol.29 , Issue.3 , pp. 506-514
    • Güler, N.F.1    Übeyli, E.D.2    Güler, I.3
  • 22
    • 0031029383 scopus 로고    scopus 로고
    • A patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: Possible use as a warning device
    • H. Qu, and J. Gorman, "A patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: possible use as a warning device", IEEE Trans. Biomed. Eng., vol. 44 (2), 1997, pp. 115-22.
    • (1997) IEEE Trans. Biomed. Eng , vol.44 , Issue.2 , pp. 115-122
    • Qu, H.1    Gorman, J.2
  • 23
    • 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
    • 1-8
    • 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," Phys. Rev. E, vol. 64, 2001, pp. 061907 (1-8).
    • (2001) Phys. Rev. E , vol.64 , pp. 061907
    • Andrzejak, R.G.1    Lehnertz, K.2    Mormann, F.3    Rieke, C.4    David, P.5    Elger, C.E.6
  • 26
    • 33846095446 scopus 로고    scopus 로고
    • Features extracted by eigenvector methods for detecting variability of EEG signals
    • E.D. Übeyli, and I. Güler, "Features extracted by eigenvector methods for detecting variability of EEG signals", P. Recogn. Lett., vol. 28 (5), 2007, pp 592-603.
    • (2007) P. Recogn. Lett , vol.28 , Issue.5 , pp. 592-603
    • Übeyli, E.D.1    Güler, I.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.