메뉴 건너뛰기




Volumn 23, Issue 3, 2013, Pages

Automated diagnosis of epilepsy using CWT, HOS and texture parameters

Author keywords

classifier; discrete wavelet transform; Electrocardiogram; epilepsy; higher order statistics; ictal; interictal

Indexed keywords

AUTOMATED CLASSIFICATION; CONTINUOUS WAVELET TRANSFORMS; ELECTROENCEPHALOGRAM SIGNALS; EPILEPSY; ICTAL; INTERICTAL; PROBABILISTIC NEURAL NETWORKS; RADIAL BASIS FUNCTION(RBF);

EID: 84877308974     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129065713500093     Document Type: Article
Times cited : (127)

References (82)
  • 1
    • 0034779445 scopus 로고    scopus 로고
    • Glossary of descriptive terminology for ictal semiology: Report of the ILAE Task Force on classification and terminology
    • DOI 10.1046/j.1528-1157.2001.22001.x
    • W. Blume, H. Luders, E. Mizrahi, C. Tassinari, W. van Emde Boas and J. Engel, Glossary of descriptive terminology for ictal semiology: Report of the ILAE task force on classification and terminology, Epilepsia 42(9) (2001) 1212-1218. (Pubitemid 32951809)
    • (2001) Epilepsia , vol.42 , Issue.9 , pp. 1212-1218
    • Blume, W.T.1    Luders, H.O.2    Mizrahi, E.3    Tassinari, C.4    Van Emde Boas, W.5    Engel Jr., J.6
  • 3
    • 16344387731 scopus 로고    scopus 로고
    • Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE)
    • DOI 10.1111/j.0013-9580.2005.66104.x
    • R. Fisher, W. van Emde Boas, W. Blume, C. Elger, P. Genton, P. Lee and J. Engel, Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE), Epilepsia 46(4) (2005) 470-472. (Pubitemid 40470667)
    • (2005) Epilepsia , vol.46 , Issue.4 , pp. 470-472
    • Fisher, R.S.1    Van Emde Boas, W.2    Blume, W.3    Elger, C.4    Genton, P.5    Lee, P.6    Engel Jr., J.7
  • 4
    • 84877298918 scopus 로고    scopus 로고
    • World Health Organization, Epilepsy: Aetiogy [sic], epidemiology and prognosis, (accessed on March 2012
    • World Health Organization, Epilepsy: Aetiogy [sic], epidemiology and prognosis, http://www.who. int/mediacentre/factsheets/fs165/en/(accessed on March 2012
  • 6
    • 0842310823 scopus 로고    scopus 로고
    • A neural-network-based detection of epilepsy
    • DOI 10.1179/016164104773026534
    • V. P. Nigam and D. Graupe, A neural-network-based detection of epilepsy, Neurol. Res. 26(1) (2004) 55-60. (Pubitemid 38174388)
    • (2004) Neurological Research , vol.26 , Issue.1 , pp. 55-60
    • Nigam, V.P.1    Graupe, D.2
  • 7
    • 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 timedomain and frequency domain features, J. Med. Syst. 29(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
  • 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, J. Neurosc. Met. 123(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
    • 33846672121 scopus 로고    scopus 로고
    • A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy
    • DOI 10.1109/TBME.2006.886855, 4
    • H. Adeli, S. Ghosh-Dastidar and N. Dadmehr, A Wavelet-chaos methodology for analysis of EEGs and EEG sub-bands to detect seizure and epilepsy, IEEE Trans. Biomed. Eng. 54(2) (2007) 205-211. (Pubitemid 46188163)
    • (2007) IEEE Transactions on Biomedical Engineering , vol.54 , Issue.2 , pp. 205-211
    • Adeli, H.1    Ghosh-Dastidar, S.2    Dadmehr, N.3
  • 10
    • 51349083532 scopus 로고    scopus 로고
    • A spatio-temporal wavelet-chaos methodology for eeg-based diagnosis of alzheimer's diseas
    • H. Adeli, S. Ghosh-Dastidar and N. Dadmehr, A Spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's diseas, Neurosci. Lett. 444(2) (2008) 190-19.
    • (2008) Neurosci. Lett. , vol.444 , Issue.2 , pp. 190-19
    • Adeli, H.1    Ghosh-Dastidar, S.2    Dadmehr, N.3
  • 11
    • 77749242546 scopus 로고    scopus 로고
    • Wavelet synchronization methodology: A new approach for eeg-based diagnosis of adhd
    • M. Ahmadlou and H. Adeli, Wavelet synchronization methodology: A new approach for EEG-based diagnosis of ADHD, Clinical EEG Neurosci. 41(1) (2010) 1-10.
    • (2010) Clinical EEG Neurosci. , vol.41 , Issue.1 , pp. 1-10
    • Ahmadlou, M.1    Adeli, H.2
  • 12
    • 77958187047 scopus 로고    scopus 로고
    • Fractality and a wavelet-chaos-neural network methodology for eeg-based diagnosis of autistic spectrum disorder
    • M. Ahmadlou, H. Adeli and A. Adeli, Fractality and a wavelet-chaos-neural network methodology for EEG-based diagnosis of autistic spectrum disorder, J. Clin. Neurophysiol. 27(5) (2010) 328-333.
    • (2010) J. Clin. Neurophysiol. , vol.27 , Issue.5 , pp. 328-333
    • Ahmadlou, M.1    Adeli, H.2    Adeli, A.3
  • 13
    • 79952194903 scopus 로고    scopus 로고
    • Fractality and a wavelet-chao methodology for eeg-based diagnosis of alzheime's diseas
    • A. Ahmadlou, H. Adeli and A. Adeli, Fractality and a wavelet-chao methodology for EEG-based diagnosis of Alzheime's diseas, Alzheimer Dis. Assoc. Disord. 25(1) (2011) 85-92.
    • (2011) Alzheimer Dis. Assoc. Disord. , vol.25 , Issue.1 , pp. 85-92
    • Ahmadlou, A.1    Adeli, H.2    Adeli, A.3
  • 15
    • 33751396389 scopus 로고    scopus 로고
    • EEG signal classification using wavelet feature extraction and a mixture of expert model
    • DOI 10.1016/j.eswa.2006.02.005, PII S0957417406000844
    • A. Subasi, EEG signal classification using wavelet feature extraction and a mixture of expert model, Exp. Syst. Appl. 32(4) (2007) 1084-1093. (Pubitemid 44821797)
    • (2007) Expert Systems with Applications , vol.32 , Issue.4 , pp. 1084-1093
    • Subasi, A.1
  • 16
    • 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. Guenes, Classification of epileptic form EEG using a hybrid system based on decision tree classifier and fast fourier transform, Appl. Math. Comput. 187(2) (2007) 1017-1026. (Pubitemid 46627890)
    • (2007) Applied Mathematics and Computation , vol.187 , Issue.2 , pp. 1017-1026
    • Polat, K.1    Gunes, S.2
  • 18
    • 38749083808 scopus 로고    scopus 로고
    • Automatic seizure detection based on timefrequency analysis and artificial neural networks
    • A. T. Tzallas, M. G. Tsipouras and D. I. Fotiadis, Automatic seizure detection based on timefrequency analysis and artificial neural networks, Comput. Intell. Neurosci. (2007
    • (2007) Comput. Intell. Neurosci.
    • Tzallas, A.T.1    Tsipouras, M.G.2    Fotiadis, D.I.3
  • 19
    • 56349101801 scopus 로고    scopus 로고
    • Automatic detection of epileptic seizures in eeg using discrete wavelet transform and approximate entropy
    • H. Ocak, Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy, Exp. Syst. Appl. 36(2) (2009) 2027-2036.
    • (2009) Exp Syst Appl , vol.36 , Issue.2 , pp. 2027-2036
    • Ocak, H.1
  • 21
    • 77957830692 scopus 로고    scopus 로고
    • Eeg signal classification using pca, ica, lda and support vector machines
    • A. Subasi and M. I. Gursoy, EEG signal classification using PCA, ICA, LDA and Support Vector Machines, Exp. Syst. Appl. 37(12) (2010) 8659-8666.
    • (2010) Exp. Syst. Appl. , vol.37 , Issue.12 , pp. 8659-8666
    • Subasi, A.1    Gursoy, M.I.2
  • 23
    • 61849108243 scopus 로고    scopus 로고
    • Automatic identification of epilepsy by hos and power spectrum parameters using eeg signals: A comparative stud
    • Vancouver, August
    • C. K. Chua, V. Chandran, U. R. Acharya and C. M. Lim, Automatic identification of epilepsy by HOS and power spectrum parameters using EEG signals: A comparative stud, 30th IEEE-EMBS-2008, Vancouver, August 2008, pp. 3824-3827.
    • (2008) 30th IEEE-EMBS-2008 , pp. 3824-3827
    • Chua, C.K.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 24
    • 78649560818 scopus 로고    scopus 로고
    • Analysis and automatic identification of sleep stages using higher order spectra
    • U. R. Acharya, E. C. P. Chua, C. K. Chua, C. M. Lim and T. Tamura, Analysis and automatic identification of sleep stages using higher order spectra, Int. J. Neural Syst. 20(6) (2010) 509-521.
    • (2010) Int. J. Neural Syst. , vol.20 , Issue.6 , pp. 509-521
    • Acharya, U.R.1    Chua, E.C.P.2    Chua, C.K.3    Lim, C.M.4    Tamura, T.5
  • 25
    • 57649228948 scopus 로고    scopus 로고
    • Automatic identification of epilepsy by hos and power spectrum parameters using eeg signals: A comparative study
    • C. K. Chua, V. Chandran, U. R. Acharya and C. M. Lim, Automatic identification of epilepsy by HOS and power spectrum parameters using EEG signals: A comparative study, 29th IEEE-EMBS-2007 (2007), pp. 6495-6498.
    • (2007) 29th IEEE EMBS-2007 , pp. 6495-6498
    • Chua, C.K.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 26
    • 84877262991 scopus 로고    scopus 로고
    • EEG time series Database
    • EEG time series Database, http://www.meb. unibonn.de/epileptologie/ science/physik/eegdata.
  • 27
    • 58149159364 scopus 로고    scopus 로고
    • Analysis of epileptic eeg signals using higher order spectra
    • K. C. Chua, V. Chandran, U. R. Acharya and C. M. Lim, Analysis of epileptic EEG signals using higher order spectra, J. Med. Eng. Technol. 33(1) (2009) 42-50.
    • (2009) J. Med. Eng. Technol. , vol.33 42-50 , Issue.1
    • Chua, K.C.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 28
    • 84859351360 scopus 로고    scopus 로고
    • Application of non-linear and wavelet based features for the automated identification of epileptic eeg signals
    • U. R. Acharya, S. Vinitha, A. P. C Alvin, R. Yanti and J. S. Suri, Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals, Int. J. Neural Syst. 22(2) (2012) 1250002-1-1250002-14.
    • (2012) Int. J. Neural Syst. , vol.22 , Issue.2 , pp. 12500021-125000214
    • Acharya, U.R.1    Vinitha, S.2    Alvin, A.P.C.3    Yanti, R.4    Suri, J.S.5
  • 29
    • 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
    • R. G. Andrzejak, K. Lehnertz, C. Rieke, F. Mormann, 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 64 (2001) 061907.
    • (2001) Phys. Rev. E , vol.64 , pp. 061907
    • Andrzejak, R.G.1    Lehnertz, K.2    Rieke, C.3    Mormann, F.4    David, P.5    Elger, C.E.6
  • 30
    • 79953213343 scopus 로고    scopus 로고
    • Abnormal interictal gamma activity may manifest a seizure onset zone in temporal lobe epilepsy
    • A. V. Medvedev, A. M. Murro and K. J. Meador, Abnormal interictal gamma activity may manifest a seizure onset zone in temporal lobe epilepsy, Int. J. Neural Syst. 21(2) (2011) 103-114.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.2 , pp. 103-114
    • Medvedev, A.V.1    Murro, A.M.2    Meador, K.J.3
  • 31
    • 79953213681 scopus 로고    scopus 로고
    • Effect of electrical stimulation parameters on seizure treatment in the kainate animal model
    • P. Rajdev, M. Ward and P. Irazoqui, Effect of electrical stimulation parameters on seizure treatment in the kainate animal model, Int. J. Neural Syst. 21(2) (2011) 151-162.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.2 , pp. 151-162
    • Rajdev, P.1    Ward, M.2    Irazoqui, P.3
  • 32
    • 80053354397 scopus 로고    scopus 로고
    • Response neuromodulators based on artificial neural networks used to control seizure-like events in a computational model of epilepsy, int
    • S. Colici, O. C. Zalay and B. L. Bardakjian, Response neuromodulators based on artificial neural networks used to control seizure-like events in a computational model of epilepsy, Int. J. Neural Syst. 21(5) (2011) 367-383.
    • (2011) J. Neural Syst. , vol.21 , Issue.5 , pp. 367-383
    • Colici, S.1    Zalay, O.C.2    Bardakjian, B.L.3
  • 33
    • 80053354397 scopus 로고    scopus 로고
    • Response neuromodulators based on artificial neural networks used to control seizure-like events in a computational model of epilepsy, int
    • S. Colici, O. C. Zalay and B. L. Bardakjian, Response neuromodulators based on artificial neural networks used to control seizure-like events in a computational model of epilepsy, Int. J. Neural Syst. 21(5) (2011) 367-383.
    • (2011) J. Neural Syst. , vol.21 , Issue.5 , pp. 367-383
    • Colici, S.1    Zalay, O.C.2    Bardakjian, B.L.3
  • 35
    • 33745053715 scopus 로고    scopus 로고
    • Neural network-wavelet microsimulation model for delay and queue length estimation at freeway work zones
    • DOI 10.1061/(ASCE)0733-947X(2006)132:4(331)
    • S. Ghosh-Dastidar and H. Adeli, Neural networkwavelet micro-simulation model for delay and queue length estimation at freeway work zones, J. Transport. Eng. 132(4) (2006) 331-341. (Pubitemid 43870498)
    • (2006) Journal of Transportation Engineering , vol.132 , Issue.4 , pp. 331-341
    • Ghosh-Dastidar, S.1    Adeli, H.2
  • 36
    • 21344435472 scopus 로고    scopus 로고
    • Dynamic wavelet neural network for nonlinear identification of highrise buildings
    • DOI 10.1111/j.1467-8667.2005.00399.x
    • X. Jiang and H. Adeli, Dynamic wavelet neural network for nonlinear identification of highrise buildings, Comput.-Aided Civil Infrastruct. Eng. 20(5) (2005) 316-330. (Pubitemid 40906713)
    • (2005) Computer-Aided Civil and Infrastructure Engineering , vol.20 , Issue.5 , pp. 316-330
    • Jiang, X.1    Adeli, H.2
  • 37
    • 26444571471 scopus 로고    scopus 로고
    • Dynamic wavelet neural network model for traffic flow forecasting
    • DOI 10.1061/(ASCE)0733-947X(2005)131:10(771)
    • X. Jiang and H. Adeli, Dynamic wavelet neural network model for traffic flow forecasting, J. Transport. Eng. 131(10) (2005) 771-779. (Pubitemid 41419813)
    • (2005) Journal of Transportation Engineering , vol.131 , Issue.10 , pp. 771-779
    • Jiang, X.1    Adeli, H.2
  • 38
    • 33947706698 scopus 로고    scopus 로고
    • Bayesian wavelet packet denoising for structural system identification
    • DOI 10.1002/stc.161
    • X. Jiang, S. Mahadevan and H. Adeli, Bayesian wavelet packet denoising for structural system identification, Struct. Contr. Health Monit. 14(2) (2007) 333-356. (Pubitemid 46491912)
    • (2007) Structural Control and Health Monitoring , vol.14 , Issue.2 , pp. 333-356
    • Jiang, X.1    Mahadevan, S.2    Adeli, H.3
  • 39
    • 34547595423 scopus 로고    scopus 로고
    • Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings
    • DOI 10.1002/nme.1964
    • X. Jiang and H. Adeli, Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings, Int. J. Numer. Meth. Eng. 71(5) (2007) 606-629. (Pubitemid 47190309)
    • (2007) International Journal for Numerical Methods in Engineering , vol.71 , Issue.5 , pp. 606-629
    • Jiang, X.1    Adeli, H.2
  • 40
    • 0036571167 scopus 로고    scopus 로고
    • Incident detection algorithm using wavelet energy representation of traffic patterns
    • DOI 10.1061/(ASCE)0733-947X(2002)128:3(232)
    • A. Karim and H. Adeli, Incident detection algorithm using wavelet energy representation of traffic patterns, J. Transport. Eng. 128(3) (2002) 232-242. (Pubitemid 34500232)
    • (2002) Journal of Transportation Engineering , vol.128 , Issue.3 , pp. 232-242
    • Karim, A.1    Adeli, H.2
  • 41
    • 0036145931 scopus 로고    scopus 로고
    • Comparison of fuzzy-wavelet radial basis function neural network freeway incident detection model with California algorithm
    • DOI 10.1061/(ASCE)0733-947X(2002)128:1(21)
    • A. Karim and H. Adeli, Comparison of the fuzzy -Wavelet RBFNN freeway incident detection model with the california algorithm, J. Transport. Eng. 128(1) (2002) 21-30. (Pubitemid 34096524)
    • (2002) Journal of Transportation Engineering , vol.128 , Issue.1 , pp. 21-30
    • Karim, A.1    Adeli, H.2
  • 42
    • 0037250154 scopus 로고    scopus 로고
    • Fast automatic incident detection on urban and rural freeways using wavelet energy algorithm
    • DOI 10.1061/(ASCE)0733-947X(2003)129:1(57)
    • A. Karim and H. Adeli, Fast automatic incident detection on urban and rural freeways using the wavelet energy algorithm, J. Transport. Eng. 129(1) (2003) 57-68. (Pubitemid 36137746)
    • (2003) Journal of Transportation Engineering , vol.129 , Issue.1 , pp. 57-68
    • Karim, A.1    Adeli, H.2
  • 43
    • 43749121111 scopus 로고    scopus 로고
    • Dynamic fuzzy wavelet neuroemulator for non-linear control of irregular building structures
    • DOI 10.1002/nme.2195
    • X. Jiang and H. Adeli, Dynamic fuzzy wavelet neuroemulator for nonlinear control of irregular highrise building structures, Int. J. Numer. Meth. Eng. 74(7) (2008) 1045-1066. (Pubitemid 351689220)
    • (2008) International Journal for Numerical Methods in Engineering , vol.74 , Issue.7 , pp. 1045-1066
    • Jiang, X.1    Adeli, H.2
  • 44
    • 14844364669 scopus 로고    scopus 로고
    • Hybrid control of smart structures using a novel wavelet-based algorithm
    • H. Kim and H. Adeli, Hybrid control of smart structures using a novel wavelet-based algorithm, Comput.-Aided Civil Infrastruct. Eng. 20(1) (2005) 7-22. (Pubitemid 40464642)
    • (2005) Computer-Aided Civil and Infrastructure Engineering , vol.20 , Issue.1 , pp. 7-22
    • Kim, H.1    Adeli, H.2
  • 49
    • 0027235180 scopus 로고    scopus 로고
    • Pattern recognition using invariants defined from higher order spectra one-dimensional inputs
    • V. Chandran and S. L. Elgar, Pattern recognition using invariants defined from higher order spectra one-dimensional inputs, IEEE Trans. Signal Process. 41 (1997) 205-212.
    • (1997) IEEE Trans. Signal Process. , vol.41 , pp. 205-212
    • Chandran, V.1    Elgar, S.L.2
  • 50
    • 39749182703 scopus 로고    scopus 로고
    • Cardiac state diagnosis using higher order spectra of heart rate variability
    • K. C. Chua, V. Chandran, U. R. Acharya and C. M. Lim, Cardiac state diagnosis using higher order spectra of heart rate variability, J. Med. Eng. Technol. 32 (2006) 145-155.
    • (2006) J. Med. Eng. Technol. , vol.32 , pp. 145-155
    • Chua, K.C.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 51
    • 84856227784 scopus 로고    scopus 로고
    • Application of higher order spectra to identify epileptic eeg
    • K. C. Chua, V. Chandran, U. R. Acharya and C. M. Lim, Application of higher order spectra to identify epileptic EEG, J. Med. Syst. 35(6) (2011) 1563-1571.
    • (2011) J. Med. Syst. , vol.35 , Issue.6 , pp. 1563-1571
    • Chua, K.C.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 53
    • 76449101504 scopus 로고    scopus 로고
    • Study of normal ocular thermogram using textural parameters
    • J. H. Tan, E. Y. K. Ng and U. R. Acharya, Study of normal ocular thermogram using textural parameters, Infrared Phys. Technol. 53(2) (2010) 120-126.
    • (2010) Infrared Phys. Technol. , vol.532 , pp. 120-126
    • Tan, J.H.1    Ng, E.Y.K.2    Acharya, U.R.3
  • 55
    • 0001416258 scopus 로고
    • Texture classification using gray level run length
    • M. M. Galloway, Texture classification using gray level run length, Comput. Graph. Image Process. 4 (1975) 172-179.
    • (1975) Comput Graph Image Process , vol.4 , pp. 172-179
    • Galloway, M.M.1
  • 56
    • 0036647193 scopus 로고    scopus 로고
    • Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
    • DOI 10.1109/TPAMI.2002.1017623
    • T. Ojala, M. Pietikainen and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Trans. Pattern Anal. Mach. Intell. 24 (2002) 971-987. (Pubitemid 34835471)
    • (2002) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.24 , Issue.7 , pp. 971-987
    • Ojala, T.1    Pietikainen, M.2    Maenpaa, T.3
  • 57
    • 80052918395 scopus 로고    scopus 로고
    • Automated diagnosis of oral cancer using higher order spectra features and local binary pattern: A comparative study
    • M. M. R. Krishnan, U. R. Acharya, C. Chakraborty and A. K. Ray, Automated diagnosis of oral cancer using higher order spectra features and local binary pattern: A comparative study, Tech. Canc. Res. Treat. 10 (2011) 433-455.
    • (2011) Tech. Canc. Res. Treat. , vol.10 , pp. 433-455
    • Krishnan, M.M.R.1    Acharya, U.R.2    Chakraborty, C.3    Ray, A.K.4
  • 58
    • 85054952615 scopus 로고
    • Rapid texture identification
    • K. I. Laws, Rapid texture identification, SPIE Conf. Series, Vol. 238 (1980), pp. 376-380.
    • (1980) SPIE Conf. Series , vol.238 , pp. 376-380
    • Laws, K.I.1
  • 63
    • 69449101508 scopus 로고    scopus 로고
    • A probabilistic neural network for earthquake magnitude prediction
    • H. Adeli and A. Panakkat, A probabilistic neural network for earthquake magnitude prediction, Neural Netw. 22 (2009) 1018-1024.
    • (2009) Neural Netw. , vol.22 , pp. 1018-1024
    • Adeli, H.1    Panakkat, A.2
  • 64
    • 77958031946 scopus 로고    scopus 로고
    • Enhanced probabilistic neural network with local decision circles: A robust classifier
    • M. Ahmadlou and H. Adeli, Enhanced probabilistic neural network with local decision circles: A robust classifier, Integr. Comput.-Aided Eng. 17(3) (2010) 197-210.
    • (2010) Integr. Comput.-Aided Eng. , vol.17 , Issue.3 , pp. 197-210
    • Ahmadlou, M.1    Adeli, H.2
  • 66
    • 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
    • C. Petitmengin, M. Baulac and V. Navarro, Seizure anticipation: Are neurophenomenological approaches able to detect pre-ictal symptoms? Epilepsy Behav. 9(2) (2006) 298-306. (Pubitemid 44283808)
    • (2006) Epilepsy and Behavior , vol.9 , Issue.2 , pp. 298-306
    • Petitmengin, C.1    Baulac, M.2    Navarro, V.3
  • 69
    • 34547597104 scopus 로고    scopus 로고
    • Improved spiking neural networks for EEG classification and epilepsy and seizure detection
    • S. Ghosh-Dastidar and H. Adeli, Improved spiking neural networks for EEG classification and epilepsy and seizure detection, Integr. Comput.-Aided Eng. 14(3) (2007) 187-212. (Pubitemid 47191475)
    • (2007) Integrated Computer-Aided Engineering , vol.14 , Issue.3 , pp. 187-212
    • Ghosh-Dastidar, S.1    Adeli, H.2
  • 70
    • 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 Trans. Biomed. Eng. 54(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
  • 71
    • 38349123053 scopus 로고    scopus 로고
    • Principal component analysis enhanced cosine radial basis function neural network for robust epilepsy and seizure detection
    • S. Ghosh-Dastidar, H. Adeli and N. Dadmehr, Principal component analysis enhanced cosine radial basis function neural network for robust epilepsy and seizure detection, IEEE Trans. Biomed. Eng. 55(2) (2008) 512-518.
    • (2008) IEEE Trans. Biomed. Eng. , vol.55 , Issue.2 , pp. 512-518
    • Ghosh-Dastidar, S.1    Adeli, H.2    Dadmehr, N.3
  • 72
    • 71049128082 scopus 로고    scopus 로고
    • A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection
    • S. Ghosh-Dastidar and H. Adeli, A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection, Neural Netw. 22(10) (2009) 1419-1431.
    • (2009) Neural Netw. , vol.22 , Issue.10 , pp. 1419-1431
    • Ghosh-Dastidar, S.1    Adeli, H.2
  • 74
    • 67449161052 scopus 로고    scopus 로고
    • Automatic identification of epileptic eeg signals using higher order spectra
    • K. C. Chua, V. Chandran, U. R. Acharya, C. M. Lim, Automatic identification of epileptic EEG signals using higher order spectra, Int. J. Eng. Med. 223(4) (2009) 485-495.
    • (2009) Int J Eng Med , vol.223 , Issue.4 , pp. 485-495
    • Chua K, C.1    Chandran, V.2    Acharya U, R.3    Lim C, M.4
  • 75
    • 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
    • N. F. Guler, E. D. Ubey and I. Guler, Recurrent neural network employing Lyapunov exponents for EEG signals classification, Exp. Syst. Appl. 29(3) (2005) 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
  • 76
    • 76449108621 scopus 로고    scopus 로고
    • Automatic identification of epileptic eeg signals using nonlinear parameters
    • U. R. Acharya, K. C. Chua, T. C. Lim, Dorithy and J. S. Suri, Automatic identification of epileptic EEG signals using nonlinear parameters, J. Mech. Med. Biol. 9(4) (2009) 539-553.
    • (2009) J. Mech. Med. Biol. , vol.9 , Issue.4 , pp. 539-553
    • Acharya, U.R.1    Chua, K.C.2    Lim Dorithy, T.C.3    Suri, J.S.4
  • 77
    • 79960037752 scopus 로고    scopus 로고
    • Application of recurrence quantification analysis for the automated identification of epileptic eeg signals
    • U. R. Acharya, S. Vinitha, S. Chattopadhyay, W. Yu and A. P. C. Alvin, Application of recurrence quantification analysis for the automated identification of epileptic EEG signals, Int. J. Neural Syst. 21(3) (2011) 199-211.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.3 , pp. 199-211
    • Acharya, U.R.1    Vinitha, S.2    Chattopadhyay, S.3    Yu, W.4    Alvin, A.P.C.5
  • 79
    • 80053348045 scopus 로고    scopus 로고
    • Automatic detection of epileptic eeg signals using higher order cumulant features, int
    • U. R. Acharya, S. Vinitha and J. S. Suri, Automatic detection of epileptic EEG signals using higher order cumulant features, Int. J. Neural Syst. 21(5) (2011) 1-12.
    • (2011) J. Neural Syst. , vol.21 , Issue.5 , pp. 1-12
    • Acharya, U.R.1    Vinitha, S.2    Suri, J.S.3
  • 80
    • 77951577412 scopus 로고    scopus 로고
    • Automatic identification of epileptic and background eeg signals using frequency domain parameters
    • O. Faust, U. R. Acharya, C. M. Lim and B. Sputh, Automatic identification of epileptic and background EEG signals using frequency domain parameters, Int. J. Neural Syst. 20(2) (2010) 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    Sputh, B.4
  • 81
    • 84877839633 scopus 로고    scopus 로고
    • Automated diagnosis of epileptic electroencephalogram using independent component analysis and discrete wavelet transform for different electroencephalogram durations
    • doi: 10.1177/0954411912467883
    • U. R. Acharya, R. Yanti, G. Swapna, V. S. Sree, R. J. Martis and J. S. Suri, Automated diagnosis of epileptic electroencephalogram using independent component analysis and discrete wavelet transform for different electroencephalogram durations, Proc. Inst. Mech. Eng. Pt. H J. Eng. Med. (2012), doi: 10.1177/0954411912467883.
    • (2012) Proc. Inst. Mech. Eng. Pt. H J. Eng. Med.
    • Acharya, U.R.1    Yanti, R.2    Swapna, G.3    Sree, V.S.4    Martis, R.J.5    Suri, J.S.6
  • 82
    • 84859217391 scopus 로고    scopus 로고
    • Use of principal component analysis for automatic detection of epileptic eeg activities
    • U. R. Acharya, S. Vinitha and J. S. Suri, Use of principal component analysis for automatic detection of epileptic EEG activities, Exp. Syst. Appl. 39(10) (2012) 9072-9078.
    • (2012) Exp. Syst. Appl. , vol.39 , Issue.10 , pp. 9072-9078
    • Acharya, U.R.1    Vinitha, S.2    Suri, J.S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.