메뉴 건너뛰기




Volumn 36, Issue 1, 2012, Pages 1-13

Diagnosis of epilepsy from electroencephalography signals using multilayer perceptron and Elman artificial neural networks and wavelet transform

Author keywords

Artificial neural networks; Electroencephalography; Elman network; Epilepsy; Multilayer perceptron; Principal component analysis; Receiver operation characteristic analysis; Signal processing; Wavelet transform

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; ELECTROENCEPHALOGRAPHY; EPILEPSY; HUMAN; PERCEPTRON; PRINCIPAL COMPONENT ANALYSIS; RECEIVER OPERATING CHARACTERISTIC; WAVELET ANALYSIS; INSTRUMENTATION; METHODOLOGY; SIGNAL PROCESSING;

EID: 84860258234     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-010-9440-0     Document Type: Article
Times cited : (19)

References (33)
  • 1
    • 1542600129 scopus 로고    scopus 로고
    • The diagnosis of epilepsy and the art of listening
    • Trevathan, E., The diagnosis of epilepsy and the art of listening. Neurology 61:13-14, 2003.
    • (2003) Neurology , vol.61 , pp. 13-14
    • Trevathan, E.1
  • 2
  • 3
    • 33746233572 scopus 로고    scopus 로고
    • Epilepsy case studies. USA
    • Faught, E., Epilepsy case studies. USA. Neurol. Clin. 24:291-307, 2006.
    • (2006) Neurol. Clin. , vol.24 , pp. 291-307
    • Faught, E.1
  • 4
    • 0037452661 scopus 로고    scopus 로고
    • Diagnosis and management of epilepsy
    • Blume, T. W., Diagnosis and management of epilepsy. CMAJ 168 (4):441-8, 2003.
    • (2003) CMAJ , vol.168 , Issue.4 , pp. 441-448
    • Blume, T.W.1
  • 6
    • 28444469422 scopus 로고    scopus 로고
    • The importance of acknowledging clinical uncertainty in the diagnosis of epilepsy and non-epileptic events
    • DOI 10.1136/adc.2004.065441
    • Beach, R., and Reading, R., The importance of acknowledging clinical uncertainty in the diagnosis of epilepsy and non-epileptic events. Arch. Dis. Child. 90:1219-1222, 2005. (Pubitemid 41736303)
    • (2005) Archives of Disease in Childhood , vol.90 , Issue.12 , pp. 1219-1222
    • Beach, R.1    Reading, R.2
  • 7
    • 67349125387 scopus 로고    scopus 로고
    • The role of EEG in epilepsy: A critical review
    • Noachtar, S., and Rémi, J., The role of EEG in epilepsy: A critical review. Epilepsy Behav. 15:22-33, 2009.
    • (2009) Epilepsy Behav. , vol.15 , pp. 22-33
    • Noachtar, S.1    Rémi, J.2
  • 9
    • 44949265237 scopus 로고    scopus 로고
    • Epileptic EEG detection using neural networks and post-classification
    • Patnaik, L. M., and Manyam, O. K., Epileptic EEG detection using neural networks and post-classification. Comput. Methods Programs Biomed. 91:100-109, 2008.
    • (2008) Comput. Methods Programs Biomed. , vol.91 , pp. 100-109
    • Patnaik, L.M.1    Manyam, O.K.2
  • 10
    • 22144480299 scopus 로고    scopus 로고
    • Epileptic seizure detection using dynamic wavelet network
    • DOI 10.1016/j.eswa.2005.04.007, PII S0957417405000606
    • Subasi, A., Epileptic seizure detection using dynamic wavelet network. Expert Systems Appl. 29:343-355, 2005. (Pubitemid 40982998)
    • (2005) Expert Systems with Applications , vol.29 , Issue.2 , pp. 343-355
    • Subasi, A.1
  • 12
    • 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
    • Subasi, A., EEG signal classification using wavelet feature extraction and a mixture of expert model. Expert Systems Appl. 32:1084-1093, 2007. (Pubitemid 44821797)
    • (2007) Expert Systems with Applications , vol.32 , Issue.4 , pp. 1084-1093
    • Subasi, A.1
  • 14
    • 16844376435 scopus 로고    scopus 로고
    • Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real-time application
    • DOI 10.1016/j.compbiomed.2004.05.001
    • Kiymik, K., İnan, G., Dizibüyük, A., and Akin, M., Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real time application. Comput. Biol. Med. 35(7):603-616, 2004. (Pubitemid 40487489)
    • (2005) Computers in Biology and Medicine , vol.35 , Issue.7 , pp. 603-616
    • Kiymik, M.K.1    Guler, I.2    Dizibuyuk, A.3    Akin, M.4
  • 15
    • 17744374301 scopus 로고    scopus 로고
    • Classification of EEG signals using neural network and logistic regression
    • DOI 10.1016/j.cmpb.2004.10.009
    • Subasi, A., and Erçelebi, E., Classification of EEG Signals Using Neural Network and Logistic Regression. Comput. Methods Programs Biomed. 78(2):87-99, 2005. (Pubitemid 40575687)
    • (2005) Computer Methods and Programs in Biomedicine , vol.78 , Issue.2 , pp. 87-99
    • Subasi, A.1    Ercelebi, E.2
  • 18
    • 17844371713 scopus 로고    scopus 로고
    • Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients
    • DOI 10.1016/j.eswa.2004.12.027, PII S0957417404001745
    • Subasi, A., Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients. Expert Systems Appl. 28:701-711, 2005. (Pubitemid 40583848)
    • (2005) Expert Systems with Applications , vol.28 , Issue.4 , pp. 701-711
    • Subasi, A.1
  • 20
    • 0029379261 scopus 로고
    • Determining mental state from EEG signals using neural networks
    • Anderson, C. W., Devulapalli, S. V., and Stolz, E. A., Determining mental state from EEG signals using neural networks. Sci. Program. 4:171-183, 1995.
    • (1995) Sci. Program. , vol.4 , pp. 171-183
    • Anderson, C.W.1    Devulapalli, S.V.2    Stolz, E.A.3
  • 21
    • 2142771128 scopus 로고    scopus 로고
    • Neural Networks, http://www.doc.ic.ac.uk∼nd/surprise-96/Journal/vol4/ cs11/report.html, 2007.
    • (2007) Neural Networks
  • 22
    • 78650263676 scopus 로고    scopus 로고
    • An introduction to wavelet theory and analysis
    • NM, October: 1-25
    • Miner, N. E., An introduction to wavelet theory and analysis. Sandia Report, NM, October: 1-25, 1998.
    • (1998) Sandia Report
    • Miner, N.E.1
  • 26
    • 26944458497 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients
    • DOI 10.1016/j.jneumeth.2005.04.013, PII S0165027005001172
    • Güler, İ., and Übeyli, E. D., Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients. J. Neurosci. Methods 148:113-121, 2005. (Pubitemid 41476221)
    • (2005) Journal of Neuroscience Methods , vol.148 , Issue.2 , pp. 113-121
    • Guler, I.1    Ubeyli, E.D.2
  • 27
    • 34547682093 scopus 로고    scopus 로고
    • Applying artificial neural networks to the diagnosis of organic dyspepsia
    • DOI 10.1177/0962280206071839
    • García-Altés, A., Santín, D., and Barenys, M., Applying artificial neural networks to the diagnosis of organic dyspepsia. Stat. Methods Med. Res. 16:331-346, 2007. (Pubitemid 47215257)
    • (2007) Statistical Methods in Medical Research , vol.16 , Issue.4 , pp. 331-346
    • Garcia-Altes, A.1    Santin, D.2    Barenys, M.3
  • 28
    • 77954391575 scopus 로고    scopus 로고
    • Studies on the application of different ANNs to predict permeate flux in rotating disk membrane modules: A case study with MATLAB™
    • Bhattacharjee, C., Sen, D., Sarkar, P., Data, S., and Bhattacharya, P. K., Studies on the application of different ANNs to predict permeate flux in rotating disk membrane modules: A case study with MATLAB™. Desalination and Water Treatment 2:170-184, 2009.
    • (2009) Desalination and Water Treatment , vol.2 , pp. 170-184
    • Bhattacharjee, C.1    Sen, D.2    Sarkar, P.3    Data, S.4    Bhattacharya, P.K.5
  • 30
    • 46149087741 scopus 로고    scopus 로고
    • Analysis of principal component analysis-based and fisher discriminant analysis-based face recognition algorithms
    • 13-14 November
    • Naz, E., Farooq, U., Naz, T., Analysis of principal component analysis-based and fisher discriminant analysis-based face recognition algorithms. 2nd International Conference on Emerging Technologies Peshawar, Pakistan, 13-14 November 2006.
    • (2006) 2nd International Conference on Emerging Technologies Peshawar, Pakistan
    • Naz, E.1    Farooq, U.2    Naz, T.3
  • 31
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to ROC analysis
    • Fawcett, T., An introduction to ROC analysis. Pattern Recognit. Lett. 27:861-874, 2006.
    • (2006) Pattern Recognit. Lett. , vol.27 , pp. 861-874
    • Fawcett, T.1
  • 32
    • 0018079655 scopus 로고
    • Basic principles of ROC analysis
    • Metz, C. E., Basic principles of ROC analysis. Sem Nuc Med. 283-298, 1978. (Pubitemid 9075026)
    • (1978) Seminars in Nuclear Medicine , vol.8 , Issue.4 , pp. 283-298
    • Metz, C.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.