Classification of Normal and Epileptic Seizure EEG Signals Based on Empirical Mode Decomposition - Complex System Modelling and Control Through Intelligent Soft Computations

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Mukhopadhyay, S., & Ray, G. C. (1998). A new interpretation of nonlinear energy operator and its

ef cacy in spike detection. IEEE Transactions on Biomedical Engineering, 45(2), 180 - 187.

Ngugi, A. K., Bottomley, C., Kleinschmidt, I., Sander, J. W., & Newton, C. R. (2010). Estimation

of the burden of active and life-time epilepsy: A meta-analytic approach. Epilepsia, 51,

883 - 890.

Nigam, V. P., & Graupe, D. (2004). A neural-network-based detection of epilepsy. Neurological

Research, 26,55

60.

Ocak, H. (2009). Automatic detection of epileptic seizures in EEG using discrete wavelet

transform and approximate entropy. Expert Systems with Applications, 36(2), 2017

2036.

Oweis, R. J., & Abdulhay, E. W. (2011). Seizure classification in EEG signals utilizing Hilbert-

Huang transform. BioMedical Engineering Online, 10, 38.

Pachori, R. B. (2008). Discrimination between ictal and seizure-free EEG signals using empirical

mode decomposition. Research Letters in Signal Processing, 293056,5p.

Pachori, R. B., & Bajaj, V. (2011). Analysis of normal and epileptic seizure EEG signals using

empirical mode decomposition. Computer Methods and Programs in Biomedicine, 104(3),

373 - 381.

Pachori, R. B., Hewson, D., Snoussi, H., & Duch ê ne, J. (2009). Postural time-series analysis using

empirical mode decomposition and second-order difference plots. In IEEE International

Conference on Acoustics, Speech and Signal Processing (pp. 537 - 540), Taipei, Taiwan, 19 - 24

Apr 2009.

Pachori, R. B., & Patidar, S. (2014). Epileptic seizure classi cation in EEG signals using second-

order difference plot of intrinsic mode functions. Computer Methods and Programs in

Biomedicine, 113(2), 494

502.

Pachori, R. B., & Sircar, P. (2008). EEG signal analysis using FB expansion and second-order

linear TVAR process. Signal Processing, 88(2), 415

420.

Polat, K., & G

, S. (2007). Classification of epileptiform EEG using a hybrid system based on

decision tree classifier and fast Fourier transform. Applied Mathematics and Computation, 187

(2), 1017

1026.

Prieto, T. E., Myklebust, J. B., Hoffmann, R. G., Lovett, E. G., & Mykelbust, B. M. (1996).

Measures of postural steadiness: Differences between healthy young and elderly adults. IEEE

Transactions on Biomedical Engineering, 43(9), 956

966.

Ramsay, R. E., Rowan, A. J., & Pryor, F. M. (2004). Special considerations in treating the elderly

patient with epilepsy. Neurology, 62(5 suppl 2), S24

S29.

Ray, G. C. (1994). An algorithm to separate nonstationary part of a signal using mid-prediction

filter. IEEE Transactions on Signal Processing, 42(9), 2276 - 2279.

Schomer, D. L., & da Silva, F. L. (Eds.) (2005). Electroencephalography: Basic Principles,

Clinical Applications, and Related Fields. Philadelphia: Lippincot Williams & Wilkins.

Senthil, P. K., Arumuganathan, R., Sivakumar, K., & Vimal, C. (2008). Removal of artifacts from

EEG signals using adaptive

filter through wavelet

transform. In 9th IEEE International

2141).

Sharma, R., Pachori, R. B., & Gautam, S. (2014). Empirical mode decomposition based

classification of focal and non-focal EEG signals. In IEEE International Conference on

Medical Biometrics (pp. 135

Conference on Signal Processing, 2008 (pp. 2138

01 June 2014.

Srinivasan, V., Eswaran, C., & Sriraam, N. (2005). Artificial neural network based epileptic

detection using time

140), Shenzhen, China, 30 May

domain and frequency

domain features. Journal of Medical Systems, 29

660.

Srinivasan, V., Eswaran, C., & Sriraam, N. (2007). Approximate entropy-based epileptic EEG

detection using arti cial neural networks. IEEE Transactions on Information Technology in

Biomedicine, 11(3), 288

(6), 647

295.

Subasi, A. (2007). EEG signal classi cation using wavelet feature extraction and a mixture of

expert model. Expert Systems with Applications, 32(4), 1084 - 1093.

Subasi, A., & Gursoy, M. I. (2010). EEG signal classi cation using PCA, ICA, LDA and support

vector machine. Expert Systems with Applications, 37(12), 8659 - 8666.

Complex System Modelling and Control Through Intelligent Soft Computations

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