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[34] Fasil OK, Rajesh R, Thasleema TM.
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In: 2017 IEEE Region 10 Humanitarian
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IEEE; 2017. pp. 646–649
[35] Accardo A, Affinito M, Carrozzi M,
Bouquet F. Use of the fractal dimension
for the analysis of
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Biological Cybernetics. 1997;77(5):
339-350
[36] Mardi Z, Ashtiani SN, Mikaili M.
EEG-based drowsiness detection for
safe driving using chaotic features and
statistical tests. Journal of Medical
Signals and Sensors. 2011;1(2):130
[37] Acharya R, Faust O, Kannathal N,
Chua T, Laxminarayan S. Non-linear
analysis of EEG signals at various sleep
stages. Computer Methods and
Programs in Biomedicine. 2005;80(1):
37-45
[38] Ocak H. Automatic detection of
epileptic seizures in EEG using discrete
wavelet transform and approximate
entropy. Expert Systems with
Applications. 2009;36(2):2027-2036
[39] Kumar Y, Dewal ML, Anand RS.
Epileptic seizures detection in EEG
using DWT-based ApEn and artificial
neural network. Signal, Image and
Video Processing. 2014;8(7):1323-1334
[40] Guo L, Rivero D, Seoane JA,
Pazos A. Classification of EEG signals
using relative wavelet energy and
artificial neural networks. In:
Proceedings of the First ACM/SIGEVO
Summit on Genetic and Evolutionary
Computation; ACM; 2009. pp. 177–184
[41] Li M, Chen W, Zhang T.
Classification of epilepsy EEG signals
using DWT-based envelope analysis and
neural network ensemble. Biomedical
Signal Processing and Control. 2017;31:
357-365
[42] Kumar Y, Dewal ML, Anand RS.
Epileptic seizure detection using DWT
based fuzzy approximate entropy and
support vector machine.
Neurocomputing. 2014;133:271-279
[43] Liu Y, Zhou W, Yuan Q, Chen S.
Automatic seizure detection using
wavelet transform and SVM in longterm intracranial EEG. IEEE
Transactions on Neural Systems and
Rehabilitation Engineering. 2012;20(6):
749-755
[44] Mohammadi Z, Frounchi J,
Amiri M. Wavelet-based emotion
recognition system using EEG signal.
Neural Computing and Applications.
2017;28(8):1985-1990
[45] Silveira TD, Kozakevicius AD,
Rodrigues CR. Drowsiness detection for
single channel EEG by DWT best
m-term approximation. Research on
Biomedical Engineering. 2015;31(2):
107-115
77
Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures
DOI: http://dx.doi.org/10.5772/intechopen.89017
Statistical Mechanics and its
Applications. 2004;341:649-676
[32] Liang Z, Wang Y, Sun X, Li D,
Voss LJ, Sleigh JW, et al. EEG entropy
measures in anesthesia. Frontiers in
Computational Neuroscience. 2015;9:16
[33] Inuso G, La Foresta F, Mammone N,
Morabito FC. Brain activity
investigation by EEG processing:
Wavelet analysis, kurtosis and Renyi’s
entropy for artifact detection. In: 2007
International Conference on
Information Acquisition; IEEE; 2007.
pp. 195–200
[34] Fasil OK, Rajesh R, Thasleema TM.
Influence of differential features in focal
and non-focal EEG signal classification.
In: 2017 IEEE Region 10 Humanitarian
Technology Conference (R10-HTC);
IEEE; 2017. pp. 646–649
[35] Accardo A, Affinito M, Carrozzi M,
Bouquet F. Use of the fractal dimension
for the analysis of
electroencephalographic time series.
Biological Cybernetics. 1997;77(5):
339-350
[36] Mardi Z, Ashtiani SN, Mikaili M.
EEG-based drowsiness detection for
safe driving using chaotic features and
statistical tests. Journal of Medical
Signals and Sensors. 2011;1(2):130
[37] Acharya R, Faust O, Kannathal N,
Chua T, Laxminarayan S. Non-linear
analysis of EEG signals at various sleep
stages. Computer Methods and
Programs in Biomedicine. 2005;80(1):
37-45
[38] Ocak H. Automatic detection of
epileptic seizures in EEG using discrete
wavelet transform and approximate
entropy. Expert Systems with
Applications. 2009;36(2):2027-2036
[39] Kumar Y, Dewal ML, Anand RS.
Epileptic seizures detection in EEG
using DWT-based ApEn and artificial
neural network. Signal, Image and
Video Processing. 2014;8(7):1323-1334
[40] Guo L, Rivero D, Seoane JA,
Pazos A. Classification of EEG signals
using relative wavelet energy and
artificial neural networks. In:
Proceedings of the First ACM/SIGEVO
Summit on Genetic and Evolutionary
Computation; ACM; 2009. pp. 177–184
[41] Li M, Chen W, Zhang T.
Classification of epilepsy EEG signals
using DWT-based envelope analysis and
neural network ensemble. Biomedical
Signal Processing and Control. 2017;31:
357-365
[42] Kumar Y, Dewal ML, Anand RS.
Epileptic seizure detection using DWT
based fuzzy approximate entropy and
support vector machine.
Neurocomputing. 2014;133:271-279
[43] Liu Y, Zhou W, Yuan Q, Chen S.
Automatic seizure detection using
wavelet transform and SVM in longterm intracranial EEG. IEEE
Transactions on Neural Systems and
Rehabilitation Engineering. 2012;20(6):
749-755
[44] Mohammadi Z, Frounchi J,
Amiri M. Wavelet-based emotion
recognition system using EEG signal.
Neural Computing and Applications.
2017;28(8):1985-1990
[45] Silveira TD, Kozakevicius AD,
Rodrigues CR. Drowsiness detection for
single channel EEG by DWT best
m-term approximation. Research on
Biomedical Engineering. 2015;31(2):
107-115
77
Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures
DOI: http://dx.doi.org/10.5772/intechopen.89017