References
[1] Falco-Walter JJ, Scheffer IE,
Fisher RS. The new definition and
classification of seizures and epilepsy.
Epilepsy Research. 2018;139:73-79
[2] Saab ME, Gotman J. A system to
detect the onset of epileptic seizures in
scalp EEG. Clinical Neurophysiology.
2005;116(2):427-442
[3] Tzimourta KD, Tzallas AT,
Giannakeas N, Astrakas LG,
Tsalikakis DG, Tsipouras MG. Epileptic
seizures classification based on longterm EEG signal wavelet analysis. In:
Precision Medicine Powered by Health
and Connected Health. Singapore:
Springer; 2018. pp. 165-169
[4] Annegers JF, Coan SP. The risks of
epilepsy after traumatic brain injury.
Seizure. 2000;9(7):453-457
[5] Gupta A, Singh P, Karlekar M. A
novel signal modeling approach for
classification of seizure and seizure-free
EEG signals. IEEE Transactions on
Neural Systems and Rehabilitation
Engineering. 2018;26(5):925-935
[6] Kumar TS, Kanhangad V,
Pachori RB. Classification of seizure and
seizure-free EEG signals using local
binary patterns. Biomedical Signal
Processing and Control. 2015;15:33-40
[7] Huang NE, Shen Z, Long SR,
Wu MC, Shih HH, Zheng Q, et al. The
empirical mode decomposition and the
Hilbert spectrum for nonlinear and nonstationary time series analysis.
Proceedings of the Royal Society of
London, Series A: Mathematical,
Physical and Engineering Sciences.
1998;454(1971):903-995
[8] Nunes JC, Bouaoune Y, Delechelle E,
Niang O, Bunel P. Image analysis by
bidimensional empirical mode
decomposition. Image and Vision
Computing. 2003;21(12):1019-1026
[9] Zeng W, Yuan C, Wang Q, Liu F,
Wang Y. Classification of gait patterns
between patients with Parkinsons
disease and healthy controls using phase
space reconstruction (PSR), empirical
mode decomposition (EMD) and neural
networks. Neural Networks. 2019;111:
64-76
[10] Hasan NI, Bhattacharjee A. Deep
learning approach to cardiovascular
disease classification employing
modified ECG signal from empirical
mode decomposition. Biomedical Signal
Processing and Control. 2019;52:
128-140
[11] Mi X, Liu H, Li Y. Wind speed
prediction model using singular
spectrum analysis, empirical mode
decomposition and convolutional
support vector machine. Energy
Conversion and Management. 2019;180:
196-205
[12] Thilagaraj M, Rajasekaran MP. An
empirical mode decomposition (EMD)based scheme for alcoholism
identification. Pattern Recognition
Letters. 2019;125:133-139
[13] Hadoush H, Alafeef M, Abdulhay E.
Automated identification for autism
severity level: EEG analysis using
empirical mode decomposition and
second order difference plot.
Behavioural Brain Research. 2019;362:
240-248
[14] Ghritlahare R, Sahu M, Kumar R.
Classification of two-class motor
imagery EEG signals using empirical
mode decomposition and Hilbert-Huang
transformation. In: Computing and
Network Sustainability. Singapore:
Springer; 2019. pp. 375-386
[15] Gaur P, Pachori RB, Wang H,
Prasad G. A multi-class EEG-based BCI
classification using multivariate
75
Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures
DOI: http://dx.doi.org/10.5772/intechopen.89017
[1] Falco-Walter JJ, Scheffer IE,
Fisher RS. The new definition and
classification of seizures and epilepsy.
Epilepsy Research. 2018;139:73-79
[2] Saab ME, Gotman J. A system to
detect the onset of epileptic seizures in
scalp EEG. Clinical Neurophysiology.
2005;116(2):427-442
[3] Tzimourta KD, Tzallas AT,
Giannakeas N, Astrakas LG,
Tsalikakis DG, Tsipouras MG. Epileptic
seizures classification based on longterm EEG signal wavelet analysis. In:
Precision Medicine Powered by Health
and Connected Health. Singapore:
Springer; 2018. pp. 165-169
[4] Annegers JF, Coan SP. The risks of
epilepsy after traumatic brain injury.
Seizure. 2000;9(7):453-457
[5] Gupta A, Singh P, Karlekar M. A
novel signal modeling approach for
classification of seizure and seizure-free
EEG signals. IEEE Transactions on
Neural Systems and Rehabilitation
Engineering. 2018;26(5):925-935
[6] Kumar TS, Kanhangad V,
Pachori RB. Classification of seizure and
seizure-free EEG signals using local
binary patterns. Biomedical Signal
Processing and Control. 2015;15:33-40
[7] Huang NE, Shen Z, Long SR,
Wu MC, Shih HH, Zheng Q, et al. The
empirical mode decomposition and the
Hilbert spectrum for nonlinear and nonstationary time series analysis.
Proceedings of the Royal Society of
London, Series A: Mathematical,
Physical and Engineering Sciences.
1998;454(1971):903-995
[8] Nunes JC, Bouaoune Y, Delechelle E,
Niang O, Bunel P. Image analysis by
bidimensional empirical mode
decomposition. Image and Vision
Computing. 2003;21(12):1019-1026
[9] Zeng W, Yuan C, Wang Q, Liu F,
Wang Y. Classification of gait patterns
between patients with Parkinsons
disease and healthy controls using phase
space reconstruction (PSR), empirical
mode decomposition (EMD) and neural
networks. Neural Networks. 2019;111:
64-76
[10] Hasan NI, Bhattacharjee A. Deep
learning approach to cardiovascular
disease classification employing
modified ECG signal from empirical
mode decomposition. Biomedical Signal
Processing and Control. 2019;52:
128-140
[11] Mi X, Liu H, Li Y. Wind speed
prediction model using singular
spectrum analysis, empirical mode
decomposition and convolutional
support vector machine. Energy
Conversion and Management. 2019;180:
196-205
[12] Thilagaraj M, Rajasekaran MP. An
empirical mode decomposition (EMD)based scheme for alcoholism
identification. Pattern Recognition
Letters. 2019;125:133-139
[13] Hadoush H, Alafeef M, Abdulhay E.
Automated identification for autism
severity level: EEG analysis using
empirical mode decomposition and
second order difference plot.
Behavioural Brain Research. 2019;362:
240-248
[14] Ghritlahare R, Sahu M, Kumar R.
Classification of two-class motor
imagery EEG signals using empirical
mode decomposition and Hilbert-Huang
transformation. In: Computing and
Network Sustainability. Singapore:
Springer; 2019. pp. 375-386
[15] Gaur P, Pachori RB, Wang H,
Prasad G. A multi-class EEG-based BCI
classification using multivariate
75
Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures
DOI: http://dx.doi.org/10.5772/intechopen.89017