[
Andrzejak R.G., Schindler K., Rummel K., Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients, American Physical Society, 86:046206, 2012.
]Search in Google Scholar
[
Arunkumara N., Kumara K.R., Venkataraman V., Entropy features for focal EEG and non- focal EEG, Journal of Computational Science, 2018.
]Search in Google Scholar
[
Berg A.T., Millichap J.J., The 2010 revised classification of seizures and epilepsy, Continuum (Minneap Minn), 19:571-597, 2013.
]Search in Google Scholar
[
Chang R.S.K., Leung C.Y.W., Ho C.C.A., Yung A., Classifications of seizures and epilepsies, where are we? – A brief historical review and update, Journal of the Formosan Medical Association, 2017; 116(10):736-741.
]Search in Google Scholar
[
Cherian R., Kanaga E.G., Theoretical and methodological analysis of EEG based seizure detection and prediction: An exhaustive review, Journal of Neuroscience Methods, 369:109483, 2022.
]Search in Google Scholar
[
Chua C.K., Chandran V., Acharya U.R, Lim C.M, Higher order spectral (HOS) analysis of epileptic EEG signals, In Proceedings 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 6495-6498, 2007.
]Search in Google Scholar
[
Chua C.K., Chandran V., Acharya U.R., Lim C.M., Analysis of epileptic EEG signals using higher order spectra, J. Med. Eng. Technol, 33(1):42-50, 2009.
]Search in Google Scholar
[
Das A.B., Bhuiyan M.I.H., Discrimination and classification of focal and non-focal EEG signals using entropy-based features in the EMD-DWT domain, Biomedical Signal Processing and Control, 29:11-21, 2016.
]Search in Google Scholar
[
Delgado R., Tibau X.A., Why Cohen’s Kappa should be avoided as performance measure in classification, Plos One, 2019.
]Search in Google Scholar
[
Fisher R.S., Boas V.E., Blume W., Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE), Epilepsia, 46(4):470-472, 2005.
]Search in Google Scholar
[
Goutte C., Gaussier E., A Probabilistic Interpretation of Precision, Recall and F-score, with Implication for Evaluation, Proceedings of the European Colloquium on IR Resarch, 345-359, 2005.
]Search in Google Scholar
[
Gupta V., Pachori R.B., Classification of focal EEG signals using FBSE based flexible time-frequency coverage wavelet transform, Biomedical Signal Processing and Control, 62:102124, 2020.
]Search in Google Scholar
[
Gupta V., Priya T., Yadav A.K., Pachori R.B., Acharya U.R., Automated detection of focal EEG signals using features extracted from flexible analytic wavelet transform, Pattern Recognit. Lett. 94, 180-188, 2017.
]Search in Google Scholar
[
Hasan T.F., Tatum W.O., When should obtain a routine EEG while managing people with epilepsy? Epilepsy & Behavior Reports, 16:2-20, 2021.
]Search in Google Scholar
[
Hosseini S.A., A Hybrid Approach Based on Higher Order Spectra for Clinical Recognition of Seizure and Epilepsy Using Brain Activity, Neuro Science, 8:479-492, 2017.
]Search in Google Scholar
[
Hrisca-Eva O.D., Murariu M.G., Lazar A.M., Higher Order Statistics and Phase Synchronization as Features in a Motor Imagery Paradigm, International Journal of Advanced Computer Science and Applications, vol. 12, no. 8, pp.128-133, 2021.
]Search in Google Scholar
[
Lai W.C, Chang T.P, Wang J.J., Kan C.W., Chen W.W., An evaluation of Mahalanobis Distance and grey relational analysis for crack pattern in concrete structures, Computational Materials Science, 2012.
]Search in Google Scholar
[
Lim C.M., Chua K.C., Chandran V., Acharya U.R., Application of Higher Order Spectra to Identify Epileptic EEG, Springer Science+Business Media, LLC, 35:1563-1571, 2010.
]Search in Google Scholar
[
Martinez-del-Rincon J., Santofimia J., Xavier del Toro, Barba J., Romero F., Navas P., Lopez J. C., Non-linear classifiers applied to EEG analysis for epilepsy seizure detection, Expert Systems with Applications, Pages 99-112, 2017.
]Search in Google Scholar
[
Narin A., Detection of Focal and Non-focal epileptic seizure using continuous Wavelet Transform-based scalogram images and pre-trained Deep Neural Networks, IRBM, 43(1): 22-31, 2022.
]Search in Google Scholar
[
No author listed, Proposal for revised clinical and electroencephalographic classification of epileptic seizures, From the Commission on Classification and Terminology of the International League Against Epilepsy, Epilepsia, 22:489e501, 1981.
]Search in Google Scholar
[
Oliva J.T., Rosa J.L.G., Classification for EEG report generation and epilepsy detection, Neurocomputing, 335: 81-95, 2019.
]Search in Google Scholar
[
Prendergast L.A., Smith J.A., Influence functions for linear discriminant analysis: Sensitivity analysis and efficient influence diagnostics, Journal of Multivariate Analysis, 190:104993, 2022.
]Search in Google Scholar
[
Rai K., Bajaj V., Kumar A., Features extraction for classification of focal and non-focal EEG signals, Information Science and Applications, 599-605, 2015.
]Search in Google Scholar
[
Rezaei N., Abbari J.P., Chapter 8 - Linear and quadratic discriminant analysis in R, Immunoinformatics of Cancers, Pages 127-142, 2022.
]Search in Google Scholar
[
Rivola A., White P.R., Detecting system non-linearities by means of Higher order statistics, Institute of Sound and Vibration Research - University of Southampton – Southampton, 2002.
]Search in Google Scholar
[
Seyed A.K., Sankar R., Applications of Higher Order Statistics in Electroencephalography Signal Processing: A Comprehensive Survey, IEEE Reviews in Biomedical Engineering, 13:1-15, 2020.
]Search in Google Scholar
[
Sharma R., Pachori R.P., Empirical Mode Decomposition based Classification of Focal and Non-focal EEG Signals, International Conference on Medical Biometrics. IEEE Computer Society, 2014.
]Search in Google Scholar
[
Sriraam N., Raghu S., Classification of Focal and Non-Focal Epileptic Seizures Using Multi-Features and SVM Classifier, Image & Signal Processing, 2017.
]Search in Google Scholar
[
Steriade C., Sperling M.R., DiVentura B., Lozano M., Proposal for an updated seizure classification framework in clinical trials, Epilepsia, 2021.
]Search in Google Scholar
[
Subasi A., Jukic S., Kevri J., Comparison of EMD, DWT and WPD for the localization of epileptogenic foci using Random Forest classifier, Measurement, 146:846-855, 2019.
]Search in Google Scholar
[
Swami A., Mendel J.M., Chrysostomos L., Nikias M., Higher-Order Spectral Analysis Toolbox. For Use with MATLAB - Polyspectra and Linear Processes, 2:12-55, 2001.
]Search in Google Scholar
[
Ullah I, Hussain M., Qazi E.H., Aboalsamh H., An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach, College of Computer and Information Science, 107:61-71, 2018.
]Search in Google Scholar
[
Vries Z., Locke E, Hoda M., Using a national surgical database to predict complications following posterior lumbar surgery and comparing the area under the curve and F1-score for the assessment of prognostic capability, The Spine Journal 21:1135-1142, 2021.
]Search in Google Scholar
[
Who, Epilepsy, 2017 https://www.who.int/news-room/fact-sheets/detail/epilepsy.
]Search in Google Scholar
