Detection of epileptic electroencephalogram based on Permutation Entropy and Support Vector Machines

By N. Nicolaou, J. Georgiou. Expert systems with applications, 2012

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Epileptic Seizure Classification of EEG Time-Series Using Rational Discrete Short-Time Fourier Transform (2015, unknown): “Nicoletta and Georgiou (2012) [42] E-B 82.”
An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach (2018, background): “Nicolaou et al. (Nicolaou et al., 2012) extracted the permutation entropy feature from EEG signals.”
Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review (2012, background): “Nicolaou and Georgiou [78] investigated the use of permutation entropy as a feature for automated epileptic seizure detection.”
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review (2022, methodology): “Among the nonlinear dynamic methods are permutation entropy [103], approximate entropy [104], singular value decomposition entropy, power spectrum entropy [105] and sample entropy [106].”