EEG-based epileptic seizure detection using binary dragonfly algorithm and deep neural network

• Published in: Scientific reports Vol. 13; no. 1; p. 17710
• Main Authors: Yogarajan, G., Alsubaie, Najah, Rajasekaran, G., Revathi, T., Alqahtani, Mohammed S., Abbas, Mohamed, Alshahrani, Madshush M., Soufiene, Ben Othman
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18.10.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/4077; 692/699; 692/700; Algorithms; Asymmetry; Convulsions & seizures; EEG; Electroencephalography; Epilepsy; Hemispheric laterality; Humanities and Social Sciences; multidisciplinary; Neural networks; Science; Science (multidisciplinary); Seizures; Symmetry; Wavelet transforms

Electroencephalogram (EEG) is one of the most common methods used for seizure detection as it records the electrical activity of the brain. Symmetry and asymmetry of EEG signals can be used as indicators of epileptic seizures. Normally, EEG signals are symmetrical in nature, with similar patterns on...