Machine learning-based EEG signals classification model for epileptic seizure detection

• Published in: Multimedia tools and applications Vol. 80; no. 12; pp. 17849 - 17877
• Main Authors: Aayesha, Qureshi, Muhammad Bilal, Afzaal, Muhammad, Qureshi, Muhammad Shuaib, Fayaz, Muhammad
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2021; Springer Nature B.V
• Subjects: Algorithms; Classification; Computer Communication Networks; Computer Science; Convulsions & seizures; Data Structures and Information Theory; Datasets; EEG; Electroencephalography; Epilepsy; Feature extraction; Machine learning; Multimedia Information Systems; Seizure detection; Seizures; Signal classification; Signal processing; Special Purpose and Application-Based Systems; Signal processing; Seizure detection; Epilepsy; EEG; Machine learning; Classification

The detection of epileptic seizures by classifying electroencephalography (EEG) signals into ictal and interictal classes is a demanding challenge, because it identifies the seizure and seizure-free states of an epileptic patient. In previous works, several machine learning-based strategies were int...