A review of epileptic seizure detection using machine learning classifiers

• Published in: Brain informatics Vol. 7; no. 1; pp. 5 - 18
• Main Authors: Siddiqui, Mohammad Khubeb, Morales-Menendez, Ruben, Huang, Xiaodi, Hussain, Nasir
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 25.05.2020; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Analysis; Applications of machine learning on epilepsy; Artificial Intelligence; Black-box and non-black-box classifiers; Brain; Classifiers; Cognitive Psychology; Computation by Abstract Devices; Computer Science; Convulsions & seizures; Electroencephalography; Epilepsy; Health Informatics; Machine learning; Nervous system diseases; Neurological diseases; Neurons; Neurosciences; Organs; Review; Seizure detection; Seizure localization; Seizures; Seizures (Medicine); Signal monitoring; Statistical features; Taxonomy; Seizure localization; Applications of machine learning on epilepsy; Seizure detection; Epilepsy; Black-box and non-black-box classifiers; EEG signals; Statistical features

Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human organs and generate signals. The monitoring of these brain signals is commonly done using Elec...