A Novel Machine Learning Model for the Detection of Epilepsy and Epileptic Seizures Using Electroencephalographic Signals Based on Chaos and Fractal Theories
Machine learning is an expanding research area. Its main application is in the medical field and particularly the detection of epilepsy and epileptic seizures through electroencephalographic signals (EEG). It aims to design an intelligent framework that enables an immediate diagnosis of this disease...
Main Authors: | Zayneb Brari, Safya Belghith |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2021-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/2107113 |
Similar Items
-
Temporal lobe epileptic seizures: clinical and electroencephalographic aspects
by: DANTAS FÁBIO GALVÃO
Published: (1998-01-01) -
Biomarkers of epileptic seizures and epilepsy
by: Bogdan Lorber, et al.
Published: (2013-07-01) -
THE CLINICAL AND ELECTROENCEPHALOGRAPHIC CHARACTERISTICS AND TREATMENT OF EPILEPTIC SYNDROMES ASSOCIATED WITH TONIC SEIZURES
by: K. Yu. Mukhin, et al.
Published: (2015-04-01) -
Electroencephalographic Correlates of Cognition among Nigerian Women with Epilepsy on Anti-epileptic Monotherapy
by: Ogunjimi LO, et al.
Published: (2021-05-01) -
Machine learning applications for electroencephalograph signals in epilepsy: a quick review
by: Yang Si
Published: (2020-04-01)