The aim of this paper is to develop an automated system for epileptic seizure prediction from intracranial EEG signals based on Hilbert-Huang transform (HHT) and Bayesian classifiers. Proposed system includes decomposition of the signals into intrinsic mode functions for obtaining features and use of Bayesian networks with correlation based feature selection for binary classification of preicta...

Temporal seizures due to hippocampal origins are very common among epileptic patients. Presented is a novel seizure prediction approach employing correlation and chaos theories. The early identification of seizure signature allows for various preventive measures to be undertaken. Electro-encephalography signals are spectrally broken down into the following sub-bands: delta; theta; alpha; beta; ...

Epilepsy is a condition that affects the brain and causes repeated seizures. Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the world’s population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. The cells in the brain, known as neurons, conduct electrical signals and communicate with each oth...

This writing (1) draws attention to the intricacies inherent to the pursuit of a universal seizure definition even when powerful, well-understood signal analysis methods are used to this end; (2) identifies this aim as a multi-objective optimization problem and discusses the advantages and disadvantages of adopting or rejecting a unitary seizure definition; and (3) introduces a probabilistic me...

BACKGROUND The number of patients suffering post-stroke seizure after ischemic stroke (PSSi) is quite considerable, especially because ischemic stroke is more prevalent than hemorrhage in the general population. This study aimed to determine the predicting factors for seizure recurrence in ischemic stroke survivors and develop a clinical scoring system for the prediction of risks for seizure re...

Epileptic seizures of mesial temporal origin are preceded by changes in signal properties detectable in the intracranial EEG. A series of computer algorithms designed to detect the changes in spatiotemporal dynamics of the EEG signals and to warn of impending seizures have been developed. In this study, we evaluated the performance of a novel adaptive threshold seizure warning algorithm (ATSWA)...

In this era, big data applications including biomedical are becoming attractive as the data generation and storage is increased in the last years. The big data processing to extract knowledge becomes challenging since the data mining techniques are not adapted to the new requirements. In this study, we analyse the EEG signals for epileptic seizure detection in the big data scenario using Rotati...

Improved understanding of the interaction between state of vigilance (SOV) and seizure onset has therapeutic potential. Six rats received injections of tetanus toxin (TeTX) in the ventral hippocampus that resulted in chronic spontaneous seizures. The distribution of SOV before 486 seizures was analyzed for a total of 19 d of recording. Rapid eye movement sleep (REM) and exploratory wake, both o...

PURPOSE Febrile seizure, the most common type of pediatric convulsive disorder, is a benign seizure syndrome distinct from epilepsy. However, as epilepsy is also common during childhood, we aimed to identify the prognostic factors that can predict epilepsy in children with febrile seizures. METHODS The study comprised 249 children at the Korea University Ansan Hospital who presented with febr...

Corresponding Author: Heydarian F. MD Pediatric ward,Ghaem hospital Mashhad Cell Phone: +98 915 5155126 Tel: +98 511 8012469 Email:[email protected] Abstract Objective Simple febrile seizures are the most common form of childhood seizures, often recurring within the first twenty-four hours. This study was conducted to determine the probable role of low serum sodium levels in predicting seiz...