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Seizures: Classification

Seizures: Classification

Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:

Seizures l: Introduction

Seizures l: Introduction

Understanding seizures and epilepsy relies on key definitions that help in recognizing, classifying, and managing these disorders. These definitions provide a framework for recognizing, classifying, and managing seizure disorders.DefinitionsA seizure is a sudden, abnormal burst of electrical activity in the brain that can cause changes in awareness, movement, sensation, or behavior, depending on the area involved. Epilepsy is a chronic condition characterized by recurrent, unprovoked seizures,...

Epilepsy ll: Types

Epilepsy ll: Types

Recurrent seizures, stemming from abnormal electrical activity in the brain, are the defining characteristic of epilepsy, a chronic neurological condition. Because seizure features vary greatly, epilepsy is classified using two systems: by seizure type and by epilepsy syndromes. These classifications enable clinicians to describe seizure patterns and select suitable treatment strategies.I. Classification by Seizure Type1. Focal EpilepsyFocal epilepsy begins in one hemisphere of the brain.

Epilepsy and Seizures: Overview

Epilepsy and Seizures: Overview

Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...

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Related Experiment Video

Updated: Jun 12, 2026

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

Published on: September 20, 2024

Time varying neonatal seizure localization.

W Deburchgraeve¹, P J Cherian, M De Vos

¹Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Postbox 02446, 3001 Leuven-Heverlee, Belgium. wouter.deburchgraeve@esat.kuleuven.be

Methods of Information in Medicine

|June 8, 2010

Summary

This summary is machine-generated.

This study introduces a new method using higher-order decomposition and SVD to pinpoint neonatal seizures in the brain. It offers reliable spatial and temporal seizure information from EEG data for easier interpretation.

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Last Updated: Jun 12, 2026

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

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Published on: September 20, 2024

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method

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Continuous Video Electroencephalogram during Hypoxia-Ischemia in Neonatal Mice

Published on: June 11, 2020

Area of Science:

Neonatal neurology
Computational neuroscience
Medical signal processing

Background:

Neonatal brain injury is often caused by oxygen deprivation (asphyxia).
Neonatal seizures are a primary indicator of neurological disorders in newborns.
Multichannel electroencephalogram (EEG) recordings are crucial for localizing seizure origins.

Purpose of the Study:

To objectively determine the scalp distribution of neonatal seizures.
To identify the timing and strength of dominant seizure sources within the brain.

Main Methods:

The study employs a novel approach combining higher-order CP-decomposition with singular value decomposition (SVD).

Main Results:

The method's effectiveness is demonstrated using both simulated and real neonatal seizure EEG data.
The technique successfully illustrates the spatial distribution and temporal dynamics of seizures.

Conclusions:

The proposed method reliably provides spatio-temporal seizure information from EEG.
It offers a clear overview of EEG activity during seizures, facilitating interpretation.