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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:

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...

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.

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,...

Seizures ll: Types

Seizures ll: Types

Seizures are sudden bursts of abnormal electrical discharge in the brain that interfere with normal function. They are commonly divided into three groups: focal seizures, generalized seizures, and other types that do not fit neatly into either category.Focal SeizuresFocal seizures begin in a single brain region. When awareness is preserved, they are called focal aware seizures and may cause sensations such as tingling, unusual smells, or flashing lights. When awareness is impaired, they are...

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Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

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Published on: December 18, 2016

Epileptic seizure prediction using phase synchronization based on bivariate empirical mode decomposition.

Yang Zheng¹, Gang Wang¹, Kuo Li²

¹The Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, National Engineering Research Center of Health Care and Medical Devices, Xi'an Jiaotong University Branch, Xi'an 710049, PR China.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology

|December 4, 2013

Summary

This study introduces a novel seizure prediction algorithm using phase synchronization of brain activity. The method effectively detects pre-seizure changes, offering a promising tool for epilepsy management.

Keywords:

Bivariate empirical mode decomposition Electroencephalogram Phase synchronization Seizure prediction

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Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

Area of Science:

Neurology
Biomedical Engineering
Signal Processing

Background:

Epilepsy is a common neurological disorder characterized by unpredictable seizures.
Effective seizure prediction is crucial for managing refractory epilepsy.

Purpose of the Study:

To develop and evaluate a novel seizure prediction algorithm based on phase synchronization of neuronal electrical activity.
To assess the algorithm's effectiveness compared to existing methods.

Main Methods:

Utilized bivariate empirical mode decomposition (BEMD) and Hilbert transformation to detect the instantaneous phase of intracranial electroencephalograph (EEG) recordings.
Calculated mean phase coherence (MPC) to quantify phase coupling strength between EEG channels.
Analyzed preictal changes in MPC time courses for seizure alarm generation.

Main Results:

Identified both increases and decreases in phase synchronization preceding seizure onset.
The proposed phase synchronization method demonstrated superior performance compared to two other prediction algorithms.
The algorithm effectively extracted pre-seizure phase synchrony changes.

Conclusions:

The developed algorithm accurately detects phase synchrony alterations before epileptic seizures.
Phase synchronization analysis using BEMD shows potential for clinical application in epilepsy prediction.