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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...

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.

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

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Seizure prediction for epilepsy using a multi-stage phase synchrony based system.

Christopher J James¹, Disha Gupta

¹Signal Processing and Control Group, ISVR, University of Southampton, SO171 BJ, UK. C.James@soton.ac.uk

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 8, 2009

Summary

This study presents a novel multi-stage system for seizure onset prediction in epilepsy. The system utilizes phase synchrony and advanced signal processing to achieve accurate predictions with a 35-65 minute window.

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Area of Science:

Neuroscience
Signal Processing
Epilepsy Research

Background:

Seizure onset prediction in epilepsy remains a significant challenge.
Various signal processing techniques are being explored for this purpose.

Purpose of the Study:

To develop and evaluate a multi-stage phase synchrony-based system for seizure onset prediction.
To leverage the advantages of multiple signal processing techniques within a unified framework.

Main Methods:

Utilized spatially constrained Independent Component Analysis (ICA) for unmixing long-term scalp EEG data.
Estimated phase synchrony dynamics of narrowband seizure components (2-8 Hz and 8-14 Hz).
Employed Neuroscale for dimensionality reduction and Gaussian Mixture Models (GMMs) for event probability evaluation.

Main Results:

Demonstrated the feasibility of seizure onset prediction.
Achieved prediction sensitivities ranging from 65% to 100%.
Reported specificities between 65% and 80% across epileptic patients.

Conclusions:

The proposed multi-stage phase synchrony system shows promise for clinical application in epilepsy management.
The system offers a viable approach for predicting seizure onset with a substantial prediction window.