Epilepsy eeg: Difference between revisions

Jump to navigation Jump to search
VisualWikitext
m (Bot: Removing from Primary care)
 
(15 intermediate revisions by 3 users not shown)
Line 1: Line 1:
__NOTOC__
__NOTOC__
{{Epilepsy}}
{{Epilepsy}}
{{CMG}} {{AE}} {{VVS}}
{{CMG}}; {{AE}} {{Fs}}
== EEG ==
=== Electrophysiology ===


Most epileptics seize without warning, and their seizures can have dangerous or fatal consequences, if they come at a bad time and lead to an accident.  In the brain, identifiable electrical changes precede the clinical onset of a seizure by tens of seconds, and these changes can be recorded in an [[electroencephalogram]] ([[EEG]]).  Many people have wondered if EEG’s might be used to predict seizures minutes or even hours ahead of time, but as of now, this sort of prediction has not been feasible.  Many researchers are working, however, to create a system capable of detecting seizures before they clinically manifest themselves.
== Overview ==
An [[EEG]] may be helpful in the diagnosis of epilepsy. Findings on an [[EEG]] suggestive of epilepsy include synchronous generalized spikes and waves in all leads in [[Tonic-clonic seizure|tonic-clonic seizures]], spike and wave activity at a frequency of approximately 3 HZ in [[Absence seizure|absence seizures]], localized epileptic activity over the [[seizure]] focus in [[focal seizures]] with intact [[consciousness]] and [[temporal]] slow waves or spikes in [[focal seizures]] with impaired [[consciousness]].


The early detection of a seizure has many potential benefits.  Advanced warning would allow patients to take action to minimize their risk of injury and, in some circumstances, would allow them to summon help.  An automatic detection system could also be made to trigger pharmacological intervention in the form of fast-acting drugs or [[electrical stimulation]].
== Electroencephalogram ==
An [[EEG]] may be helpful in the diagnosis of epilepsy. Findings on an [[EEG]] suggestive of epilepsy include:<ref name=":0">{{cite book | last = Mattle | first = Heinrich | title = Fundamentals of neurology : an illustrated guide | publisher = Thieme | location = Stuttgart New York | year = 2017 | isbn = 9783131364524 }}</ref>


It is relatively easy to place the [[electrodes]] needed to record an EEG, but it has not been so easy to develop an [[algorithm]] to detect the onset of a seizure. For any given patient, assuming his or her seizures originate in one focus, seizure-onset EEG patterns are largely conserved from one seizure episode to the next.  Unfortunately, there is great EEG variation between patients, both in terms of baseline and in terms of seizure-onset patterns.  This variation has made the development of a generic, “one-size-fits-all” algorithm difficult.


Patient-specific algorithms based on [[machine learning]] have shown more promise.  Machine learning algorithms compute [[binary decision trees]] from manually labeled training sets of data.  EEG data must be translated into a format that the computer can interpret.  Important information must be kept while superfluous information must be discarded.  Although there are many conceivable ways of performing this “[[feature extraction]],” wavelet decomposition seems to be an effective way of extracting pertinent information from EEG signals.


The training set for the machine-learning algorithm must be labeled by hand. For an algorithm being developed by Dr. Schachter and Prof. Guttag of MIT, EEG recordings are split into two-second time windows, and each window is labeled as “seizure onset” or “not seizure onset.” 
{{Family tree/start}}
{{Family tree | | | | | | | | | | | | A01 | | | | | | | | | | A01=Epilepsy}}
{{Family tree | | | | | | | | |,|-|-|-|^|-|-|-|.| | | | | | | }}
{{Family tree | | | | | | | | B01 | | | | | | B02 | | | | | | B01=Generalized|B02=Focal}}
{{Family tree | | | | | | |,|-|^|-|.| | | |,|-|^|-|.| | | | | }}
{{Family tree | | | | | | C01 | | C02 | | C03 | | C04 | | | | C01=[[Tonic–clonic Seizure]]|C02=Absences|C03=Focal seizures without
altered consciousness|C04=[[Focal seizures]] with altered
[[consciousness]]}}
{{Family tree | | | | | | |!| | | |!| | | |!| | | |!| | | | | }}
{{Family tree | | | | | | D01 | | D02 | | D04 | | D05 | | | | D01=Synchronous generalized
spikes and waves in all leads|D02=Bursts of synchronous, generalized
spike-and-wave activity at a frequency of approximately
3 Hz|D04=Localized epileptic activity over the seizure
focus|D05=[[Temporal]] slow waves or spikes. In
the interictal period/Normal [[EEG]]}}
{{Family tree | | | | | | | | | | | | | | | | | | | | | | | | }}
{{Family tree | | | | | | | | | | | | | | | | | | | | | | | | }}
{{Family tree/end}}NOTE: Video-EEG monitoring is a combination of recording [[EEG]] and clinical behavior of the patient. Although, it's it's more expensive, it is more effective in differentiating different type if [[Seizure|seizures]].<ref name="pmid12233935">{{cite journal |vauthors=Worrell GA, Lagerlund TD, Buchhalter JR |title=Role and limitations of routine and ambulatory scalp electroencephalography in diagnosing and managing seizures |journal=Mayo Clin. Proc. |volume=77 |issue=9 |pages=991–8 |date=September 2002 |pmid=12233935 |doi=10.4065/77.9.991 |url=}}</ref>


The algorithm then takes the labeled training set and uses it to construct a decision tree capable of classifying unlabeled EEG patterns as “seizure onset” or “not seizure onset.”  The training set is unavoidably unbalanced because most time windows do not involve seizures. Certain algorithms, such as the support vector machine algorithm chosen by Schachter and Guttag, are better suited than others to handle this unbalanced training set.
{|
 
|
In the hospital, the patient-specific algorithm of Schachter and Guttag has worked fairly well.  In one trial, it detected 131 out of 139 seizures in 36 patients.  In another, it caught 53 out of 58 seizures.  The algorithm outperformed generic algorithms. 
[[File:EEG cap.jpg|400px|none|thumb|Transferred from en.wikipedia to Commons by Sreejithk2000 using CommonsHelper.]]
 
|
In the future, Dr. Schachter and Prof. Guttag hope to improve their algorithm so that it is less sensitive to electrode placement and so that it functions effectively with input from fewer electrodes and with smaller training sets. Their goal is to create an unobtrusive device that can be worn continually by epileptics to detect impending seizures. Such a device would greatly enhance the ability of these people to safely go about their lives.
[[File:Spike-waves.png|400px|none|thumb|Generalized 3 Hz spike and wave discharges in a child with childhood absence epilepsy/Uploaded from the German Wikipedia, uploaded into the German Wikipedia by Der Lange 11/6/2005, created by himself. http://commons.wikimedia.org/w/index.php?title=File:Spike-waves.png&action=edit&section=2]]
|}


==References==
==References==
Line 25: Line 41:
{{WH}}
{{WH}}
{{WS}}
{{WS}}
[[Category:Needs content]]
[[Category:Needs content]]
[[Category:Neurological disorders]]
[[Category:Neurological disorders]]
Line 31: Line 48:
[[Category:Pediatrics]]
[[Category:Pediatrics]]
[[Category:Emergency medicine]]
[[Category:Emergency medicine]]
[[Category:Primary care]]
[[Category:Signs and symptoms]]

Latest revision as of 21:37, 29 July 2020

Epilepsy Microchapters

Home

Patient Information

Overview

Historical Perspective

Classification

Pathophysiology

Causes

Differentiating Epilepsy from other Diseases

Epidemiology and Demographics

Risk Factors

Screening

Natural History, Complications and Prognosis

Diagnosis

Diagnostic Study of Choice

History and Symptoms

Physical Examination

Laboratory Findings

EEG

X Ray

CT

MRI

Echocardiography or Ultrasound

Other Imaging Findings

Other Diagnostic Studies

Treatment

Medical Therapy

Surgery

Primary Prevention

Secondary Prevention

Cost-Effectiveness of Therapy

Future or Investigational Therapies

Case Studies

Case #1

Epilepsy eeg On the Web

Most recent articles

Most cited articles

Review articles

CME Programs

Powerpoint slides

Images

American Roentgen Ray Society Images of Epilepsy eeg

All Images
X-rays
Echo & Ultrasound
CT Images
MRI

Ongoing Trials at Clinical Trials.gov

US National Guidelines Clearinghouse

NICE Guidance

FDA on Epilepsy eeg

CDC on Epilepsy eeg

Epilepsy eeg in the news

Blogs on Epilepsy eeg

Directions to Hospitals Treating Epilepsy

Risk calculators and risk factors for Epilepsy eeg

Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1]; Associate Editor(s)-in-Chief: Fahimeh Shojaei, M.D.

Overview

An EEG may be helpful in the diagnosis of epilepsy. Findings on an EEG suggestive of epilepsy include synchronous generalized spikes and waves in all leads in tonic-clonic seizures, spike and wave activity at a frequency of approximately 3 HZ in absence seizures, localized epileptic activity over the seizure focus in focal seizures with intact consciousness and temporal slow waves or spikes in focal seizures with impaired consciousness.

Electroencephalogram

An EEG may be helpful in the diagnosis of epilepsy. Findings on an EEG suggestive of epilepsy include:[1]


 
 
 
 
 
 
 
 
 
 
 
Epilepsy
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Generalized
 
 
 
 
 
Focal
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Tonic–clonic Seizure
 
Absences
 
Focal seizures without altered consciousness
 
Focal seizures with altered consciousness
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Synchronous generalized spikes and waves in all leads
 
Bursts of synchronous, generalized

spike-and-wave activity at a frequency of approximately

3 Hz
 
Localized epileptic activity over the seizure focus
 
Temporal slow waves or spikes. In the interictal period/Normal EEG
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

NOTE: Video-EEG monitoring is a combination of recording EEG and clinical behavior of the patient. Although, it's it's more expensive, it is more effective in differentiating different type if seizures.[2]

Transferred from en.wikipedia to Commons by Sreejithk2000 using CommonsHelper.
Generalized 3 Hz spike and wave discharges in a child with childhood absence epilepsy/Uploaded from the German Wikipedia, uploaded into the German Wikipedia by Der Lange 11/6/2005, created by himself. http://commons.wikimedia.org/w/index.php?title=File:Spike-waves.png&action=edit&section=2

References

  1. ↑ Mattle, Heinrich (2017). Fundamentals of neurology : an illustrated guide. Stuttgart New York: Thieme. ISBN 9783131364524.
  2. ↑ Worrell GA, Lagerlund TD, Buchhalter JR (September 2002). "Role and limitations of routine and ambulatory scalp electroencephalography in diagnosing and managing seizures". Mayo Clin. Proc. 77 (9): 991–8. doi:10.4065/77.9.991. PMID 12233935.

Template:WH Template:WS

Retrieved from "https://www.wikidoc.org/index.php?title=Epilepsy_eeg&oldid=1637863"