• Annals of Clinical Neurophysiology
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• v.9 no.2
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• pp.69-74
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• 2007

Electroencephalogram (EEG) is a representative diagnostic tool in epilepsy. However, there are several points of debate on the role of EEG in diagnosis and management of epilepsy. We suggest that EEG has some limitations for differential diagnosis from nonepileptic episodic diseases, classification of epilepsy, prediction of recurrence, and evaluation of treatment response. Interictal EEG cannot diagnose or exclude epilepsy because interictal epileptic discharge (IED) is frequently absent in epilepsy and can appear in nonepileptic conditions. Although EEG is helpful in classification of epilepsy, focal spikes in generalized epilepsy and secondary bilateral synchrony in localization related epilepsy cause interrater disagreement. It is controversial whether EEG predicts recurrence after the first seizure in adults. The predictive value of EEG in antiepileptic drug (AED) withdrawal is not absolute. The prognosis after AED withdrawal depends on epilepsy syndrome. Many studies could not confirm the value of EEG in assessing the treatment response. After all, epilepsy is clinically diagnosed and assessed. Interictal EEG alone does not provide decisive information and routine follow-up of EEG is not recommended.

• Korean Journal of Biological Psychiatry
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• v.8 no.2
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• pp.233-238
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• 2001

The routine interictal electroencephalogram(EEG) continues to play an important role in the diagnosis and treatment of epilepsy. The clinical investigation of brain disease in the last decade has been marked by dramatic advances in functional imaging, magnetic resonance scanning and digitized EEG. Epilepsy is a disorder of electrical hyperirritability of cerebral cortex and the interictal EEG remains the most convenient means available to demonstrate cortical hyperirritability. The sensitivity and specificity of the EEG in the diagnosis of epilepsy have been disputed. In this review, the type of EEG findings in epilepsy are reviewed and the sensitivity and specificity of interictal epileptiform discharge are discussed. And also the role of EEG in various clinical situations are summarized.

• Annals of Clinical Neurophysiology
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• v.9 no.2
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• pp.63-68
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• 2007

The EEG plays an important diagnostic role in epilepsy and provides supporting evidence of a seizure disorder as well as assisting with classification of seizures and epilepsy syndromes. There are a variety of electroclinical syndromes that are really defined by the EEG such as Lennox-Gastaut syndrome, benign rolandic epilepsy, childhood absence epilepsy, juvenile myoclonic epilepsy and also for localization purposes, it is vitally important especially for temporal lobe epilepsy. The sensitivity of first routine EEG in diagnosis of epilepsy has been known about 20-50%, but this proportion rises to 80-90% if sleep EEG and repetitive recording should be added. Convincing evidences suggest that the EEG may also provide useful prognostic information regarding seizure recurrence after a single unprovoked attack and following antiepileptic drug (AED) withdrawal. Moreover, patterns in the EEG make it possible to disclose an ictal feature of nonconvulsive status epilepticus, separate epileptic from other non-epileptic episodes and clarify the clues predictive of the cause of the encephalopathy (i.e., triphasic waves in metabolic encephalopathy). Therefore, regardless of its low sensitivity and other pitfalls, EEG should be considered not only in the situation of new onset episode such as a newly developed, unprovoked seizure or a condition manifesting decreased mentality from obscure origin, but also as a barometer of the long-term outcome following AED withdrawal.

• Biomedical Science Letters
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• v.18 no.4
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• pp.428-434
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• 2012

Epilepsy is a chronic neurological disease showing a symptom of repeated seizures without any other physical disorders. Among the diagnostic examination for epilepsy, the electroencephalogram (EEG) has been known as an important test. This study aimed to investigate the EEG with photic stimulation in the pediatric epilepsy patients. They underwent digital sleep and waking EEGs or waking EEGs with photic stimulation. Epilepsy type, seizure history, and season of occurring seizure were analyzed. Epilepsy patients showed more response during the period of photic-on and eye close at the frequency of 10~20 Hz during the EEG activation procedure. Photoparoxysmal response (PPR) was shown in 206 patients out of total 1,551 epilepsy patients. PPR was appeared more frequently during summer and winter seasons, and especially in the patients who had a history of seizure. During the PPR, EEG pattern showed spike (77.18%), theta (9.71%), and spike + theta (13.11%). On the other hand, beta and theta waves were not significantly changed by photic stimulation. However, alpha wave was decreased and delta wave was increased by photic stimulation (P<0.05). These changes may be due to temporarily altered electrophysiological function of the epileptic patient's brain by the photic stimulation. There was no difference in the EEG pattern between the left and right side in the brain. In conclusion, condition of photic-on with closed eyes and frequency of 10~20 Hz during the procedure of EEG activation could be appropriate for obtaining a definite photoparoxysmal response in the electroencephalogram of the pediatric epilepsy patients.

• Clinical and Experimental Pediatrics
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• v.54 no.1
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• pp.22-28
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• 2011

Purpose: To investigate the clinical characteristics of late-onset epilepsy combined with autism spectrum disorder (ASD), and the relationship between certain types of electroencephalography (EEG) abnormalities in ASD and associated neuropsychological problems. Methods: Thirty patients diagnosed with ASD in early childhood and later developed clinical seizures were reviewed retrospectively. First, the clinical characteristics, language and behavioral regression, and EEG findings of these late-onset epilepsy patients with ASD were investigated. The patients were then classified into 2 groups according to the severity of the EEG abnormalities in the background rhythm and paroxysmal discharges. In the severe group, EEG showed persistent asymmetry, slow and disorganized background rhythms, and continuous sharp and slow waves during slow sleep (CSWS). Results: Between the two groups, there was no statistically significant difference in mean age (P=0.259), age of epilepsy diagnosis (P=0.237), associated family history (P=0.074), and positive abnormal magnetic resonance image (MRI) findings (P=0.084). The severe EEG group tended to have more neuropsychological problems (P=0.074). The severe group statistically showed more electrographic seizures in EEG (P=0.000). Rett syndrome was correlated with more severe EEG abnormalities (P=0.002). Although formal cognitive function tests were not performed, the parents reported an improvement in neuropsychological function on the follow up checkup according to a parent's questionnaire. Conclusion: Although some ASD patients with late-onset epilepsy showed severe EEG abnormalities, including CSWS, they generally showed an improvement in EEG and clinical symptoms in the longterm follow up. In addition, severe EEG abnormalities tended to be related to the neuropsychological function.

• Annals of Clinical Neurophysiology
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• v.9 no.2
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• pp.59-62
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• 2007

Electroencephalogram (EEG) is an indispensable tool for diagnosis of epilepsy and is the only assisting barometer of complete remission of epilepsy, which means prolonged, persistent suppression of cortical excitement in epileptic focus in addition to the clinical control of epileptic seizure. The specific morphologies or distribution of epileptic form discharges give us good information for the classification of seizure or epilepsy and epileptic syndromes, which consists of "Pros." in terms of diagnostic approach. In contrast, the EEG as a tool for long-term follow up might be limited due to the various clinical situation of each patient, which consists of "Cons." in terms of the usefulness of EEG for clinical decision. "Cons." aspect of EEG, which clinicians are more frequently coped with than those of "Pros", is an obstacle of utilization of follow up EEG in clinical practice. This is an overview about controversies in usefulness of EEG and the detailed aspects of "Pros." and "Cons." of EEG for clinical decision will be discussed following two articles. We tried to make consensus for the usefulness of EEG especially in the situation of "Cons." with plausible guideline.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.25 no.3
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• pp.156-162
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• 2014

Objectives : The aim of this study was to estimate the prevalences of electroencephalographic (EEG) abnormalities and epilepsy in children and adolescents with autism spectrum disorder (ASD). In addition, we intended to identify demographic and clinical correlates of epilepsy in ASD. Methods : A total of 140 children and adolescents (age $7.3{\pm}4.8yrs$, 106 boys) with ASD underwent EEG from January 2010 to December 2013 at Asan Medical Center. Medical records were reviewed for demographic information, clinical characteristics, psychiatric diagnoses and comorbidities, EEG findings and neurological diagnoses. Results : The prevalences of EEG abnormalities and epilepsy in children and adolescents with ASD was 62.1% and 38.6%, respectively. In subjects with seizure-like movements, EEG abnormalities and epilepsy were more frequent than those without seizure-like movements (EEG abnormalities : 92.5% vs. 43.7%, p<.001 ; epilepsy : 90.6% vs. 5.7%, p<.001). ASD subjects who had epilepsy were older (p=.001), had lower full scale intelligence quotient (p<.001) and took more antipsychotics (p=.006) than those who did not. Conclusion : The prevalences of EEG abnormalities and epilepsy in our sample were similar to those from Western countries. Our results suggested a possible association of older age, lower intelligence quotient, and antipsychotics use with epilepsy in ASD. Conduct of further prospective study in a larger sample is needed.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.199-206
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• 2004

Epileptic seizures result from a temporary electrical disturbance of the brain. In this paper, a method of discriminating EEG for diagnoses of temporal lobe epilepsy is proposed. The proposed method for classification of epilepsy and sleep EEG is based on the wavelet transform and the fuzzy c-means. The magnitude and mean of wavelet coefficients for each EEG band are applied to the cluster of the FCM classifier. The proposed system show a little more accurate diagnosis for EEG by analysis of frequency for Wavelet and the success rate of 95% classification using FCM. From the simulation results by the implemented system, we demonstrated this research can be reduce doctor's labors and realize quantitative diagnosis of EEG.

• Korean Journal of Clinical Laboratory Science
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• v.48 no.4
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• pp.388-393
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• 2016

Epilepsy, characterized by enduring the predisposition to generate epileptic seizures, was conceptually defined in 2005 as a disorder of the brain. According to the international league against epilepsy in 2014 that there is a high risk of recurrence within 10 years. The existence of interictal epileptiform discharges (IEDs) at the Electroencephalography (EEG) is an important risk factor for a possible recurrence of seizures, disproving that the seizures may increase. The purpose of this study was to analyze the correlation between recurrent seizures and epilepsy EEG findings in patients with IEDs, which was carried out to serve as the basis for the EEG to predict the prognosis of patients with epilepsy. This study included 432 adults older than 20 years of age who care for patients with epilepsy at Seoul National University Hospital, between June 2007 and December 2010. The results showed no difference between men and women in the EEG epilepsy disease, but there was a difference between various age groups. Correlation analysis showed a negative correlation between recurrence of seizures and age; it showed a positive correlation between recurrence and IEDs. In addition, age was associated with a predictive power of 10.9% and IEDs showed a predictive power of 15% on recurrent seizures. Therefore, EEG is considered as a very important test in epilepsy diagnosis. Therefore, further studies are necessary on the relationship between seizure recurrence and EEG.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.4
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• pp.225-229
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• 2015

Epilepsy is a disorder that causes recurring seizures, and the most objective and useful test for detecting epilepsy is the electroencephalogram (EEG). The subjects of this study are 244 patients who received an EEG after being diagnosed with epilepsy at Seoul National University Hospital in 2014, and who have agreed to the purpose of the study. Based on the EEG results, subjects were divided into normal and abnormal groups with 122 subjects in each group, regardless of their gender and age, to investigate the correlation of EEG and complete blood cell count (CBC) test results. The four significant categories that displayed significant correlation between EEG results and CBC hematological measurements in this study were the white blood cell (WBC), red blood cell (RBC), neutrophil, and lymphocyte tests. The WBC (p<0.05) and neutrophil (p<0.01) showed a positive correlation with EEG results, while RBC (p<0.05) and lymphocyte (p<0.01) showed a negative correlation. One of the limitations of this study is that it is lacking the blood test result analysis according to the types of anti-epilepsy medicine. However, the analysis of EEG results by the same disease has significant meaning. Therefore, further studies are needed to statistically analyze more data in the future.