Epileptic Seizure Detection In EEG Signals Using Non-Linear Analysis
نویسندگان
چکیده
منابع مشابه
Epileptic Seizure Detection in EEG signals Using TQWT and SVM-GOA Classifier
Background: Epilepsy is a Brain disorder disease that affects people's quality of life. If it is diagnosed at an early stage, it will not be spread. Electroencephalography (EEG) signals are used to diagnose epileptic seizures. However, this screening system cannot diagnose epileptic seizure states precisely. Nevertheless, with the help of computer-aided diagnosis systems (CADS), neurologists ca...
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Brain disorders include Alzheimer’s disease, learning disability, traumatic brain injury, stroke, emotional disorders, seizures, attention deficit disorder, etc....Seizures occasionally known as a ‘fit’ are most commonly occurring brain disorder among humans. Sometimes, a person may have seizure without aura. It is very tedious and expensive to have a person constantly observe each patient and ...
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An epileptic seizure is a transient event of abnormal excessive neuronal discharge in the brain. This unwanted event can be obstructed by detection of electrical changes in the brain that happen before the seizure takes place. The automatic detection of seizures is necessary since the visual screening of EEG recordings is a time consuming task and requires experts to improve the diagnosis. Much...
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Epileptic seizure detection is commonly implemented by expert clinicians with visual observation of electroencephalography (EEG) signals, which tends to be time consuming and sensitive to bias. The epileptic detection in most previous research suffers from low power and unsuitability for processing large datasets. Therefore, a computerized epileptic seizure detection method is highly required t...
متن کاملEpileptic Seizure Detection by Exploiting Temporal Correlation of EEG Signals
Electroencephalogram (EEG), a record of electrical signal to represent the human brain activity, has great potential for the diagnosis to treatment of mental disorder and brain diseases such as epileptic seizure. Features extraction and classification of EEG signals is the crucial task to detect the stage of ictal (i.e., seizure period) and interictal (i.e., period between seizures) signals for...
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ژورنال
عنوان ژورنال: International Journal of Engineering & Technology
سال: 2018
ISSN: 2227-524X
DOI: 10.14419/ijet.v7i3.12.16497