EEG signal classification for Epilepsy Seizure Detection using Improved Approximate Entropy
نویسندگان
چکیده
منابع مشابه
A novel automatic stepwise signal processing based computer aided diagnosis system for epilepsy-seizure detection and classification for EEG
Epilepsy is one of the brain based disease affects human due to over electricity power passed in the brain. It is also a neurological disorder problem comes after stroke or brain fever, brain attack or while less blood flow in the brain. Recurrent attack creates epilepsy mainly. Number of death increased nowadays due to epilepsy seizures. In order to control this it is essential to identify and...
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D ysfunction in the central nervous system of the neonate is often rst identi ed through seizures. The di culty in detecting clinical seizures, which involves the observation of physical manifestations characteristic to newborn seizure, has placed greater emphasis on the detection of newborn electroencephalographic (EEG) seizure. The high incidence of newborn seizure has resulted in considerabl...
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Epilepsy is the most common brain diseases that cause many problems in the daily life of the patient. In most attempts to automatic detection, the attack used an EEG. In this paper, The complete data set consists of five sets recorded from normal and epileptic patients. Each set containing 100 single-channel EEG segments. Here we used first and last sets (A and E). Set A consisted of segments r...
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The electroencephalogram (EEG) signal plays an important role in the detection of epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data and the detection of the epileptic activity requires a timeconsuming analysis of the entire length of the EEG data by an expert. The aim of this work is to develop a new method for automatic detection of EEG patterns using ...
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ژورنال
عنوان ژورنال: International Journal of Public Health Science (IJPHS)
سال: 2013
ISSN: 2252-8806
DOI: 10.11591/ijphs.v2i1.1836