A new approach for diagnosing epilepsy by using wavelet transform and neural networks

被引：9

作者：

Akin, M ^{[1
]}

Arserim, MA ^{[1
]}

Kiymik, MK ^{[1
]}

Turkoglu, I ^{[1
]}

机构：

[1] Dicle Univ, Dept Elect & Elect Engn, Diyarbakir, Turkey

来源：

PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE | 2001年 / 23卷

关键词：

wavelet; neural network; epilepsy; EEG;

D O I：

10.1109/IEMBS.2001.1020517

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Today, epilepsy keeps its importance as a major brain disorder. However, although some devices such as magnetic resonance (MR), brain tomography (BT) are used to diagnose the structural disorders of brain, for observing some special illnesses especially such as epilepsy, EEG is routinely used for observing the epileptic seizures, in neurology clinics. In our study, we aimed to classify the EEG signals and diagnose the epileptic seizures directly by using wavelet transform and an artificial neural network model. EEG signals are separated into delta, theta, alpha, and beta spectral components by using wavelet transform. These spectral components are applied to the inputs of the neural network. Then, neural network is trained to give three outputs to signify the health situation of the patients Keywords: wavelet, neural network, epilepsy, EEG.

引用

页码：1596 / 1599

页数：4

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