Detection of Epilepsy Disease From EEG Signals With Artificial Neural Networks

被引：0

作者：

Ozkan, Cansu ^{[1
]}

Dogan, Seda ^{[1
]}

Kantar, Tugce ^{[1
]}

Aksahin, Mehmet Feyzi ^{[1
]}

Erdamar, Aykut ^{[1
]}

机构：

[1] Baskent Univ, Biyomed Muhendisligi Bolumu, Ankara, Turkey

来源：

2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU) | 2016年

关键词：

EEG; epilepsy; ANN; automatic detection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The diagnosis of the epilepsy diseases are made by physicians with analyzing the electroencephalography (EEG) records. The epilepsy diseases can be determined with observing the main properties of before and on-time seizure signals in time and frequency domain. Physicians are evaluating the results after some necessary scoring on EEG records. However, this evaluation is specialistic, time consuming processes and also may subjective results. At this point, to allow detection of epilepsy diseases, a decision support system can give more objective results to the physicians for diagnosing. The subject of the study is automatically diagnosing the epilepsy diseases on EEG signals. In the proposed study, analyses of EEG signals in time and frequency domain were done and features of diseases were obtained. As a result, using artificial neural network (ANN) and obtained features, a decision support system is realized to diagnose the epilepsy. The specificity and the sensitivity of the algorithm are 94% and 66% respectively.

引用

页码：693 / 696

页数：4

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