Classification of Epileptic and Healthy Individual EEG Signals Using Neural Networks

被引：0
|
作者：
Aykat, Sukru [1 ]
Senan, Sibel [2 ]
Ensari, Tolga [2 ]
机构：
[1] Mardin Artuklu Univ, Midyat Meslek Yuksekokulu, Bilgisayar Programciligi, Mardin, Turkey
[2] Istanbul Univ Cerrahpasa, Muhendislik Fak, Bilgisayar Muhendisligi, Istanbul, Turkey
来源：
2020 5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2020年
关键词：
EEG Signal; Artificial Neural Networks; Wavelet Transform; WAVELET; SEIZURE;
D O I：
10.1109/ubmk50275.2020.9219474
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Electroencephalogram (EEG) are signals used for the analysis of the electrical and functional activity of the brain. These signals are commonly used to detect epileptic seizures. The aim of this study is to classify healthy and epileptic individual EEG signals using artificial neural networks (ANN). For this purpose, the open data source of the University of Bonn was used. The success rates of the classification results obtained with the designed ANN model show the effectiveness of this ANN structure in the application under consideration.
引用
收藏
页码：47 / 51
页数：5
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