Epileptic Seizure Detection Using Temporal Based Measures in EEG Signal

被引：0

作者：

Hussain, Shadab ^{[1
]}

Sarfraz, Mohammad ^{[1
]}

Rukhsar, Salim ^{[1
]}

机构：

[1] Aligarh Muslim Univ, Dept Elect Engn, Aligarh, Uttar Pradesh, India

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMMUNICATION AND ELECTRONICS SYSTEMS (ICCES 2018) | 2018年

关键词：

cross validation; statistical measures; and morphological measures; logistic regression; decision tree;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Neuronal activity analysis of the brain for epileptic seizure detection. This neuronal activity is recorded in electroencephalogram (EEG) data. Present work focused on two temporal based features of EEG signal, including statistical and morphological features. The discriminating potential of extracted features is examined by using logistic regression classifier and validated by 10 fold cross validation. The result of the proposed method is found as 99.38, 99.58, and 99.48 percent of sensitivity, specificity, and accuracy respectively by using EEG data of University of Bonn, Germany.

引用

页码：743 / 748

页数：6

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