Epileptic Seizure Detection Using Discrete Wavelet Transform Based Support Vector Machine

被引：0

作者：

Deshmukh, Prashant ^{[1
]}

Ingle, Rahul ^{[1
]}

Kehri, Vikram

Awale, R. N. ^{[2
]}

机构：

[1] VJTI, Bombay 400019, Maharashtra, India

[2] VJTI, Elect Engn Dept, Bombay 400019, Maharashtra, India

来源：

2017 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP) | 2017年

关键词：

(EEG) Electroencephalogram; Support vector machine (SVM); (DWT) discrete wavelet transform; Epileptic Seizure; SPIKE 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：

In this work, an effective method for the presence of epileptic seizures from continuous EEG signals is carried out using machine learning algorithm. The work for detection of epileptic Seizure from EEG signals is carried out in three stages. In first stage, DWT is used for EEG signal decomposition into its corresponding sub bands. In second stage, extraction of the statistical features from each subband and finally classification of the EEG signals into epileptic seizure and normal has been done using SVM. The result from experimental analysis shows that, the proposed method is better for detection of the epileptic seizure from EEG Signals.

引用

页码：1933 / 1937

页数：5

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