Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features

Author:

Lu Yanan1,Ma Yu12,Chen Chen3,Wang Yuanyuan12

Affiliation:

1. Department of Electronic Engineering, Fudan University, Shanghai, China

2. Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China

3. Center for Intelligent Medical Electronics, Fudan University, Shanghai, China

Publisher

IOS Press

Subject

Health Informatics,Biomedical Engineering,Information Systems,Biomaterials,Bioengineering,Biophysics

Reference16 articles.

1. Epilepsy: New advances;Moshé;The Lancet,2015

2. Berry RB. Fundamentals of Sleep Medicine E-Book. Elsevier Health Sciences 2011.

3. Real-time epileptic seizure detection using EEG;Vidyaratne;IEEE Transactions on Neural Systems and Rehabilitation Engineering,2017

4. A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension;Sharma;Pattern Recognition Letters,2017

5. Epileptic seizure detection in long-term EEG records using sparse rational decomposition and local Gabor binary patterns feature extraction;Samiee;Knowledge-Based Systems,2017

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