Electroencephalography-based feature extraction using complex network for automated epileptic seizure detection

Author:

Artameeyanant Patcharin1,Sultornsanee Sivarit2,Chamnongthai Kosin1

Affiliation:

1. Department of Electronic and Telecommunication Engineering, Faculty of Engineering; King Mongkut's University of Technology Thonburi; Bangkok 10140 Thailand

2. School of Business; University of the Thai Chamber of Commerce; Bangkok 10400 Thailand

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Reference50 articles.

1. Automated diagnosis of epileptic EEG using entropies;Acharya;Biomedical Signal Processing and Control,2012

2. Detection of seizure and epilepsy using higher order statistics in the EMD domain;Alam;IEEE Journal of Biomedical and Health Informatics,2013

3. The epileptic process as nonlinear deterministic dynamics in a stochastic environment: An evaluation on mesial temporal lobe epilepsy;Andrsejak;Epilepsy Research,2001

4. Artameyanant , P. Chiracharit , W Chamnongthai , K. 2012 Spike and epileptic seizure detection using wavelet packet transform based on approximate entropy and energy with artificial neural network Biomedical Engineering International Conference (BMEiCON 2012)

5. Artameyanant , P. Chamnongthai , K. 2013 Wavelet packet decomposition based spike and epileptic seizure classification using multiclass support vector machine the 2013 International Electrical Engineering Congress (iEECON 2013)

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