Developing multi-component dictionary-based sparse representation for automatic detection of epileptic EEG spikes-Reference-Cited by-同舟云学术

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Developing multi-component dictionary-based sparse representation for automatic detection of epileptic EEG spikes

Published:2020-07 Issue: Volume:60 Page:101966
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Jiang Yun,Chen Wanzhong,Zhang Tao^ORCID,Li Mingyang,You Yang,Zheng Xiao

Funder

Department of Science and Technology of Jilin Province

Domain Foundation of Equipment Advance Research of 13th Five-year Plan

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference34 articles.

1. Effects of dexamethasone on the Li-pilocarpine model of epilepsy: protection against hippocampal inflammation and astrogliosis;Vizuete;J. Neuroinflammation,2018

2. EMD-based temporal and spectral features for the classification of EEG signals using supervised learning;Riaz;IEEE Trans. Neural Syst. Rehabil. Eng.,2016

3. Epileptic EEG classification using nonlinear parameters on different frequency bands;Martis;J. Mech. Med. Biol.,2015

4. Epileptic seizure classification of EEG time-series using rational discrete short-time fourier transform;Samiee;IEEE Trans. Biomed. Eng.,2015

5. Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy;Ocak;Expert Syst. Appl.,2009

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