Early Seizure Detection by Applying Frequency-Based Algorithm Derived from the Principal Component Analysis-Reference-Cited by-同舟云学术

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Early Seizure Detection by Applying Frequency-Based Algorithm Derived from the Principal Component Analysis

Published:2017-08-17 Issue: Volume:11 Page:
ISSN:1662-5196
Container-title:Frontiers in Neuroinformatics
language:
Short-container-title:Front. Neuroinform.

Author:

Lee Jiseon,Park Junhee,Yang Sejung,Kim Hani,Choi Yun Seo,Kim Hyeon Jin,Lee Hyang Woon,Lee Byung-Uk

Funder

Korea Health Industry Development Institute

National Research Foundation of Korea

Publisher

Frontiers Media SA

Subject

Computer Science Applications,Biomedical Engineering,Neuroscience (miscellaneous)

Reference41 articles.

1. Mapping preictal and ictal haemodynamic networks using video-electroencephalography and functional imaging;Chaudhary;Brain,2012

2. The pilocarpine model of temporal lobe epilepsy;Curia;J. Neurosci. Methods,2008

3. EEG signals classification of epileptic patients via feature selection and voting criteria in intelligent method;Ghaffari;J. Med. Eng. Technol.,2014

4. Principal component analysis-enhanced cosine radial basis function neural network for robust epilepsy and seizure detection;Ghosh-Dastidar;IEEE Trans. Biomed. Eng.,2008

5. Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks;Guo;J. Neurosci. Methods,2010

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