Visibility Graph from Adaptive Optimal Kernel Time-Frequency Representation for Classification of Epileptiform EEG

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ID: 269213
2017
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Abstract
Detecting epileptic seizure from EEG signals constitutes a challenging problem of significant importance. Combining adaptive optimal kernel time-frequency representation and visibility graph, we develop a novel method for detecting epileptic seizure from EEG signals. We construct complex networks fr …
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zk2017internationalvisibility Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gao ZK;Cai Q;Yang YX;Dong N;Zhang SS;;
Journal international journal of neural systems
Year 2017
DOI
DOI not found
URL
https://www.ncbi.nlm.nih.gov/pubmed/27832712
Keywords
National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine algorithms computer-assisted* time factors signal processing cluster analysis brain / diagnostic imaging* brain / physiopathology pmid:27832712 doi:10.1142/s0129065717500058 zhong-ke gao qing cai shan-shan zhang datasets as topic electroencephalography / methods* entropy epilepsy / diagnostic imaging* epilepsy / physiopathology neural pathways / diagnostic imaging neural pathways / physiopathology seizures / diagnostic imaging seizures / physiopathology

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