SeizureNet: a model for robust detection of epileptic seizures based on convolutional neural network

SeizureNet: a model for robust detection of epileptic seizures based on convolutional neural network

Epilepsy is a neurological disorder and generally detected by electroencephalogram (EEG) signals. The manual inspection of epileptic seizures is a time-consuming and laborious process. Extensive automatic detection algorithms were proposed by using traditional approaches, which show good accuracy fo...

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Bibliographic Details
Main Authors: Wei Zhao, Wenfeng Wang
Format: Article
Language:English
Published: Wiley 2020-06-01
Series:Cognitive Computation and Systems
Subjects:
neurophysiology
medical signal processing
signal classification
electroencephalography
medical signal detection
convolutional neural nets
medical disorders
feature extraction
robust detection
epileptic seizures
convolutional neural network
neurological disorder
electroencephalogram signals
extensive automatic detection algorithms
eeg classification problems
time-invariant feature extraction
single-channel eeg signals
high-level features
nonseizure classification
seizurenet
softmax layer
benchmark database
ten-fold cross-validation approach
Online Access:https://digital-library.theiet.org/content/journals/10.1049/ccs.2020.0011

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https://digital-library.theiet.org/content/journals/10.1049/ccs.2020.0011

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