A novel EEG-complexity-based feature and its application on the epileptic seizure detection
SL Zhang, B Zhang, YL Su, JL Song - International Journal of Machine …, 2019 - Springer
The neurophysiology system is a complex network of nerves and cells, which carries
messages to and from the brain and spinal cord to various parts of the body. Exploring …
messages to and from the brain and spinal cord to various parts of the body. Exploring …
Automated detection of epileptic EEGs using a novel fusion feature and extreme learning machine
Automated seizure detection using EEG has gained increasing attraction in recent years and
appeared more and more helpful in both diagnosis and treatment. How to design an …
appeared more and more helpful in both diagnosis and treatment. How to design an …
Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine
Y Song, J Crowcroft, J Zhang - Journal of neuroscience methods, 2012 - Elsevier
Epilepsy is one of the most common neurological disorders–approximately one in every 100
people worldwide are suffering from it. The electroencephalogram (EEG) is the most …
people worldwide are suffering from it. The electroencephalogram (EEG) is the most …
Automatic seizure detection using a novel EEG feature based on nonlinear complexity
Epileptic seizure detection using EEGs is a heavy workload of traditional visual inspection
for diagnosing epilepsy. Therefore, more and more research on automatic seizure detection …
for diagnosing epilepsy. Therefore, more and more research on automatic seizure detection …
A sequential method using multiplicative extreme learning machine for epileptic seizure detection
D Li, Q Xie, Q Jin, K Hirasawa - Neurocomputing, 2016 - Elsevier
Epilepsy, one of the most common neurological disorders of the human brain, is
unpredictable and irregular. There is much difficulty involved in its detection. Here, a …
unpredictable and irregular. There is much difficulty involved in its detection. Here, a …
Hybrid WCA–PSO Optimized Ensemble Extreme Learning Machine and Wavelet Transform for Detection and Classification of Epileptic Seizure from EEG Signals
S Panda, S Mishra, MN Mohanty - Augmented Human Research, 2023 - Springer
Epilepsy seizures are sudden, chaotic neurological functions. The complexity of the brain is
revealed via electroencephalography (EEG). Visual examination-based EEG signal analysis …
revealed via electroencephalography (EEG). Visual examination-based EEG signal analysis …
[HTML][HTML] A new approach for epileptic seizure detection: sample entropy based feature extraction and extreme learning machine
Y Song, P Liò - Journal of Biomedical Science and Engineering, 2010 - scirp.org
The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy.
Substantial data is generated by the EEG recordings of ambulatory recording systems, and …
Substantial data is generated by the EEG recordings of ambulatory recording systems, and …
[HTML][HTML] Deep extreme learning machine with knowledge augmentation for EEG seizure signal recognition
X Zhang, S Dong, Q Shen, J Zhou… - Frontiers in …, 2023 - frontiersin.org
Introduction Intelligent recognition of electroencephalogram (EEG) signals can remarkably
improve the accuracy of epileptic seizure prediction, which is essential for epileptic …
improve the accuracy of epileptic seizure prediction, which is essential for epileptic …
[HTML][HTML] Epileptic seizure detection based on imbalanced classification and wavelet packet transform
Purpose Automatic seizure detection is significant for the diagnosis of epilepsy and the
reduction of massive workload for reviewing continuous EEG recordings. Methods …
reduction of massive workload for reviewing continuous EEG recordings. Methods …
A framework on wavelet-based nonlinear features and extreme learning machine for epileptic seizure detection
LL Chen, J Zhang, JZ Zou, CJ Zhao… - … Signal Processing and …, 2014 - Elsevier
Background Many investigations based on nonlinear methods have been carried out for the
research of seizure detection. However, some of these nonlinear measures cannot achieve …
research of seizure detection. However, some of these nonlinear measures cannot achieve …
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