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 …

[HTML][HTML] Seizure detection using integrated metaheuristic algorithm based ensemble extreme learning machine

S Panda, S Mishra, MN Mohanty, S Satapathy - Measurement: Sensors, 2023 - Elsevier
In biomedical research, the brain signal analysis occupies an important space in recent
days. Mostly Epileptic seizure detection is a challenging task for all brain signal researcher …

Epileptic seizure classification using adaptive sine cosine algorithm-whale optimization algorithm optimized learning machine model

S Panda, S Mishra, MN Mohanty… - … in Advances in Power …, 2023 - ieeexplore.ieee.org
Epileptic seizure leads to the unconsciousness of the brain due to the lack of sleep, toxic
consumption mainly. Now a days the death rate becomes high due to the negligence of the …

A DM-ELM based classifier for EEG brain signal classification for epileptic seizure detection

S Mishra, S Kumar Satapathy, SN Mohanty… - … & Integrative Biology, 2023 - Taylor & Francis
Epilepsy is one of the dreaded conditions that had taken billions of people under its cloud
worldwide. Detecting the seizure at the correct time in an individual is something that …

EEG classification approach based on the extreme learning machine and wavelet transform

Q Yuan, W Zhou, J Zhang, S Li… - Clinical EEG and …, 2012 - journals.sagepub.com
Automatic detection and classification of electroencephalogram (EEG) epileptic activity aid
diagnosis and relieve the heavy workload of doctors. This article presents a new EEG …

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 …

[PDF][PDF] An optimized extreme learning machine for epileptic seizure detection

ASM Murugavel, S Ramakrishnan - Int. J. Comput. Sci, 2014 - cs.uoregon.edu
Single hidden Layer Feed forward Neural network (SLFN) called Optimized Extreme
Learning Machine (OELM) is proposed for the classification of EEG signals with the …

[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 …

Automated detection of epileptic EEGs using a novel fusion feature and extreme learning machine

JL Song, W Hu, R Zhang - Neurocomputing, 2016 - Elsevier
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 …

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 …