Random neural network based epileptic seizure episode detection exploiting electroencephalogram signals

SY Shah, H Larijani, RM Gibson, D Liarokapis - Sensors, 2022 - mdpi.com
Epileptic seizures are caused by abnormal electrical activity in the brain that manifests itself
in a variety of ways, including confusion and loss of awareness. Correct identification of …

Neural network based seizure detection system using statistical package analysis

P Rajendran, K Ganapathy - Bulletin of Electrical Engineering and …, 2022 - beei.org
Due to the unpredictable interruptions within the functions of the human brain, disturbance
occurs and it affects the behavior of the human and is equally laid low with the frequent …

Early seizure detection algorithm based on intracranial EEG and random forest classification

C Donos, M Dümpelmann… - International journal of …, 2015 - World Scientific
The goal of this study is to provide a seizure detection algorithm that is relatively simple to
implement on a microcontroller, so it can be used for an implantable closed loop stimulation …

A Hybrid LSTM-DBN Approach for Automatic Epileptic Seizure Detection compared with Normal Human Activity using EEG Signals

S Cherukuvada, R Kayalvizhi - 2023 5th International …, 2023 - ieeexplore.ieee.org
More than 2% of people throughout the globe suffer from the neurodegenerative condition
known as epilepsy. A sudden onset of convulsive seizures characterizes epilepsy, a …

Development of an intelligent seizure prediction system

AL Rusnac, O Grigore - 2019 11th International Symposium on …, 2019 - ieeexplore.ieee.org
Epilepsy is a neurological disorder characterized by the occurrence of unexpected epileptic
seizures. This unpredictable character of epilepsy tends to hinder the daily activity of the …

[HTML][HTML] Electroencephalogram signal classification for automated epileptic seizure detection using genetic algorithm

BS Nanthini, B Santhi - Journal of natural science, biology, and …, 2017 - ncbi.nlm.nih.gov
Background: Epilepsy causes when the repeated seizure occurs in the brain.
Electroencephalogram (EEG) test provides valuable information about the brain functions …

[HTML][HTML] A MACHINE LEARNING-BASED APPROACH TO EPILEPTIC SEIZURE PREDICTION USING ELECTRO-ENCEPHALOGRAPHIC SIGNALS

BC Rebello, ARG Ramirez… - Journal of …, 2022 - ncbi.nlm.nih.gov
The brain is made up of billions of neurons, which control all actions performed by us. In
epilepsy, the pattern order of brain signals is altered, causing epileptiform discharges in an …

Epileptic seizure detection in EEG signal using machine learning techniques

AK Jaiswal, H Banka - Australasian physical & engineering sciences in …, 2018 - Springer
Epilepsy is a well-known nervous system disorder characterized by seizures.
Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy …

Comparing the effect of under-sampling and over-sampling on traditional machine learning algorithms for epileptic seizure detection

K Akyol, Ü Atila - Academic Platform-Journal of Engineering and …, 2020 - dergipark.org.tr
Epilepsy disease, a neurological disorder that causes recurrent and sudden crises, occurs at
unforeseen times. This study presents the classification of electroencephalogram signals for …

An improved cognitive approach for automated epileptic seizure detection from multichannel eeg

S Parui, D Basu - … Women in Engineering (WIE) Conference on …, 2021 - ieeexplore.ieee.org
While electroencephalography (EEG) is useful in monitoring and diagnosing epileptic
patients' brain activity, all EEG recordings must be analyzed by an expert to detect epileptic …