An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …

A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform

A Bhattacharyya, RB Pachori - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …

Automated detection of epileptic seizures using successive decomposition index and support vector machine classifier in long-term EEG

S Raghu, N Sriraam, S Vasudeva Rao… - Neural Computing and …, 2020 - Springer
Epilepsy is a commonly observed long-term neurological disorder that impairs nerve cell
activity in the brain and has a severe impact on people's daily lives. Accurate seizure …

EEG signal processing for epilepsy seizure detection using 5-level Db4 discrete wavelet transform, GA-based feature selection and ANN/SVM classifiers

M Omidvar, A Zahedi, H Bakhshi - Journal of ambient intelligence and …, 2021 - Springer
Epilepsy is a neurobiological disease caused by abnormal electrical activity of the human
brain. It is important to detect the epileptic seizures to help the epileptic patients. Using brain …

Enhanced detection of epileptic seizure using EEG signals in combination with machine learning classifiers

W Mardini, MMB Yassein, R Al-Rawashdeh… - IEEE …, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …

Detection of epileptic seizure event and onset using EEG

N Ahammad, T Fathima… - BioMed research …, 2014 - Wiley Online Library
This study proposes a method of automatic detection of epileptic seizure event and onset
using wavelet based features and certain statistical features without wavelet decomposition …

Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2023 - Elsevier
Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons,
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …

[HTML][HTML] EEG epileptic seizure detection and classification based on dual-tree complex wavelet transform and machine learning algorithms

IB Slimen, L Boubchir, Z Mbarki… - Journal of biomedical …, 2020 - ncbi.nlm.nih.gov
The visual analysis of common neurological disorders such as epileptic seizures in
electroencephalography (EEG) is an oversensitive operation and prone to errors, which has …

[HTML][HTML] Application of machine learning in epileptic seizure detection

LV Tran, HM Tran, TM Le, TTM Huynh, HT Tran… - Diagnostics, 2022 - mdpi.com
Epileptic seizure is a neurological condition caused by short and unexpectedly occurring
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …

Multi-channel EEG based automatic epileptic seizure detection using iterative filtering decomposition and Hidden Markov Model

DP Dash, MH Kolekar, K Jha - Computers in biology and medicine, 2020 - Elsevier
Electroencephalography (EEG) is a non-invasive method for the analysis of neurological
disorders. Epilepsy is one of the most widespread neurological disorders and often …