[HTML][HTML] An overview of machine learning methods in enabling IoMT-based epileptic seizure detection

ALN Al-Hajjar, AKM Al-Qurabat - The Journal of Supercomputing, 2023 - Springer
The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …

Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals

I Tasci, B Tasci, PD Barua, S Dogan, T Tuncer… - Information …, 2023 - Elsevier
Background Epilepsy is one of the most commonly seen neurologic disorders worldwide
and has generally caused seizures. Electroencephalography (EEG) is widely used in …

An intelligent optimized deep learning model to achieve early prediction of epileptic seizures

A Pandey, SK Singh, SS Udmale, KK Shukla - … Signal Processing and …, 2023 - Elsevier
Seizure prediction from electroencephalogram (EEG) time series data and a sequential
deep learning (DL) predictor substantially boosts epileptic patients' quality of life. However, a …

Brain Epileptic Seizure Detection using Joint CNN and Exhaustive Feature Selection with RNN-BLSTM Classifier

CSL Prasanna, MZU Rahman, MD Bayleyegan - IEEE Access, 2023 - ieeexplore.ieee.org
Brain Epilepsy seizure is a critical disorder, which is an uncontrolled burst of electrical
activity of brain. The early detection of brain seizure can save the life of humans. The …

An epilepsy detection method based on multi-dimensional feature extraction and dual-branch hypergraph convolutional network

J Liu, Y Yang, F Li, J Luo - Frontiers in Physiology, 2024 - frontiersin.org
Epilepsy is a disease caused by abnormal neural discharge, which severely harms the
health of patients. Its pathogenesis is complex and variable with various forms of seizures …

One‐dimensional atrous conv‐net based architecture for automatic diagnosis of epilepsy using electroencephalography signals and its brain–computer interface …

P Handa, M Gupta, E Gupta, N Goel - Expert Systems, 2024 - Wiley Online Library
Precise monitoring and diagnosis of epilepsy by manual analysis of EEG signals are
challenging due to the low doctor‐to‐patient ratio, and shortage of medical resources. To …

[HTML][HTML] Identification of TLE Focus from EEG Signals by Using Deep Learning Approach

C Ficici, Z Telatar, O Kocak, O Erogul - Diagnostics, 2023 - mdpi.com
Temporal lobe epilepsy, a neurological disease that causes seizures as a result of
excessive neural activities in the brain, is the most common type of focal seizure, accounting …

Automatic detection of epileptic seizure using machine learning-based IANFIS-LightGBM system

D Saranya, A Bharathi - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
A sudden increase in electrical activity in the brain is a defining feature of one of the severe
neurological diseases known as epilepsy. This abnormality appears as a seizure, and …

Advancing Epilepsy Disease Classification through Machine Learning and Deep Learning Models Utilizing EEG Data.

A Saleem, MA Khan, HM Yousaf - 2023 17th International …, 2023 - ieeexplore.ieee.org
Epilepsy disease is a neurological condition marked by recurring seizures that has a big
effect on people's life. Effective management and therapy depend on a prompt and correct …

Epileptic seizure detection using improved empirical mode decomposition and improved weight updated KNN

NV Saichand, SG Naik - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
Epilepsy is considered a most general neurological disorder related to brain activity
disruption. In epileptic seizures detection and classification, EEG (Electroencephalogram) …