Generalisability of epileptiform patterns across time and patients

H Karimi-Rouzbahani, A McGonigal - Scientific Reports, 2024 - nature.com
The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection
failures in achieving seizure freedom. The distinct patterns of epileptiform activity during …

Epileptic seizure classification based on random neural networks using discrete wavelet transform for electroencephalogram signal decomposition

SY Shah, H Larijani, RM Gibson, D Liarokapis - Applied Sciences, 2024 - mdpi.com
An epileptic seizure is a brief episode of symptoms and signs caused by excessive electrical
activity in the brain. One of the major chronic neurological diseases, epilepsy, affects …

Automatic focal EEG identification based on deep reinforcement learning

X Liu, X Ding, J Liu, W Nie, Q Yuan - Biomedical Signal Processing and …, 2023 - Elsevier
Electroencephalogram (EEG) signals convey information about the electrical activity of
neurons and are commonly used in clinical practice to evaluate the epileptic activity of …

[PDF][PDF] Multi-Classification of Electroencephalogram Epileptic Seizures Based on Robust Hybrid Feature Extraction Technique and Optimized Support Vector Machine …

S Saminu, G Xu, S Zhang, IA El Kader, HA Aliyu… - Electrica, 2023 - electricajournal.org
Epilepsy is a disease with various forms. However, limited dataset has confined
classification studies of epilepsy into binary classes only. This study sort to achieve …

Special Issue on Deep Learning for Electroencephalography (EEG) Data Analysis

R Prevete, F Isgrò, F Donnarumma - Applied Sciences, 2023 - mdpi.com
Brain–computer interfaces (BCI) have emerged as a groundbreaking and transformative
technology enabling communication between humans and computers through neural …

Epilepsy Diagnosis Using Directed Acyclic Graph SVM Technique in EEG Signals.

S Babu, AK Wadhwani - Traitement du Signal, 2024 - search.ebscohost.com
Epilepsy is a complicated neurological disorder that causes rapid and frequent seizures in
both adults and children. EEG signals are emerging as non-invasive methods for analyzing …

[PDF][PDF] The Deep Learning Based Epileptic Seizure Detection Using 2-layer Convolutional Network with Long Short-Term Memory.

SD Vaithilingam, P Regulagedda - International Journal of Intelligent …, 2024 - inass.org
Epilepsy is a pervasive chronic neurological disorder characterized through irregular
electrical discharges in the brain which causes seizures. Epilepsy seizure is a disorder that …

[PDF][PDF] An Integrated Remote Health Monitoring System for AI-based detection of Falls and Epileptic Seizures: Design and Evaluation

SY Shah - 2024 - researchonline.gcu.ac.uk
The advancement in technologies such as Artificial Intelligence (AI) and the Internet of
Things (IoT) has enabled the development of a variety of healthcare applications and …

Automated Classification of Focal and Non-focal Epileptic iEEG Signals using 1D-Convolutional Neural Network

AS Jangde, DS Sisodia - 2023 2nd International Conference …, 2023 - ieeexplore.ieee.org
Epilepsy affects 1% of the population across all age groups, making it the fourth most
dangerous brain disorder diagnosed worldwide. The seizures, limited to a specific area of …

Investigation of Optimal Components and Parameters of the Incremental PCA-based LSTM Network for Detection of EEG Epileptic Seizure Events

S Saminu, AH Jabire, HA Aliyu… - BIMA JOURNAL …, 2023 - journals.gjbeacademia.com
Prediction of Epileptic seizures is highly imperative to improve the epileptic patient's life.
Epileptic seizures occur due to brain cells excessive abnormal activity that leads to …