Generalisability of epileptiform patterns across time and patients
The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection
failures in achieving seizure freedom. The distinct patterns of epileptiform activity during …
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
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 …
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 …
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 …
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 …
classification studies of epilepsy into binary classes only. This study sort to achieve …
Special Issue on Deep Learning for Electroencephalography (EEG) Data Analysis
Brain–computer interfaces (BCI) have emerged as a groundbreaking and transformative
technology enabling communication between humans and computers through neural …
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 …
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 …
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 …
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
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 …
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
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 …
Epileptic seizures occur due to brain cells excessive abnormal activity that leads to …