An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
A Shoeibi, P Moridian, M Khodatars… - Computers in biology …, 2022 - Elsevier
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets
Epilepsy is a common non‐communicable, group of neurological disorders affecting more
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
EEG-rhythm specific Taylor–Fourier filter bank implemented with O-splines for the detection of epilepsy using EEG signals
JA de la O Serna, MRA Paternina… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
The neurological disorder which is associated with the abnormal electrical activity generated
from the brain causing seizures is typically termed as epilepsy. The automated detection and …
from the brain causing seizures is typically termed as epilepsy. The automated detection and …
A progressive deep wavelet cascade classification model for epilepsy detection
H He, X Liu, Y Hao - Artificial Intelligence in Medicine, 2021 - Elsevier
Automatic epileptic seizure detection according to EEG recordings is helpful for neurologists
to identify an epilepsy occurrence in the initial anti-epileptic treatment. To quickly and …
to identify an epilepsy occurrence in the initial anti-epileptic treatment. To quickly and …
Epileptic seizure detection using brain-rhythmic recurrence biomarkers and onasnet-based transfer learning
Objective: The electroencephalogram (EEG) tool has great potential for real-time monitoring
of abnormal brain activities, such as preictal and ictal seizures. Developing an EEG-based …
of abnormal brain activities, such as preictal and ictal seizures. Developing an EEG-based …
A deep learning scheme for automatic seizure detection from long-term scalp EEG
Epilepsy is a chronic brain disorder that is expressed by seizures. Monitoring brain activity
via electroencephalogram (EEG) is an established method for epilepsy diagnosis and for …
via electroencephalogram (EEG) is an established method for epilepsy diagnosis and for …
Cross-correlation aided ensemble of classifiers for BCI oriented EEG study
Recently, Brain-computer interface (BCI) oriented electroencephalographic (EEG) studies
have received due attention for decoding human brain signals corresponding to a specific …
have received due attention for decoding human brain signals corresponding to a specific …
[PDF][PDF] Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning—clinical application perspectives
M Janmohamed, D Nhu, L Kuhlmann… - Brain …, 2022 - academic.oup.com
The application of deep learning approaches for the detection of interictal epileptiform
discharges is a nascent field, with most studies published in the past 5 years. Although many …
discharges is a nascent field, with most studies published in the past 5 years. Although many …
EEG asymmetry detection in patients with severe acquired brain injuries via machine learning methods
L Corsi, P Liuzzi, S Ballanti, M Scarpino… - … Signal Processing and …, 2023 - Elsevier
Lateral brain symmetry indexes, detected by electroencephalography (EEG), are markers of
rehabilitative recovery widely used in patients with severe acquired brain injury (sABI). In …
rehabilitative recovery widely used in patients with severe acquired brain injury (sABI). In …
Nonlinear vector decomposed neural network based EEG signal feature extraction and detection of seizure
R Mouleeshuwarapprabu, N Kasthuri - Microprocessors and Microsystems, 2020 - Elsevier
Electroencephalography is one of the important medical methods to evaluate and treat
neurophysiology to combat disease related to seizure. The automatic seizure detection …
neurophysiology to combat disease related to seizure. The automatic seizure detection …