EEG seizure detection: concepts, techniques, challenges, and future trends
AA Ein Shoka, MM Dessouky, A El-Sayed… - Multimedia Tools and …, 2023 - Springer
A central nervous system disorder is usually referred to as epilepsy. In epilepsy brain activity
becomes abnormal, leading to times of abnormal behavior or seizures, and at times loss of …
becomes abnormal, leading to times of abnormal behavior or seizures, and at times loss of …
Theoretical and methodological analysis of EEG based seizure detection and prediction: An exhaustive review
Epilepsy is a chronic neurological disorder with a comparatively high prevalence rate. It is a
condition characterized by repeated and unprovoked seizures. Seizures are managed with …
condition characterized by repeated and unprovoked seizures. Seizures are managed with …
Deep learning for patient-independent epileptic seizure prediction using scalp EEG signals
Epilepsy is one of the most prevalent neurological diseases among humans and can lead to
severe brain injuries, strokes, and brain tumors. Early detection of seizures can help to …
severe brain injuries, strokes, and brain tumors. Early detection of seizures can help to …
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 …
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …
Geometric deep learning for subject independent epileptic seizure prediction using scalp EEG signals
Recently, researchers in the biomedical community have introduced deep learning-based
epileptic seizure prediction models using electroencephalograms (EEGs) that can anticipate …
epileptic seizure prediction models using electroencephalograms (EEGs) that can anticipate …
Patient-independent seizure detection based on channel-perturbation convolutional neural network and bidirectional long short-term memory
G Liu, L Tian, W Zhou - International journal of neural systems, 2022 - World Scientific
Automatic seizure detection is of great significance for epilepsy diagnosis and alleviating the
massive burden caused by manual inspection of long-term EEG. At present, most seizure …
massive burden caused by manual inspection of long-term EEG. At present, most seizure …
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 …
XAI4EEG: spectral and spatio-temporal explanation of deep learning-based seizure detection in EEG time series
In clinical practice, algorithmic predictions may seriously jeopardise patients' health and thus
are required to be validated by medical experts before a final clinical decision is met …
are required to be validated by medical experts before a final clinical decision is met …
A convolutional long short-term memory-based neural network for epilepsy detection from EEG
Epilepsy (EP) is a severe neurological disorder characterized by recurrent seizures, which
increases the risk of death three times more than normal. Currently, electroencephalography …
increases the risk of death three times more than normal. Currently, electroencephalography …
Epileptic seizure classification using level-crossing EEG sampling and ensemble of sub-problems classifier
SF Hussain, SM Qaisar - Expert Systems with Applications, 2022 - Elsevier
Epilepsy is a disorder of the brain characterized by seizures and requires constant
monitoring particularly in serious patients. Electroencephalogram (EEG) signals are …
monitoring particularly in serious patients. Electroencephalogram (EEG) signals are …