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 …
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 deep learning based ensemble learning method for epileptic seizure prediction
In epilepsy, patients suffer from seizures which cannot be controlled with medicines or
surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is …
surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is …
Spatio-temporal MLP network for seizure prediction using EEG signals
In this paper, we propose an end-to-end epilepsy seizure prediction method based on multi-
layer perceptrons (MLPs). The proposed method mainly contains two functional blocks: the …
layer perceptrons (MLPs). The proposed method mainly contains two functional blocks: the …
[HTML][HTML] Deep-EEG: an optimized and robust framework and method for EEG-based diagnosis of epileptic seizure
Detecting brain disorders using deep learning methods has received much hype during the
last few years. Increased depth leads to more computational efficiency, accuracy, and …
last few years. Increased depth leads to more computational efficiency, accuracy, and …
EEG-based seizure prediction via hybrid vision transformer and data uncertainty learning
Feature embeddings derived from continuous mapping using the deep neural network are
critical for accurate classification in seizure prediction tasks. However, the embeddings of …
critical for accurate classification in seizure prediction tasks. However, the embeddings of …
[HTML][HTML] Multi-channel vision transformer for epileptic seizure prediction
Epilepsy is a neurological disorder that causes recurrent seizures and sometimes loss of
awareness. Around 30% of epileptic patients continue to have seizures despite taking anti …
awareness. Around 30% of epileptic patients continue to have seizures despite taking anti …
An overview of EEG-based machine learning methods in seizure prediction and opportunities for neurologists in this field
B Maimaiti, H Meng, Y Lv, J Qiu, Z Zhu, Y Xie, Y Li… - Neuroscience, 2022 - Elsevier
The unpredictability of epileptic seizures is one of the most problematic aspects of the field of
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …
Seizure detection and prediction by parallel memristive convolutional neural networks
During the past two decades, epileptic seizure detection and prediction algorithms have
evolved rapidly. However, despite significant performance improvements, their hardware …
evolved rapidly. However, despite significant performance improvements, their hardware …
[HTML][HTML] Epilepsy seizures prediction based on nonlinear features of EEG signal and gradient boosting decision tree
X Xu, M Lin, T Xu - International Journal of Environmental Research and …, 2022 - mdpi.com
Epilepsy is a common neurological disorder with sudden and recurrent seizures. Early
prediction of seizures and effective intervention can significantly reduce the harm suffered by …
prediction of seizures and effective intervention can significantly reduce the harm suffered by …