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 …
An overview of machine learning methods in enabling IoMT-based epileptic seizure detection
ALN Al-Hajjar, AKM Al-Qurabat - The Journal of Supercomputing, 2023 - Springer
The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
Epileptic seizure detection based on bidirectional gated recurrent unit network
Y Zhang, S Yao, R Yang, X Liu, W Qiu… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Visual inspection of long-term electroencephalography (EEG) is a tedious task for
physicians in neurology. Based on bidirectional gated recurrent unit (Bi-GRU) neural …
physicians in neurology. Based on bidirectional gated recurrent unit (Bi-GRU) neural …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …
Epileptic seizure detection using a hybrid 1D CNN‐machine learning approach from EEG data
F Hassan, SF Hussain… - Journal of Healthcare …, 2022 - Wiley Online Library
Electroencephalography (EEG) is a widely used technique for the detection of epileptic
seizures. It can be recorded in a noninvasive manner to present the electrical activity of the …
seizures. It can be recorded in a noninvasive manner to present the electrical activity of the …
Hierarchical Harris hawks optimization for epileptic seizure classification
The intelligent recognition of electroencephalogram (EEG) signals is a valuable tool for
epileptic seizure classification. Given that visual inspection of EEG signals is time …
epileptic seizure classification. Given that visual inspection of EEG signals is time …
Automatic epileptic seizure detection in EEG signals using sparse common spatial pattern and adaptive short-time Fourier transform-based synchrosqueezing …
Epilepsy can now be diagnosed more accurately and quickly due to computer-aided seizure
detection utilizing Electroencephalography (EEG) recordings. In this work, a novel method …
detection utilizing Electroencephalography (EEG) recordings. In this work, a novel method …
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 …
Attention measurement of an autism spectrum disorder user using EEG signals: A case study
JJ Esqueda-Elizondo, R Juárez-Ramírez… - Mathematical and …, 2022 - mdpi.com
Autism Spectrum Disorder (ASD) is a neurodevelopmental life condition characterized by
problems with social interaction, low verbal and non-verbal communication skills, and …
problems with social interaction, low verbal and non-verbal communication skills, and …