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 …
Automatic seizure detection using fully convolutional nested LSTM
The automatic seizure detection system can effectively help doctors to monitor and diagnose
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
A convolutional neural network for seizure detection
O Kaziha, T Bonny - 2020 Advances in Science and …, 2020 - ieeexplore.ieee.org
In this paper, a software-based neural network is developed for the purpose of detecting
seizures from raw EEG signals. Detecting epileptic seizures manually is a long tedious …
seizures from raw EEG signals. Detecting epileptic seizures manually is a long tedious …
CNN based framework for detection of epileptic seizures
Epilepsy is a common neurological disease that uses electroencephalogram (EEG) data for
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
Convolutional neural network for detection and classification of seizures in clinical data
T Iešmantas, R Alzbutas - Medical & Biological Engineering & Computing, 2020 - Springer
Epileptic seizure detection and classification in clinical electroencephalogram data still is a
challenge, and only low sensitivity with a high rate of false positives has been achieved with …
challenge, and only low sensitivity with a high rate of false positives has been achieved with …
A CNN-LSTM hybrid network for automatic seizure detection in EEG signals
S Shanmugam, S Dharmar - Neural Computing and Applications, 2023 - Springer
Epilepsy is a chronic neurological disorder. Epileptics are prone to sudden seizures that
cause disruptions in their daily lives. The separation of epileptic and non-epileptic activity on …
cause disruptions in their daily lives. The separation of epileptic and non-epileptic activity on …
Deep learning based epileptic seizure detection with EEG data
S Poorani, P Balasubramanie - International Journal of System Assurance …, 2023 - Springer
Epilepsy is one kind of life frightening and exigent intellect mayhem in which affected
patients endure recurrent seizures. Large numbers of people are affected by this chaos …
patients endure recurrent seizures. Large numbers of people are affected by this chaos …
Scalp EEG classification using deep Bi-LSTM network for seizure detection
Automatic seizure detection technology not only reduces workloads of neurologists for
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
Deep-EEG: an optimized and robust framework and method for EEG-based diagnosis of epileptic seizure
WA Mir, M Anjum, S Shahab - Diagnostics, 2023 - mdpi.com
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 …
Seizure and non-seizure EEG signals detection using 1-D convolutional neural network architecture of deep learning algorithm
TT Chowdhury, A Hossain, SA Fattah… - 2019 1st international …, 2019 - ieeexplore.ieee.org
In this paper, seizure activities of EEG signals have been detected exploiting 1-D
convolutional neural network architecture of deep learning algorithm. In past some years …
convolutional neural network architecture of deep learning algorithm. In past some years …