Automatic seizure detection by convolutional neural networks with computational complexity analysis

D Cimr, H Fujita, H Tomaskova, R Cimler… - Computer Methods and …, 2023 - Elsevier
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 …

Automatic seizure detection using fully convolutional nested LSTM

Y Li, Z Yu, Y Chen, C Yang, Y Li… - International journal of …, 2020 - World Scientific
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 …

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 …

Epileptic seizures detection on EEG signal using deep learning techniques

D Sagga, A Echtioui, R Khemakhem… - … for Signal and …, 2022 - ieeexplore.ieee.org
Epilepsy is a chronic brain disease that affects a large percentage of the psychiatric
population, and its progression can be fatal. It is a major public health problem as well as a …

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 …

CNN based framework for detection of epileptic seizures

M Sameer, B Gupta - Multimedia tools and applications, 2022 - Springer
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 …

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 …

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 …

Scalp EEG classification using deep Bi-LSTM network for seizure detection

X Hu, S Yuan, F Xu, Y Leng, K Yuan, Q Yuan - Computers in Biology and …, 2020 - Elsevier
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 …

Automated epilepsy seizure detection from EEG signal based on hybrid CNN and LSTM model

SK Pandey, RR Janghel, PK Mishra… - Signal, Image and Video …, 2023 - Springer
Epilepsy is a neurological disorder that affects the normal functioning of the brain. More than
10% of the population across the globe is affected by this disorder. Electroencephalogram …