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 …

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 …

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 …

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 …

A LSTM-CNN Model for Epileptic Seizures Detection using EEG Signal

N Jiwani, K Gupta, MHU Sharif… - … on Emerging Smart …, 2022 - ieeexplore.ieee.org
Neurologists visually inspect electroencephalogram (EEG) reports to get the epilepsy
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …

A novel end-to-end approach for epileptic seizure classification from scalp EEG data using deep learning technique

PR Kumar, B Shilpa, RK Jha, SN Mohanty - International Journal of …, 2023 - Springer
Early detection and proper treatment of epilepsy seizure is essential and meaningful to
those who suffer from this disease. Symptoms of seizures are confusion, abnormal gazing …

A difference attention ResNet-LSTM network for epileptic seizure detection using EEG signal

X Qiu, F Yan, H Liu - Biomedical Signal Processing and Control, 2023 - Elsevier
Epileptic seizures can affect the patient's physical function and cause irreversible damage to
their brain. It is vital to detect epilepsy seizures in time and give patients antiepileptic …

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 …

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 …

Epileptic-net: an improved epileptic seizure detection system using dense convolutional block with attention network from EEG

MS Islam, K Thapa, SH Yang - Sensors, 2022 - mdpi.com
Epilepsy is a complex neurological condition that affects a large number of people
worldwide. Electroencephalography (EEG) measures the electrical activity of the brain and …