A novel end-to-end approach for epileptic seizure classification from scalp EEG data using deep learning technique
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 …
those who suffer from this disease. Symptoms of seizures are confusion, abnormal gazing …
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 …
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 …
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
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 …
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 …
10% of the population across the globe is affected by this disorder. Electroencephalogram …
A hybrid deep learning approach for epileptic seizure detection in EEG signals
Early detection and proper treatment of epilepsy is essential and meaningful to those who
suffer from this disease. The adoption of deep learning (DL) techniques for automated …
suffer from this disease. The adoption of deep learning (DL) techniques for automated …
Deep C-LSTM neural network for epileptic seizure and tumor detection using high-dimension EEG signals
Electroencephalography (EEG) is a common and significant tool for aiding in the diagnosis
of epilepsy and studying the human brain electrical activity. Previously, the traditional …
of epilepsy and studying the human brain electrical activity. Previously, the traditional …
[HTML][HTML] Automatic detection of various epileptic seizures from EEG signal using deep learning networks
Using an intelligent method to automatically detect epileptic seizures in medical applications
is one of the most important challenges in recent years to reduce the workload of doctors in …
is one of the most important challenges in recent years to reduce the workload of doctors in …
A Hybrid LSTM-DBN Approach for Automatic Epileptic Seizure Detection compared with Normal Human Activity using EEG Signals
S Cherukuvada, R Kayalvizhi - 2023 5th International …, 2023 - ieeexplore.ieee.org
More than 2% of people throughout the globe suffer from the neurodegenerative condition
known as epilepsy. A sudden onset of convulsive seizures characterizes epilepsy, a …
known as epilepsy. A sudden onset of convulsive seizures characterizes epilepsy, a …
[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 …