Epilepsy detection from eeg data using a hybrid cnn-lstm model

MAI Neloy, A Biswas, N Nahar, MS Hossain… - … Conference on Brain …, 2022 - Springer
Abstract 'An epileptic seizure', a neurological disorder, occurs when electric burst travel over
the brain, causing the person to lose control or consciousness. Anticipating epilepsy when …

Epileptic Seizure Detection from EEG Signal Using ANN-LSTM Model

R Islam, S Debnath, R Raen, N Islam, TI Palash… - … Conference on Trends …, 2022 - Springer
Epilepsy is a well-known neurological disease caused by malfunctioning nerve activity in the
brain. These malfunctioning causes episodes called seizures. Seizures in epileptic patients …

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 …

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 …

[PDF][PDF] Integrated CWT-CNN for epilepsy detection using multiclass EEG dataset

S Naseem, K Javed, MJ Khan, S Rubab… - … Materials & Continua, 2021 - cdn.techscience.cn
Electroencephalography is a common clinical procedure to record brain signals generated
by human activity. EEGs are useful in Brain controlled interfaces and other intelligent …

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 …

Automatic detection of epilepsy EEG based on CNN-LSTM network combination model

X Liu, J Jia, R Zhang - Proceedings of the 2020 4th International …, 2020 - dl.acm.org
Using EEG to detect epilepsy is a time-consuming and laborious process. The experiments
de-signed by most of the existing classification detection technologies tend to have many …

Adopting Convolutional Long Short-Term Memory Network to Detect Seizures

A Mahajan, K Somaraj, MS Jamal… - 2023 14th International …, 2023 - ieeexplore.ieee.org
Recent advances in deep learning have enabled computer-aided medical data processing,
thus adding to automated disease diagnosis and detection. Neurologists typically diagnose …

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 …

Classification of Epileptic Seizures Based on CNN and Guided Back-Propagation for Interpretation Analysis

Y Jaramillo-Munera, LM Sepulveda-Cano… - … Conference on Smart …, 2022 - Springer
Epilepsy is a brain disorder that affects nearly 50 millions people around the world.
However, despite its high prevalence, the diagnosis of epilepsy is complex and usually …