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 …

A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals

A Shoeibi, N Ghassemi, R Alizadehsani… - Expert Systems with …, 2021 - Elsevier
Epilepsy, a brain disease generally associated with seizures, has tremendous effects on
people's quality of life. Diagnosis of epileptic seizures is commonly performed on …

Epileptic seizure detection and prediction in EEGs using power spectra density parameterization

S Liu, J Wang, S Li, L Cai - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Power spectrum analysis is one of the effective tools for classifying epileptic signals based
on electroencephalography (EEG) recordings. However, the conflation of periodic and …

Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features

A Malekzadeh, A Zare, M Yaghoobi, HR Kobravi… - Sensors, 2021 - mdpi.com
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …

Seizure prediction based on transformer using scalp electroencephalogram

J Yan, J Li, H Xu, Y Yu, T Xu - Applied Sciences, 2022 - mdpi.com
Epilepsy is a chronic and recurrent brain dysfunction disease. An acute epileptic attack will
interfere with a patient's normal behavior and consciousness, having a great impact on their …

[HTML][HTML] Identification of epileptic EEG signals using convolutional neural networks

R Abiyev, M Arslan, J Bush Idoko, B Sekeroglu… - Applied sciences, 2020 - mdpi.com
Epilepsy is one of the chronic neurological disorders that is characterized by a sudden burst
of excess electricity in the brain. This abnormality appears as a seizure, the detection of …

Epileptic seizure detection in EEG using mutual information-based best individual feature selection

KM Hassan, MR Islam, TT Nguyen, MKI Molla - Expert Systems with …, 2022 - Elsevier
Epilepsy is a group of neurological disorders that affect normal brain activities and human
behavior. Electroencephalogram based automatic epileptic seizure detection has significant …

Automated FBSE-EWT based learning framework for detection of epileptic seizures using time-segmented EEG signals

A Anuragi, DS Sisodia, RB Pachori - Computers in Biology and Medicine, 2021 - Elsevier
Epilepsy is a neurological disorder that has severely affected many people's lives across the
world. Electroencephalogram (EEG) signals are used to characterize the brain's state and …

Automatic epileptic seizure detection via Stein kernel-based sparse representation

H Peng, C Lei, S Zheng, C Zhao, C Wu, J Sun… - Computers in Biology …, 2021 - Elsevier
Epileptic seizure detection is of great significance in the diagnosis of epilepsy and relieving
the heavy workload of visual inspection of electroencephalogram (EEG) recordings. This …

An efficient method for identification of epileptic seizures from EEG signals using Fourier analysis

VK Mehla, A Singhal, P Singh, RB Pachori - Physical and Engineering …, 2021 - Springer
Epilepsy is a disease recognized as the chronic neurological dysfunction of the human brain
which is described by the sudden and excessive electrical discharges of the brain cells …