Classification of seizure and seizure-free EEG signals using local binary patterns
Local binary pattern (LBP) is a texture descriptor that has been proven to be quite effective
for various image analysis tasks in image processing. In this paper one-dimensional local …
for various image analysis tasks in image processing. In this paper one-dimensional local …
Exploring the applicability of transfer learning and feature engineering in epilepsy prediction using hybrid transformer model
Objective: Epilepsy prediction algorithms offer patients with drug-resistant epilepsy a way to
reduce unintended harm from sudden seizures. The purpose of this study is to investigate …
reduce unintended harm from sudden seizures. The purpose of this study is to investigate …
[HTML][HTML] Absence seizure control by a brain computer interface
VA Maksimenko, S Van Heukelum, VV Makarov… - Scientific Reports, 2017 - nature.com
The ultimate goal of epileptology is the complete abolishment of epileptic seizures. This
might be achieved by a system that predicts seizure onset combined with a system that …
might be achieved by a system that predicts seizure onset combined with a system that …
Epileptic seizure detection using lacunarity and Bayesian linear discriminant analysis in intracranial EEG
W Zhou, Y Liu, Q Yuan, X Li - IEEE Transactions on Biomedical …, 2013 - ieeexplore.ieee.org
Automatic seizure detection plays an important role in long-term epilepsy monitoring, and
seizure detection algorithms have been intensively investigated over the years. This paper …
seizure detection algorithms have been intensively investigated over the years. This paper …
EEG-based prediction of epileptic seizures using phase synchronization elicited from noise-assisted multivariate empirical mode decomposition
In this study, we examined the phase locking value (PLV) for seizure prediction, particularly,
in the gamma frequency band. We prepared simulation data and 65 clinical cases of …
in the gamma frequency band. We prepared simulation data and 65 clinical cases of …
A multi-view deep learning method for epileptic seizure detection using short-time fourier transform
With the advances in pervasive sensor technologies, physiological signals can be captured
continuously to prevent the serious outcomes caused by epilepsy. Detection of epileptic …
continuously to prevent the serious outcomes caused by epilepsy. Detection of epileptic …
Predicting epileptic seizures from scalp EEG based on attractor state analysis
H Chu, CK Chung, W Jeong, KH Cho - Computer methods and programs in …, 2017 - Elsevier
Abstract Background and Objective Epilepsy is the second most common disease of the
brain. Epilepsy makes it difficult for patients to live a normal life because it is difficult to …
brain. Epilepsy makes it difficult for patients to live a normal life because it is difficult to …
Predicting epileptic seizures in scalp EEG based on a variational Bayesian Gaussian mixture model of zero-crossing intervals
AS Zandi, R Tafreshi, M Javidan… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
A novel patient-specific seizure prediction method based on the analysis of positive zero-
crossing intervals in scalp electroencephalogram (EEG) is proposed. In a moving-window …
crossing intervals in scalp electroencephalogram (EEG) is proposed. In a moving-window …
Synchronization phenomena in human epileptic brain networks
K Lehnertz, S Bialonski, MT Horstmann, D Krug… - Journal of neuroscience …, 2009 - Elsevier
Epilepsy is a malfunction of the brain that affects over 50 million people worldwide. Epileptic
seizures are usually characterized by an abnormal synchronized firing of neurons involved …
seizures are usually characterized by an abnormal synchronized firing of neurons involved …
Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features
Y You, X Zhong, G Liu, Z Yang - Artificial Intelligence in Medicine, 2022 - Elsevier
This work proposed a novel method for automatic sleep stage classification based on the
time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a …
time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a …