Automated seizure prediction

UR Acharya, Y Hagiwara, H Adeli - Epilepsy & Behavior, 2018 - Elsevier
In the past two decades, significant advances have been made on automated
electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number …

A novel wavelet transform-homogeneity model for sudden cardiac death prediction using ECG signals

JP Amezquita-Sanchez, M Valtierra-Rodriguez… - Journal of medical …, 2018 - Springer
Sudden cardiac death (SCD) is one of the main causes of death among people. A new
methodology is presented for predicting the SCD based on ECG signals employing the …

Animal models for epileptic foci localization, seizure detection, and prediction by electrical impedance tomography

R Wang, W Zhu, G Liang, J Xu, J Guo… - Wiley Interdisciplinary …, 2022 - Wiley Online Library
Surgical resection of lesions and closed‐loop suppression are the two main treatment
options for patients with refractory epilepsy whose symptoms cannot be managed with …

[HTML][HTML] A new methodology based on EMD and nonlinear measurements for sudden cardiac death detection

O Vargas-Lopez, JP Amezquita-Sanchez… - Sensors, 2019 - mdpi.com
Heart diseases are among the most common death causes in the population. Particularly,
sudden cardiac death (SCD) is the cause of 10% of the deaths around the world. For this …

A structured approach towards big data identification

H Ahmed, MA Ismail - IEEE Transactions on Big Data, 2021 - ieeexplore.ieee.org
Big data is a” relative” concept. It is the combination of data, application, and platform
properties. The term big data has been used with almost every problem involving large size …

Electroencephalographic response of brain stimulation by shock waves from laser generated carbon nanotube transducer

J Lee, JW Larocco, DG Paeng - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Neuromodulation is used to treat neurological disorders. Focused ultrasound can deliver
acoustic energy to local regions of the brain, including deep brain structures. In addition, it is …

[HTML][HTML] An overview of machine learning and deep learning techniques for predicting epileptic seizures

M Zurdo-Tabernero, Á Canal-Alonso… - Journal of Integrative …, 2024 - degruyter.com
Epilepsy is a neurological disorder (the third most common, following stroke and migraines).
A key aspect of its diagnosis is the presence of seizures that occur without a known cause …

Epileptic seizure prediction from multivariate EEG data using Multidimensional convolution network

X Wei, Y Wang, Z Zhang, X Cao… - 2022 7th International …, 2022 - ieeexplore.ieee.org
Background: The ability to predict coming seizures will improve the quality of life of patients
with epilepsy. Analysis of brain electrical activity using electroencephalogram (EEG) signals …

Machine Learning and Deep Learning Techniques for Epileptic Seizures Prediction: A Brief Review

M Hernández, Á Canal-Alonso, F de la Prieta… - … Conference on Practical …, 2022 - Springer
The third most common neurological disorder, only behind stroke and migraines, is
Epilepsy. The main criteria for its diagnosis are the occurrence of unprovoked seizures and …

Epileptic seizure detection from multivariate sequential signals using Multidimensional convolution network

X Wei, Y Zhou - 2022 - researchsquare.com
Background The ability to predict coming seizures will improve the quality of life of patients
with epilepsy. Analysis of brain electrical activity using multivariate sequential signals can be …