Patient-specific seizure prediction using the convolutional neural networks

R Jana, S Bhattacharyya, S Das - Intelligence Enabled Research: DoSIER …, 2020 - Springer
An epileptic seizure is a disease of the central nervous system caused by abnormal activity
generated by neurons in the brain. Seizure reduces the quality of life of epileptic patients …

Use of artificial neural networks for classification intracraneal EEG signals from epileptic patients

P Marchena, M Díaz, R Esteller, I Martínez… - World Congress on …, 2009 - Springer
An epileptic seizure is an episode of abnormal electrical brain activity that might involve
partial or total consciousness loss and/or involuntary movements among others …

[HTML][HTML] Automatic detection of various epileptic seizures from EEG signal using deep learning networks

S Sheykhivand, S Meshgini, Z Mousavi - Computational Intelligence in …, 2020 - isee.ui.ac.ir
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 …

An Epileptic Seizure Detection and Classification Based on Machine Learning Techniques

L Singh, RR Janghel, SP Sahu - Next Generation Healthcare …, 2022 - api.taylorfrancis.com
There are a range of common neurological diseases referred to as epilepsy, and the term is
used to describe seizures that are uncontrollable due to abnormal electrical discharges in …

Epileptic Seizure Prediction Using Bandpass Filtering and Convolutional Neural Network

N Mustaqeem, T Rahman, JFBK Priyo… - … Conference on Machine …, 2022 - Springer
The paper proposes a generalized approach for epileptic seizure prediction rather than a
patient-specific approach. The early diagnosis of seizures may assist in reducing the …

Real-time epileptic seizure prediction based on online monitoring of pre-ictal features

H Sadeghzadeh, H Hosseini-Nejad… - Medical & biological …, 2019 - Springer
Reliable prediction of epileptic seizures is of prime importance as it can drastically change
the quality of life for patients. This study aims to propose a real-time low computational …

Process efficient artificial neural network-based approach for channel selection and classification of seizures

T Rajesh Kumar, K Geetha, G Remmiya Devi… - … Application Tools for …, 2020 - Springer
The rate of neurological and psychiatric disorders is increasing rapidly in our day-to-day life,
and epilepsy is one of the common neurological disorders in brain which is a constant …

Wavelet based features for classification of normal, ictal and interictal EEG signals

T Fathima, M Bedeeuzzaman… - Journal of Medical …, 2013 - ingentaconnect.com
Electroencephalogram (EEG) is the major diagnostic tool used for analyzing the human
epileptic seizure activity and there is a strong need of an efficient automatic seizure …

Epileptic state detection: Pre-ictal, inter-ictal, ictal

A Yayik, E Yildirim, Y Kutlu, S Yildirim - International Journal of …, 2015 - dergipark.org.tr
Epileptic seizure detection and prediction from electroencephalography (EEG) is a vital area
of research. In this study, Second-Order Difference Plot (SODP) is used to extract features …

Application of machine learning in epileptic seizure detection

LV Tran, HM Tran, TM Le, TTM Huynh, HT Tran… - Diagnostics, 2022 - mdpi.com
Epileptic seizure is a neurological condition caused by short and unexpectedly occurring
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …