Automated EEG analysis of epilepsy: a review

UR Acharya, SV Sree, G Swapna, RJ Martis… - Knowledge-Based …, 2013 - Elsevier
Epilepsy is an electrophysiological disorder of the brain, characterized by recurrent seizures.
Electroencephalogram (EEG) is a test that measures and records the electrical activity of the …

Application of entropies for automated diagnosis of epilepsy using EEG signals: A review

UR Acharya, H Fujita, VK Sudarshan, S Bhat… - Knowledge-based …, 2015 - Elsevier
Epilepsy is the neurological disorder of the brain which is difficult to diagnose visually using
Electroencephalogram (EEG) signals. Hence, an automated detection of epilepsy using …

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals

UR Acharya, SL Oh, Y Hagiwara, JH Tan… - Computers in biology and …, 2018 - Elsevier
An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of
epilepsy. The EEG signal contains information about the electrical activity of the brain …

An automated system for epilepsy detection using EEG brain signals based on deep learning approach

I Ullah, M Hussain, H Aboalsamh - Expert Systems with Applications, 2018 - Elsevier
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …

Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system

J Kevric, A Subasi - Biomedical Signal Processing and Control, 2017 - Elsevier
In this study, three popular signal processing techniques (Empirical Mode Decomposition,
Discrete Wavelet Transform, and Wavelet Packet Decomposition) were investigated for the …

Automated diagnosis of epileptic EEG using entropies

UR Acharya, F Molinari, SV Sree… - … signal processing and …, 2012 - Elsevier
Epilepsy is a neurological disorder characterized by the presence of recurring seizures. Like
many other neurological disorders, epilepsy can be assessed by the electroencephalogram …

Artificial intelligence techniques for automated diagnosis of neurological disorders

U Raghavendra, UR Acharya, H Adeli - European neurology, 2020 - karger.com
Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …

Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals

UR Acharya, SV Sree, PCA Ang, R Yanti… - International journal of …, 2012 - World Scientific
Epilepsy, a neurological disorder, is characterized by the recurrence of seizures.
Electroencephalogram (EEG) signals, which are used to detect the presence of seizures, are …

Automated diagnosis of epilepsy using key-point-based local binary pattern of EEG signals

AK Tiwari, RB Pachori, V Kanhangad… - IEEE journal of …, 2016 - ieeexplore.ieee.org
The electroencephalogram (EEG) signals are commonly used for diagnosis of epilepsy. In
this paper, we present a new methodology for EEG-based automated diagnosis of epilepsy …

Automated epilepsy detection techniques from electroencephalogram signals: a review study

S Supriya, S Siuly, H Wang, Y Zhang - Health information science and …, 2020 - Springer
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …