Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time‐Frequency Domains

AS Al-Fahoum, AA Al-Fraihat - … Scholarly Research Notices, 2014 - Wiley Online Library
Technically, a feature represents a distinguishing property, a recognizable measurement,
and a functional component obtained from a section of a pattern. Extracted features are …

Automated epileptic seizure detection methods: a review study

AT Tzallas, MG Tsipouras, DG Tsalikakis… - Epilepsy-histological …, 2012 - books.google.com
Epilepsy is a neurological disorder with prevalence of about 1-2% of the world's population
(Mormann, Andrzejak, Elger & Lehnertz, 2007). It is characterized by sudden recurrent and …

A machine learning approach to epileptic seizure prediction using Electroencephalogram (EEG) Signal

M Savadkoohi, T Oladunni, L Thompson - Biocybernetics and Biomedical …, 2020 - Elsevier
This study investigates the properties of the brain electrical activity from different recording
regions and physiological states for seizure detection. Neurophysiologists will find the work …

Wavelet-based EEG processing for epilepsy detection using fuzzy entropy and associative petri net

HS Chiang, MY Chen, YJ Huang - IEEE Access, 2019 - ieeexplore.ieee.org
Epilepsy is a common neurological disease that can cause seizures and loss of
consciousness and can have a severe negative impact on long-term cognitive function …

Epileptic seizure detection in EEGs using time–frequency analysis

AT Tzallas, MG Tsipouras… - IEEE transactions on …, 2009 - ieeexplore.ieee.org
The detection of recorded epileptic seizure activity in EEG segments is crucial for the
localization and classification of epileptic seizures. However, since seizure evolution is …

Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks

L Guo, D Rivero, J Dorado, JR Rabunal… - Journal of neuroscience …, 2010 - Elsevier
About 1% of the people in the world suffer from epilepsy. The main characteristic of epilepsy
is the recurrent seizures. Careful analysis of the electroencephalogram (EEG) recordings …

Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection

D Wang, D Miao, C Xie - Expert Systems with Applications, 2011 - Elsevier
In this study, a hierarchical electroencephalogram (EEG) classification system for epileptic
seizure detection is proposed. The system includes the following three stages:(i) original …

Spectral information of EEG signals with respect to epilepsy classification

MG Tsipouras - EURASIP Journal on Advances in Signal Processing, 2019 - Springer
Background The spectral information of the EEG signal with respect to epilepsy is examined
in this study. Method In order to assess the impact of the alternative definitions of the …

Automatic feature extraction using genetic programming: An application to epileptic EEG classification

L Guo, D Rivero, J Dorado, CR Munteanu… - Expert Systems with …, 2011 - Elsevier
This paper applies genetic programming (GP) to perform automatic feature extraction from
original feature database with the aim of improving the discriminatory performance of a …

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

D Gajic, Z Djurovic, J Gligorijevic… - Frontiers in …, 2015 - frontiersin.org
We present a new technique for detection of epileptiform activity in EEG signals. After
preprocessing of EEG signals we extract representative features in time, frequency and time …