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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 …
and a functional component obtained from a section of a pattern. Extracted features are …
Automated epileptic seizure detection methods: a review study
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 …
(Mormann, Andrzejak, Elger & Lehnertz, 2007). It is characterized by sudden recurrent and …
A machine learning approach to epileptic seizure prediction using Electroencephalogram (EEG) Signal
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 …
regions and physiological states for seizure detection. Neurophysiologists will find the work …
Epileptic seizure detection in EEGs using time–frequency analysis
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 …
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
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 …
is the recurrent seizures. Careful analysis of the electroencephalogram (EEG) recordings …
Wavelet-based EEG processing for epilepsy detection using fuzzy entropy and associative petri net
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 …
consciousness and can have a severe negative impact on long-term cognitive function …
Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection
D Wang, D Miao, C **e - 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 …
seizure detection is proposed. The system includes the following three stages:(i) original …
Automatic feature extraction using genetic programming: An application to epileptic EEG classification
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 …
original feature database with the aim of improving the discriminatory performance of a …
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 …
in this study. Method In order to assess the impact of the alternative definitions of the …
Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis
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 …
preprocessing of EEG signals we extract representative features in time, frequency and time …