Analysis of EEG signal for seizure detection based on WPT

Electroencephalogram (EEG) is a diagnostic method that provides information about the functioning of the brain. EEG can be used to diagnose the abnormally functioning part of the brain by monitoring electrical activities. An automated system has been proposed to create a computer-based expert opinio...

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Veröffentlicht in:	Electronics letters Jg. 56; H. 25; S. 1381 - 1383
1. Verfasser:	Arı, A
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 10.12.2020
Schlagworte:	abnormally functioning part automated system binary cases binary classification brain computer‐based expert opinion diagnostic method dispersion entropy EEG signal electrical activities electroencephalography entropy evaluated classification accuracy extracted feature vector feature extraction KNN line length methods medical signal detection medical signal processing multiclass cases multiclass classification evaluated accuracy neighbour classifiers objective view pattern classification public EEG seizure dataset seizure detection signal classification Special Issue: Current Trends in Cognitive Science and Brain Computing Research and Applications support vector machine support vector machines SVM wavelet packet wavelet transforms WPT computer-based expert opinion wavelet transforms KNN SVM entropy feature extraction neighbour classifiers automated system multiclass cases WPT line length methods binary classification evaluated classification accuracy electroencephalography pattern classification multiclass classification evaluated accuracy diagnostic method support vector machines abnormally functioning part medical signal detection brain EEG signal wavelet packet signal classification medical signal processing support vector machine seizure detection public EEG seizure dataset electrical activities binary cases dispersion entropy objective view extracted feature vector
ISSN:	0013-5194, 1350-911X, 1350-911X
Online-Zugang:	Volltext
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