Quantifying the dynamics of electroencephalographic (EEG) signals to distinguish alcoholic and non-alcoholic subjects using an MSE based K-d tree algorithm

In this paper, we have employed K-d tree algorithmic based multiscale entropy analysis (MSE) to distinguish alcoholic subjects from non-alcoholic ones. Traditional MSE techniques have been used in many applications to quantify the dynamics of physiological time series at multiple temporal scales. Ho...

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Bibliographic Details

Published in:	Biomedizinische Technik Vol. 63; no. 4; p. 481
Main Authors:	Hussain, Lal, Aziz, Wajid, Saeed, Sharjil, Shah, Saeed Arif, Nadeem, Malik Sajjad A, Awan, Imtiaz Ahmed, Abbas, Ali, Majid, Abdul, Kazmi, Syed Zaki Hassan
Format:	Journal Article
Language:	English
Published:	Germany 01.08.2018
Subjects:	Algorithms Electroencephalography - methods Entropy Reproducibility of Results Sensitivity and Specificity fast multiscale sample entropy (fMSE) complexity analysis electroencephalogram (EEG) multiscale sample entropy (MSE)
ISSN:	1862-278X, 1862-278X
Online Access:	Get more information
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