Multivariate Multiscale Entropy for Brain Consciousness Analysis

Ahmed, Mosabber Uddin, Li, Ling, Cao, Jianting, Mandic, Danilo P. (2011) Multivariate Multiscale Entropy for Brain Consciousness Analysis. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE. . pp. 182-196. IEEE ISBN 978-1-4244-4121-1. E-ISBN 978-1-4577-1589-1. (doi:10.1109/IEMBS.2011.6090185) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:30735)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL: http://dx.doi.org/10.1109/IEMBS.2011.6090185

Abstract

The recently introduced multiscale entropy (MSE) analysis accounts for the complexity over multiple time scales and therefore can reveal the complex structure of the biological signal. The existing MSE algorithm deals with scalar time series whereas multivariate time series are common in experimental and biological systems. To that cause, the MSE method is extended to multivariate case in this paper. Simulation results to characterize brain consciousness supports the efficiency of this holistic approach.

Item Type:	Conference or workshop item (Paper)
DOI/Identification number:	10.1109/IEMBS.2011.6090185
Uncontrolled keywords:	entropy; time series analysis; electroencephalography; complexity theory; white noise; vectors
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Caroline Li
Date Deposited:	21 Sep 2012 09:49 UTC
Last Modified:	16 Nov 2021 10:08 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/30735 (The current URI for this page, for reference purposes)

University of Kent Author Information

Li, Ling.

Creator's ORCID:	https://orcid.org/0000-0002-4026-0216
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