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Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals

Azami, H, Rostaghi, M, Abasolo, Daniel Emilio and Escudero, J (2017) Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals IEEE Transactions on Biomedical Engineering.

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Abstract

Objective: We propose a novel complexity measure to overcome the deficiencies of the widespread and powerful multiscale entropy (MSE), including, MSE values may be undefined for short signals, and MSE is slow for real-time applications. Methods: We introduce multiscale dispersion entropy (DisEn - MDE) as a very fast and powerful method to quantify the complexity of signals. MDE is based on our recently developed DisEn, which has a computation cost of O(N), compared with O(N2) for sample entropy used in MSE. We also propose the refined composite MDE (RCMDE) to improve the stability of MDE. Results: We evaluate MDE, RCMDE, and refined composite MSE (RCMSE) on synthetic signals and three biomedical datasets. The MDE, RCMDE, and RCMSE methods show similar results, although the MDE and RCMDE are faster, lead to more stable results, and discriminate different types of physiological signals better than MSE and RCMSE. Conclusion: For noisy short and long time series, MDE and RCMDE are noticeably more stable than MSE and RCMSE, respectively. For short signals, MDE and RCMDE, unlike MSE and RCMSE, do not lead to undefined values. The proposed MDE and RCMDE are significantly faster than MSE and RCMSE, especially for long signals, and lead to larger differences between physiological conditions known to alter the complexity of the physiological recordings.

Item Type: Article
Subjects : Mechanical Engineering Science
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Azami, HUNSPECIFIEDUNSPECIFIED
Rostaghi, MUNSPECIFIEDUNSPECIFIED
Abasolo, Daniel EmilioD.Abasolo@surrey.ac.ukUNSPECIFIED
Escudero, JUNSPECIFIEDUNSPECIFIED
Date : 8 March 2017
Identification Number : 10.1109/TBME.2017.2679136
Copyright Disclaimer : Copyright 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords : Complexity, multiscale dispersion entropy, nonlinearity, biomedical signals, electroencephalogram, blood pressure.
Related URLs :
Additional Information : MDE and RCMDE are expected to be useful for the analysis of physiological signals thanks to their ability to distinguish different types of dynamics. The Matlab codes used in this paper are freely available at http://dx.doi.org/10.7488/ds/1709
Depositing User : Symplectic Elements
Date Deposited : 01 Mar 2017 14:33
Last Modified : 19 Jul 2017 11:29
URI: http://epubs.surrey.ac.uk/id/eprint/813655

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