Multiscale fluctuation-based dispersion entropy and its applications to neurological diseases

Azami, H., Arnold, S.E., Sanei, S. ORCID: 0000-0002-3437-2801, Chang, Z., Sapiro, G., Escudero, J. and Gupta, A.S., 2019. Multiscale fluctuation-based dispersion entropy and its applications to neurological diseases. IEEE Access, 7, pp. 68718-68733. ISSN 2169-3536

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Abstract

Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuation-based dispersion patterns. To quantify the physiological dynamics over multiple time scales, multiscale FDispEn (MFDE) is developed in this paper. MFDE is robust to the presence of baseline wanders or trends in the data. We evaluate MFDE, compared with popular multiscale sample entropy (MSE), multiscale fuzzy entropy (MFE), and the recently introduced multiscale dispersion entropy (MDE), on selected synthetic data and five neurological diseases’ datasets: 1) focal and non-focal electroencephalograms (EEGs); 2) walking stride interval signals for young, elderly, and Parkinson’s subjects; 3) stride interval fluctuations for Huntington’s disease and amyotrophic lateral sclerosis; 4) EEGs for controls and Alzheimer’s disease patients; and 5) eye movement data for Parkinson’s disease and ataxia. The MFDE avoids the problem of the undefined MSE values and, compared with the MFE and MSE, leads to more stable entropy values over the scale factors for white and pink noises. Overall, the MFDE is the fastest and most consistent method for the discrimination of different states of neurological data, especially where the mean value of a time series considerably changes along with the signal (e.g., eye movement data). This paper shows that MFDE is a relevant new metric to gain further insights into the dynamics of neurological diseases’ recordings. The MATLAB codes for the MFDE and its refined composite form are available in Xplore.

Item Type: Journal article
Publication Title: IEEE Access
Creators: Azami, H., Arnold, S.E., Sanei, S., Chang, Z., Sapiro, G., Escudero, J. and Gupta, A.S.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Volume: 7
ISSN: 2169-3536
Identifiers:
NumberType
10.1109/access.2019.2918560DOI
Divisions: Schools > School of Science and Technology
Depositing User: Linda Sullivan
Date Added: 17 Jun 2019 08:45
Last Modified: 17 Jun 2019 08:45
URI: http://irep.ntu.ac.uk/id/eprint/36820

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