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Cited by 319

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals

Open access
·2017·IEEE Transactions on Biomedical Engineering
DOI 10.1109/tbme.2017.2679136
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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: ) 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. SIGNIFICANCE: 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/1982.

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Metadata

Venue
IEEE Transactions on Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2017-12
Volume
64
Issue
12
Pages
2872-2879
ISSN
  • 0018-9294 (ISSN-L)
  • 1558-2531
DOI
10.1109/tbme.2017.2679136
OpenAlex
W2610099500
Cited by
319
References
41
FWCI
12.68
Type
journal article
Language
en
Open access
green

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