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Entropy 2017, 19(6), 257; doi:10.3390/e19060257

Time-Shift Multiscale Entropy Analysis of Physiological Signals

Department of Biomedical Engineering, Linköping University, 581 83 Linköping, Sweden
Received: 17 April 2017 / Revised: 1 June 2017 / Accepted: 2 June 2017 / Published: 5 June 2017
(This article belongs to the Special Issue Entropy in Signal Analysis)
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Abstract

Measures of predictability in physiological signals using entropy measures have been widely applied in many areas of research. Multiscale entropy expresses different levels of either approximate entropy or sample entropy by means of multiple factors for generating multiple time series, enabling the capture of more useful information than using a scalar value produced by the two entropy methods. This paper presents the use of different time shifts on various intervals of time series to discover different entropy patterns of the time series. Examples and experimental results using white noise, 1/ f noise, photoplethysmography, and electromyography signals suggest the validity and better performance of the proposed time-shift multiscale entropy analysis of physiological signals than the multiscale entropy. View Full-Text
Keywords: approximate entropy; sample entropy; multiscale entropy; higuchi’s fractal dimension; time shift; physiological signals approximate entropy; sample entropy; multiscale entropy; higuchi’s fractal dimension; time shift; physiological signals
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Pham, T.D. Time-Shift Multiscale Entropy Analysis of Physiological Signals. Entropy 2017, 19, 257.

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