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Entropy 2017, 19(10), 568; https://doi.org/10.3390/e19100568

Entropy Analysis of Short-Term Heartbeat Interval Time Series during Regular Walking

1
Department of Medical Imaging, Bengbu Medical College, Bengbu 233030, China
2
Department of Informatics, University of Leicester, Leicester LE1 7RH, UK
3
School of Control Science and Engineering, Shandong University, Jinan 250061, China
4
School of Computer Science and Technology, Nanjing Normal University, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Received: 18 September 2017 / Revised: 11 October 2017 / Accepted: 21 October 2017 / Published: 24 October 2017
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Abstract

Entropy measures have been extensively used to assess heart rate variability (HRV), a noninvasive marker of cardiovascular autonomic regulation. It is yet to be elucidated whether those entropy measures can sensitively respond to changes of autonomic balance and whether the responses, if there are any, are consistent across different entropy measures. Sixteen healthy subjects were enrolled in this study. Each subject undertook two 5-min ECG measurements, one in a resting seated position and another while walking on a treadmill at a regular speed of 5 km/h. For each subject, the two measurements were conducted in a randomized order and a 30-min rest was required between them. HRV time series were derived and were analyzed by eight entropy measures, i.e., approximate entropy (ApEn), corrected ApEn (cApEn), sample entropy (SampEn), fuzzy entropy without removing local trend (FuzzyEn-g), fuzzy entropy with local trend removal (FuzzyEn-l), permutation entropy (PermEn), conditional entropy (CE), and distribution entropy (DistEn). Compared to resting seated position, regular walking led to significantly reduced CE and DistEn (both p ≤ 0.006; Cohen’s d = 0.9 for CE, d = 1.7 for DistEn), and increased PermEn (p < 0.0001; d = 1.9), while all these changes disappeared after performing a linear detrend or a wavelet detrend (<~0.03 Hz) on HRV. In addition, cApEn, SampEn, FuzzyEn-g, and FuzzyEn-l showed significant decreases during regular walking after linear detrending (all p < 0.006; 0.8 < d < 1), while a significantly increased ApEn (p < 0.0001; d = 1.9) and a significantly reduced cApEn (p = 0.0006; d = 0.8) were observed after wavelet detrending. To conclude, multiple entropy analyses should be performed to assess HRV in order for objective results and caution should be paid when drawing conclusions based on observations from a single measure. Besides, results from different studies will not be comparable unless it is clearly stated whether data have been detrended and the methods used for detrending have been specified. View Full-Text
Keywords: exercise; short-term heart rate variability (HRV); complexity; entropy; approximate entropy (ApEn); conditional entropy (CE); distribution entropy (DistEn); fuzzy entropy (FuzzyEn); permutation entropy (PermEn); sample entropy (SampEn) exercise; short-term heart rate variability (HRV); complexity; entropy; approximate entropy (ApEn); conditional entropy (CE); distribution entropy (DistEn); fuzzy entropy (FuzzyEn); permutation entropy (PermEn); sample entropy (SampEn)
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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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Shi, B.; Zhang, Y.; Yuan, C.; Wang, S.; Li, P. Entropy Analysis of Short-Term Heartbeat Interval Time Series during Regular Walking. Entropy 2017, 19, 568.

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