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

Bo Shi,Chaochao Yuan,Peng Li,Shuihua Wang,Yudong Zhang

doi:10.3390/e19100568

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.

Highlights

Reduced heart rate variability (HRV), a sign of impaired cardiovascular autonomic control [1], has been associated with elevated risk for cardiovascular disease in the general population [2,3,4], and increased mortality in patients with various circulatory system diseases [5,6,7,8]
An average of 375 (SD: 46; min: 307; max: 485) RR intervals were obtained from the 16 participants during theEntropy
sample entropy (SampEn), and fuzzy entropy (FuzzyEn)-l; Under corrected ApEn (cApEn) is positively correlated with SampEn, FuzzyEn-g, and FuzzyEn-l; SampEn is positively correlated with

Summary

Introduction

Reduced heart rate variability (HRV), a sign of impaired cardiovascular autonomic control [1], has been associated with elevated risk for cardiovascular disease in the general population [2,3,4], and increased mortality in patients with various circulatory system diseases [5,6,7,8]. HRV, by definition, indicates the tiny fluctuations of the time intervals between consecutive normal sinus heartbeats. It can be extracted from the electrocardiographic (ECG) recordings. Entropy 2017, 19, 568 simple, non-invasive, and cost-efficient, HRV has emerged as a promising tool for assessing risk for cardiovascular diseases and monitoring disease progression. HRV is usually measured under well-controlled conditions (e.g., resting supine or seated position) over a short period (e.g., 5–30 min). The long-term ambulatory measurement facilitates the track of HRV changes with activities of free living (e.g., exercise) [10]. The exercise-evoked HRV changes could potentially provide disease-related information [11] but may be overlooked by single laboratory assessments that usually do not last long. A couple of previous studies have examined acute HRV changes induced by different activity patterns, e.g., intense exercise or low-intensity exercise, isometric or dynamic exercise [12,13,14,15,16,17,18,19,20,21]

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