Sample Entropy Analysis of Heart Rate Variability during Rest and Exercise in Hypoxia

Walking is an everyday activity in our daily life. Because walking affects heart rate variability, in this research, for the first time, we analyzed the coupling among the alterations of the complexity of walking paths and heart rate. We benefited from the fractal theory and sample entropy to evaluate the influence of the complexity of paths on the complexity of heart rate variability (HRV) during walking. We calculated the fractal exponent and sample entropy of the R-R time series for nine participants who walked on four paths with various complexities. The findings showed a strong coupling among the alterations of fractal dimension (an indicator of complexity) of HRV and the walking paths. Besides, the result of the analysis of sample entropy also verified the obtained results from the fractal analysis. In further studies, we can analyze the coupling among the alterations of the complexities of other physiological signals and walking paths.

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Multiscale entropy analysis of heart rate variability in sinoaortic denervated rats

Autonomic Neuroscience ◽

10.1016/j.autneu.2015.07.079 ◽

2015 ◽

Vol 192 ◽

pp. 78

Author(s):

L.E.V. Silva ◽

J.A. Castania ◽

H.C. Salgado ◽

R. Fazan

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Multiscale Entropy ◽

Entropy Analysis

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A Hybrid Signal Processing of RR Intervals from QTc Variation Searching Arrhythmia and Improving Heart Rate Variability Assessment in Acute Large Artery Ischemic Stroke

Journal of Medical Engineering ◽

10.1155/2016/9823026 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6

Author(s):

S. Rangsungnoen ◽

P. Chanbenjapipu ◽

N. Mathuradavong ◽

K. Suwanprasert

Keyword(s):

Heart Rate ◽

Signal Processing ◽

Heart Rate Variability ◽

Acute Stroke ◽

Sample Entropy ◽

Scaling Exponent ◽

Large Artery ◽

Qrs Detection ◽

Poincaré Plot ◽

Mean Heart Rate

Sudden death caused by abnormal QTc and atrial fibrillation (AF) has been reported in stroke. Heart rate variability (HRV) is reduced with missing beats of RRI during arrhythmic episode and abnormal QTc variation during acute stroke. In this study, we develop a hybrid signal processing by Pan Tompkins QRS detection and Kalman filter estimator for meaningful missing beats and searching AF with prolonged QTc. We use this hybrid model to investigate RRIs of Lead II ECG in thirty acute stroke patients with long QTc and AF (LQTc-AF) and normal QTc without AF (NQTc-nonAF) and then assess them by HRV. In LQTc-AF Kalman, higher mean heart rate with lower mean RRIs compared to NQTc-nonAF Kalman was characterized. LQTc-AF Kalman showed significant increase in SDNN, HF, SD2, SD2/SD1, and sample entropy. SDNN and HF associated with high RMSSD, pNN50, and SD1 reflect predominant parasympathetic drive for sympathovagal balance in LQTc-AF Kalman. Greater SD2, SD2/SD1, and sample entropy indicate more scatter of Poincaré plot. Compared with conventional Labchart, fractal scaling exponent of α1 (DFA) is higher in LQTc-AF Kalman. Remarkable complexity with parasympathetic drive in LQTc-AF Kalman suggests an influence of missing beats during stroke.

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