scholarly journals Complexity-Based Decoding of the Coupling Among Heart Rate Variability (HRV) and Walking Path

2020 ◽  
Vol 11 ◽  
Author(s):  
Shahul Mujib Kamal ◽  
Mohammad Hossein Babini ◽  
Ondrej Krejcar ◽  
Hamidreza Namazi
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Fractal Dimension ◽  
Daily Life ◽  
Fractal Theory ◽  
Sample Entropy ◽  
Physiological Signals ◽  
Everyday Activity ◽  
First Time

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.

scholarly journals COMPLEXITY AND INFORMATION-BASED ANALYSIS OF THE HEART RATE VARIABILITY (HRV) WHILE SITTING, HAND BIKING, WALKING, AND RUNNING

Fractals ◽  
2021 ◽  
pp. 2150201
Author(s):  
HAMIDREZA NAMAZI
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Fractal Dimension ◽  
Information Content ◽  
Shannon Entropy ◽  
Human Activities ◽  
Complex Structure ◽  
Sample Entropy ◽  
Heart Activity

Analysis of the variations of heart activity during different human activities is an important area of research in sport sciences. Therefore, in this paper, we evaluated the variations of heart activity for 23 subjects while sitting, hand biking, walking, and running. Since the obtained R-R time series (as the indicator of heart rate variability (HRV)) has a complex structure that contains information, we employed fractal dimension, sample entropy, and Shannon entropy for our analysis. According to the results, doing a harder activity causes a more significant alteration in the complexity and information content of HRV. The results of statistical analyses also verified the obtained results. Similar investigations can be conducted in case of other activities to evaluate the variations in heart activity in different conditions.

scholarly journals AGE-BASED ANALYSIS OF HEART RATE VARIABILITY (HRV) FOR PATIENTS WITH CONGESTIVE HEART FAILURE

Fractals ◽  
2021 ◽  
pp. 2150135
Author(s):  
HAMIDREZA NAMAZI ◽  
DUMITRU BALEANU ◽  
ONDREJ KREJCAR
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Congestive Heart Failure ◽  
Heart Rate Variability ◽  
Fractal Dimension ◽  
Age Groups ◽  
Approximate Entropy ◽  
Sample Entropy ◽  
Heart Activity ◽  
Complexity Measures

It is known that heart activity changes during aging. In this paper, we evaluated alterations of heart activity from the complexity point of view. We analyzed the variations of heart rate of patients with congestive heart failure that are categorized into four different age groups, namely 30–39, 50–59, 60–69, and 70–79 years old. For this purpose, we employed three complexity measures that include fractal dimension, sample entropy, and approximate entropy. The results showed that the trend of increment of subjects’ age is reflected in the trend of increment of the complexity of heart rate variability (HRV) since the values of fractal dimension, approximate entropy, and sample entropy increase as subjects get older. The analysis of the complexity of other physiological signals can be further considered to investigate the variations of activity of other organs due to aging.

Evaluation of Importance of Central Effects of Atenolol and Metoprolol Measured by Heart Rate Variability During Mental Performance Tasks, Physical Exercise, and Daily Life in Stable Postinfarct Patients

Circulation ◽  
1995 ◽  
Vol 92 (12) ◽  
pp. 3415-3423 ◽  
Author(s):  
Ype S. Tuininga ◽  
Harry J.G.M. Crijns ◽  
Jan Brouwer ◽  
Maarten P. van den Berg ◽  
Arie J. Man in’t Veld ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Physical Exercise ◽  
Daily Life ◽  
Mental Performance ◽  
Performance Tasks ◽  
Central Effects

Runoff Fractal Dimension of Songhua River Basin in Harbin Station Based on Db4 Wavelet

2012 ◽  
Vol 550-553 ◽  
pp. 2537-2540
Author(s):  
Hai Yan Gu ◽  
Yong Wang ◽  
Lei Yu
Keyword(s):  
Time Series ◽  
Fractal Dimension ◽  
River Basin ◽  
Fractal Theory ◽  
Measurement Methods ◽  
Self Similarity ◽  
Songhua River ◽  
Songhua River Basin ◽  
The Songhua River Basin ◽  
The Songhua River

The wavelet analysis and fractal theory into the analysis of hydrological time series, fluctuations in hydrological runoff sequence given the complexity of the measurement methods--- fractal dimension. The real monthly runoffs of 28 years from Songhua River basin in Harbin station are selected as research target. Wavelet transform combined with spectrum method is used to calculate the fractal dimension of runoff. Moreover, the result demonstrates that the runoff in Songhua River basin has the characteristic of self-similarity, and the complexity of runoff in the Songhua River basin in Harbin station is described quantificationally.

On the fractal nature of heart rate variability in humans: effects of respiratory sinus arrhythmia

1995 ◽  
Vol 269 (2) ◽  
pp. H480-H486 ◽  
Author(s):  
Y. Yamamoto ◽  
J. O. Fortrat ◽  
R. L. Hughson
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Coarse Graining ◽  
Resting Heart Rate ◽  
Breathing Frequency ◽  
Fractal Nature ◽  
Sinus Arrhythmia ◽  
Spectral Exponent ◽  
Random Fractal

The purpose of the present study was to investigate the basic fractal nature of the variability in resting heart rate (HRV), relative to that in breathing frequency (BFV) and tidal volume (TVV), and to test the hypothesis that fractal HRV is due to the fractal BFV and/or TVV in humans. In addition, the possible fractal nature of respiratory volume curves (RVC) and HRV was observed. In the first study, eight subjects were tested while they sat quietly in a comfortable chair for 60 min. Beat-to-beat R-R intervals, i.e., HRV, and breath-by-breath BFV and TVV were measured. In the second study, six subjects were tested while they were in the supine position for 20-30 min. The RVC was monitored continuously together with HRV. Coarse-graining spectral analysis (Yamamoto, Y., and R. L. Hughson, Physica D 68: 250-264, 1993) was applied to these signals to evaluate the percentage of random fractal components in the time series (%Fractal) and the spectral exponent (beta), which characterizes irregularity of the signals. The estimates of beta were determined for each variable only over the range normally used to evaluate HRV. Values for %Fractal and beta of both BFV and TVV were significantly (P < 0.05) greater than those for HRV. In addition, there was no significant (P > 0.05) correlation between the beta values of HRV relative to either BFV (r = 0.14) or TVV (r = 0.34). RVC showed a smooth oscillation as compared with HRV; %Fractal for RVC (42.3 +/- 21.7%, mean +/- SD) was significantly (P < 0.05) lower than that for HRV (78.5 +/- 4.2%).(ABSTRACT TRUNCATED AT 250 WORDS)

An application of fractional differintegration to heart rate variability time series

2013 ◽  
Vol 111 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Miguel A. García-González ◽  
Mireya Fernández-Chimeno ◽  
Lluis Capdevila ◽  
Eva Parrado ◽  
Juan Ramos-Castro
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability

Aging and spectral characteristics of the nonharmonic component of 24-h heart rate variability

1999 ◽  
Vol 276 (6) ◽  
pp. R1724-R1731 ◽  
Author(s):  
Seiichiro Sakata ◽  
Junichiro Hayano ◽  
Seiji Mukai ◽  
Akiyoshi Okada ◽  
Takao Fujinami
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Power Law ◽  
Daily Life ◽  
Spectral Characteristics ◽  
Normal Subjects ◽  
Break Point ◽  
Total Power ◽  
Interindividual Difference ◽  
Analysis Of Dynamics

To examine whether heart rate variability (HRV) during daily life shows power law behavior independently of age and interindividual difference in the total power, log-log scaled coarse-graining spectra of the nonharmonic component of 24-h HRV were studied in 62 healthy men (age 21–79 yr). The spectra declined with increasing frequency in all subjects, but they appeared as broken lines slightly bending downward, particularly in young subjects with a large total power. Regression of the spectrum by a broken line with a single break point revealed that the spectral exponent (β) was greater in the region below than above the break point (1.63 ± 0.23 vs. 0.96 ± 0.21, P < 0.001). The break point frequency increased with age ( r = 0.51, P < 0.001) and β correlated with age negatively below the break point ( r = 0.39) and positively above the break point ( r = 0.70). The contribution to interindividual difference in total power was greater from the differences in the power spectral density at frequencies closer to both ends of the frequency axis and minimal from that at −3.25 log(Hz), suggesting hingelike movement of the spectral shape at this frequency with the difference in total power. These characteristics of the 24-h HRV spectrum were simulated by an artificial signal generated by adding two noises with different β values. Given that the power law assumption is fundamental to the analysis of dynamics through the log-log scaled spectrum, our observations are substantial for physiological and clinical studies of the heartbeat dynamic during daily life and suggest that the nonharmonic component of HRV in normal subjects during daily life may include at least two 1/ f β fluctuations that differ in dynamics and age dependency.

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