Wavelet-Based Multiscale Sample Entropy and Chaotic Features for Congestive Heart Failure Recognition Using Heart Rate Variability

2015 ◽  
Vol 35 (3) ◽  
pp. 338-347 ◽  
Author(s):  
Sung-Nien Yu ◽  
Ming-Yuan Lee
Fractals ◽  
2021 ◽  
pp. 2150135
Author(s):  
HAMIDREZA NAMAZI ◽  
DUMITRU BALEANU ◽  
ONDREJ KREJCAR

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.


EP Europace ◽  
2003 ◽  
Vol 4 (Supplement_2) ◽  
pp. B15-B15
Author(s):  
F. Giraldi ◽  
M. Kloss ◽  
C. Fantoni ◽  
F. Regolip ◽  
H. Klein ◽  
...  

EP Europace ◽  
2005 ◽  
Vol 7 (Supplement_1) ◽  
pp. 137-138 ◽  
Author(s):  
A. Piatkowska ◽  
K. Szymanowska ◽  
A. Nowicka ◽  
M. Kandziora ◽  
M. Wierzchowiecki ◽  
...  

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