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HUMAN MODULATED HEART RATE VARIABILITY SIGNAL IN SPORTS USING MULTIFRACTAL ANALYSIS

Authors :
Jie Chu
Mohammed Basheri
Jianshe Wei
Source :
Fractals. 30
Publication Year :
2022
Publisher :
World Scientific Pub Co Pte Ltd, 2022.

Abstract

The purpose is to apply the multifractal analysis method to the research of human physiology in the process of sports. The mass index spectrum is used for multifractal analysis of heart rate variability signal based on the heart rate variability signal analysis theory and fractal theory. Finally, 10 healthy college students are selected as the experimental subjects. RAC-3003 portable electronic measuring instrument is used to collect heart rate signals in different exercise stages. Finally, the data are analyzed by [Formula: see text] and Lo-[Formula: see text] analysis methods. The results show that the lowest value of ln[Formula: see text] is 3.1 and the highest value is 7.0 in different stages in the morning, and the lowest value is 3.3 and the highest value is 7.5 in different stages in the afternoon. The average value of random signal ln[Formula: see text] gradually increases from 2.6 to 3.7; whether in the morning or in the afternoon, the average Hurst exponent during exercise is lower than that before and after exercise, and the average Hurst exponent after exercise is slightly higher than that before exercise; the long-range correlation index of heart rate variability signal in each exercise stage first increases and then decreases, and the changes of short-range correlation index and long-range correlation index are opposite; the average of fitting intercept of [Formula: see text] curve is lower than that of Lo-[Formula: see text] curve in the first and third stages; the fractal coefficient of the original data in the first and third stages of exercise is significantly higher than that in the second stage, which indicates that the overall fractal degree of heart rate variability signal before and after exercise is higher.

Details

ISSN :
17936543 and 0218348X
Volume :
30
Database :
OpenAIRE
Journal :
Fractals
Accession number :
edsair.doi...........901c14b8da0d44d97148b5f7b67ecffb