Heart rate variability series during physical activity analyzed with multifractal techniques

Abstract Our study uses multifractal techniques to analyze time series of heart rate variability series ( RR time series) during rest and physical activity. Subsets of the RR time series data were extracted for each stage. The multifractal spectra of the RR time series data were constructed using the method developed by Chhabra and Jensen. Then, parameters such as width, symmetry, and curvature of the multifractal spectra were calculated. The multifractal spectra obtained at resting stage were broad, skewed to the right, and they had small curvatures around in the maximum. On the contrary, the subsets of the RR time series obtained during physical activity were narrow, skewed to the left, and showed an increased curvature value around the maximum. In addition, these multifractal spectrum parameters shown significant differences in series of subjects who perform physical activity regularly and sedentary. Furthermore, the results obtained from this study were compared with data from previous works involving patients with congestive heart failure and healthy subjects.

Authors

Institutions

Publication Details

Journal
Journal of Physics Complexity
Published
2024-10-17
DOI
https://doi.org/10.1088/2632-072x/ad8717
Citations
3
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
3.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heart rate variability series during physical activity analyzed with multifractal techniques

F. Angulo‐Brown, Alejandro Muñoz-Diosdado, José Alberto Zamora-Justo, Ana María Aguilar-Molina
3 citations
Journal of Physics Complexity
Complex Systems and Time Series Analysis
3.39
article

Heart rate variability series during physical activity analyzed with multifractal techniques

F. Angulo‐Brown, Alejandro Muñoz-Diosdado, José Alberto Zamora-Justo, Ana María Aguilar-Molina
article en
3 citations

Abstract

Abstract Our study uses multifractal techniques to analyze time series of heart rate variability series ( RR time series) during rest and physical activity. Subsets of the RR time series data were extracted for each stage. The multifractal spectra of the RR time series data were constructed using the method developed by Chhabra and Jensen. Then, parameters such as width, symmetry, and curvature of the multifractal spectra were calculated. The multifractal spectra obtained at resting stage were broad, skewed to the right, and they had small curvatures around in the maximum. On the contrary, the subsets of the RR time series obtained during physical activity were narrow, skewed to the left, and showed an increased curvature value around the maximum. In addition, these multifractal spectrum parameters shown significant differences in series of subjects who perform physical activity regularly and sedentary. Furthermore, the results obtained from this study were compared with data from previous works involving patients with congestive heart failure and healthy subjects.

Journal of Physics ComplexityVol. 5(4)
Instituto Politécnico Nacional (MX)
Openalex Percentile: Top 6%
Complex Systems and Time Series Analysis
3.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.