TY - GEN
T1 - Application of Local Scaling Exponent Profile to Heart Rate Variability Analysis
AU - Fujimoto, Yudai
AU - Watanabe, Eiichi
AU - Hayano, Junichiro
AU - Kiyono, Ken
N1 - Publisher Copyright:
© 2024 European Signal Processing Conference, EUSIPCO. All rights reserved.
PY - 2024
Y1 - 2024
N2 - The long-range correlation analysis of time series, such as detrended fluctuation analysis (DFA) and detrending moving-average analysis (DMA), has estimated a scaling exponent with the presence of a sufficiently broad scaling range indicating a linear relation in the log-log plot of the fluctuation function as the necessary condition. Therefore, it was difficult to interpret the results of the scaling analysis when the scaling range did not exist or linearity in the slope estimation broke down. However, a previous study reported that the DFA scaling exponents at very narrow intervals of heart rate variability (HRV) showed clearly different behavior between healthy subjects and patients with congestive heart failure (CHF). In this study, we propose a method to estimate a profile consisting of such local scaling exponents and apply this to long-term HRV analysis. By evaluating the discriminating ability between healthy subjects and CHF patients and between survivor and nonsurvivor groups of CHF patients by receiver operating characteristic (ROC) analysis, we demonstrate the usefulness of the local scaling exponent profile.
AB - The long-range correlation analysis of time series, such as detrended fluctuation analysis (DFA) and detrending moving-average analysis (DMA), has estimated a scaling exponent with the presence of a sufficiently broad scaling range indicating a linear relation in the log-log plot of the fluctuation function as the necessary condition. Therefore, it was difficult to interpret the results of the scaling analysis when the scaling range did not exist or linearity in the slope estimation broke down. However, a previous study reported that the DFA scaling exponents at very narrow intervals of heart rate variability (HRV) showed clearly different behavior between healthy subjects and patients with congestive heart failure (CHF). In this study, we propose a method to estimate a profile consisting of such local scaling exponents and apply this to long-term HRV analysis. By evaluating the discriminating ability between healthy subjects and CHF patients and between survivor and nonsurvivor groups of CHF patients by receiver operating characteristic (ROC) analysis, we demonstrate the usefulness of the local scaling exponent profile.
KW - fractal analysis
KW - Hurst exponent
KW - time series process
UR - http://www.scopus.com/inward/record.url?scp=85208446024&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85208446024&partnerID=8YFLogxK
U2 - 10.23919/eusipco63174.2024.10715171
DO - 10.23919/eusipco63174.2024.10715171
M3 - Conference contribution
AN - SCOPUS:85208446024
T3 - European Signal Processing Conference
SP - 726
EP - 729
BT - 32nd European Signal Processing Conference, EUSIPCO 2024 - Proceedings
PB - European Signal Processing Conference, EUSIPCO
T2 - 32nd European Signal Processing Conference, EUSIPCO 2024
Y2 - 26 August 2024 through 30 August 2024
ER -