Suppr超能文献

左心室收缩功能不全患者心率的小波变换模极大值与多重分形去趋势波动分析比较

Comparison of wavelet transform modulus maxima and multifractal detrended fluctuation analysis of heart rate in patients with systolic dysfunction of left ventricle.

作者信息

Galaska Rafal, Makowiec Danuta, Dudkowska Aleksandra, Koprowski Andrzej, Chlebus Krzysztof, Wdowczyk-Szulc Joanna, Rynkiewicz Andrzej

机构信息

First Department of Cardiology Medical University of Gdansk, Poland.

出版信息

Ann Noninvasive Electrocardiol. 2008 Apr;13(2):155-64. doi: 10.1111/j.1542-474X.2008.00215.x.

Abstract

BACKGROUND

In recent years the WTMM (wavelet transform modulus maxima) and MDFA (multifractal detrended fluctuation analysis) methods have become widely used techniques for the determination of nonlinear, multifractal heart rate (HR) dynamics. The purpose of our study was to compare multifractal parameters of heart rate calculated using both methods in a group of 90 patients with reduced left ventricular systolic function (rlvs group) and in a group of 39 healthy persons (nsr group).

METHODS

For each subject from the rlvs group (LVEF < or =40%) and the nsr group, a 24-hour ECG Holter monitoring was performed. The width of the multifractal spectrum and global Hurst exponent were calculated by means of WTMM and MDFA methods for 5-hour daytime and nighttime subsets.

RESULTS

The width of the multifractal spectrum was significantly lower and the Hurst exponent was significantly higher in rlvs group in comparison to nsr group both during diurnal activity and nocturnal rest according to MDFA and only during diurnal activity according to WTMM method. In both groups we observed significant differences of the multifractal spectrum width and the global Hurst exponent between the nighttime and daytime recordings.

CONCLUSIONS

MDFA seems to be more sensitive as compared with WTMM method in differentiation between multifractal properties of the heart rate in healthy subjects and patients with left ventricular systolic dysfunction.

摘要

背景

近年来,小波变换模极大值(WTMM)和多重分形去趋势波动分析(MDFA)方法已成为用于确定非线性、多重分形心率(HR)动力学的广泛使用的技术。我们研究的目的是比较在90例左心室收缩功能降低患者组(rlvs组)和39例健康人组(nsr组)中使用这两种方法计算的心率多重分形参数。

方法

对rlvs组(左心室射血分数[LVEF]≤40%)和nsr组的每个受试者进行24小时动态心电图监测。通过WTMM和MDFA方法计算5小时白天和夜间子集的多重分形谱宽度和全局赫斯特指数。

结果

根据MDFA方法,在白天活动和夜间休息期间,rlvs组的多重分形谱宽度显著更低,赫斯特指数显著更高,而根据WTMM方法仅在白天活动期间如此。在两组中,我们观察到夜间和白天记录之间的多重分形谱宽度和全局赫斯特指数存在显著差异。

结论

与WTMM方法相比,MDFA在区分健康受试者和左心室收缩功能障碍患者心率的多重分形特性方面似乎更敏感。

相似文献

2
Aging in autonomic control by multifractal studies of cardiac interbeat intervals in the VLF band.
Physiol Meas. 2011 Oct;32(10):1681-99. doi: 10.1088/0967-3334/32/10/014. Epub 2011 Sep 19.
3
Wavelet versus detrended fluctuation analysis of multifractal structures.
Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Jul;74(1 Pt 2):016103. doi: 10.1103/PhysRevE.74.016103. Epub 2006 Jul 6.
4
Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization.
Comput Biol Med. 2015 May;60:66-73. doi: 10.1016/j.compbiomed.2015.02.012. Epub 2015 Feb 23.
7
Multifractal analysis for grading complex fractionated electrograms in atrial fibrillation.
Physiol Meas. 2015 Nov;36(11):2269-84. doi: 10.1088/0967-3334/36/11/2269. Epub 2015 Oct 9.
8
Wavelet leader multifractal analysis of heart rate variability in atrial fibrillation.
J Electrocardiol. 2018 Nov-Dec;51(6S):S83-S87. doi: 10.1016/j.jelectrocard.2018.08.030. Epub 2018 Aug 23.

引用本文的文献

1
Time-variability of muscle oxygen saturation during graded maximal exercise.
Eur J Appl Physiol. 2025 Jul 21. doi: 10.1007/s00421-025-05871-6.
2
Toxic Metal -Mediated Neurodegradation: A Focus on Glutathione and GST Gene Variants.
Arch Razi Inst. 2022 Apr 30;77(2):525-536. doi: 10.22092/ARI.2021.356279.1816. eCollection 2022 Apr.
4
Influence of age and aerobic fitness on the multifractal characteristics of electrocardiographic RR time-series.
Front Physiol. 2013 May 13;4:100. doi: 10.3389/fphys.2013.00100. eCollection 2013.
5
The year of 2008 in electrocardiology.
Ann Noninvasive Electrocardiol. 2010 Jan;15(1):85-9. doi: 10.1111/j.1542-474X.2009.00347.x.

本文引用的文献

1
Multiscale entropy analysis of biological signals.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Feb;71(2 Pt 1):021906. doi: 10.1103/PhysRevE.71.021906. Epub 2005 Feb 18.
2
1/f scaling in heart rate requires antagonistic autonomic control.
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Nov;70(5 Pt 1):050901. doi: 10.1103/PhysRevE.70.050901. Epub 2004 Nov 16.
3
Self-affine fractal variability of human heartbeat interval dynamics in health and disease.
Eur J Appl Physiol. 2003 Oct;90(3-4):305-16. doi: 10.1007/s00421-003-0915-2. Epub 2003 Aug 27.
4
Quantitative analysis of heart rate variability.
Chaos. 1995 Mar;5(1):88-94. doi: 10.1063/1.166090.
5
Effect of nonstationarities on detrended fluctuation analysis.
Phys Rev E Stat Nonlin Soft Matter Phys. 2002 Apr;65(4 Pt 1):041107. doi: 10.1103/PhysRevE.65.041107. Epub 2002 Apr 8.
8
Behavioral-independent features of complex heartbeat dynamics.
Phys Rev Lett. 2001 Jun 25;86(26 Pt 1):6026-9. doi: 10.1103/PhysRevLett.86.6026.
9
Magnitude and sign correlations in heartbeat fluctuations.
Phys Rev Lett. 2001 Feb 26;86(9):1900-3. doi: 10.1103/PhysRevLett.86.1900.
10
Correlated and uncorrelated regions in heart-rate fluctuations during sleep.
Phys Rev Lett. 2000 Oct 23;85(17):3736-9. doi: 10.1103/PhysRevLett.85.3736.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验