• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

健康人和充血性心力衰竭患者RR心动图的多重分形谱曲率:一种评估健康状况的新工具

Multifractal Spectrum Curvature of RR Tachograms of Healthy People and Patients with Congestive Heart Failure, a New Tool to Assess Health Conditions.

作者信息

Aguilar-Molina Ana María, Angulo-Brown Fernando, Muñoz-Diosdado Alejandro

机构信息

Departamento de Física, Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, Edif. No.9 U.P. Zacatenco, Mexico City 07738, Mexico.

Unidad Profesional Interdisciplinaria de Biotecnología, Instituto Politécnico Nacional, Av. Acueducto s/n, Barrio la Laguna, Ticomán, Mexico City 07340, Mexico.

出版信息

Entropy (Basel). 2019 Jun 11;21(6):581. doi: 10.3390/e21060581.

DOI:10.3390/e21060581
PMID:33267295
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7515070/
Abstract

We calculate the multifractal spectra of heartbeat RR-interval time series (tachograms) of healthy subjects and patients with congestive heart failure (CHF). From these time series, we obtained new subseries of 6 h durations when healthy persons and patients were asleep and awake respectively. For each time series and subseries, we worked out the multifractal spectra with the Chhabra and Jensen method and found that their graphs have different shapes for CHF patients and healthy persons. We suggest to measure two parameters: the curvature around the maximum and the symmetry for all these multifractal spectra graphs, because these parameters were different for healthy and CHF subjects. Multifractal spectra of healthy subjects tend to be right skewed especially when the subjects are asleep and the curvature around the maximum is small compared with the curvature around the maximum of the CHF multifractal spectra; that is, the spectra of patients tend to be more pointed around the maximum. In CHF patients, we also have encountered differences in the curvature of the multifractal spectra depending on their respective New York Heart Association (NYHA) index.

摘要

我们计算了健康受试者和充血性心力衰竭(CHF)患者心跳RR间期时间序列(心动周期图)的多重分形谱。从这些时间序列中,我们分别获取了健康人和患者在睡眠和清醒状态下时长为6小时的新子序列。对于每个时间序列和子序列,我们用Chhabra和Jensen方法算出多重分形谱,发现CHF患者和健康人的多重分形谱图形状不同。我们建议测量所有这些多重分形谱图的两个参数:最大值处的曲率和对称性,因为健康受试者和CHF受试者的这些参数不同。健康受试者的多重分形谱往往向右偏斜,尤其是当受试者处于睡眠状态时,且最大值处的曲率与CHF多重分形谱最大值处的曲率相比很小;也就是说,患者的谱在最大值附近往往更尖锐。在CHF患者中,我们还发现多重分形谱的曲率因其各自的纽约心脏协会(NYHA)分级而有所不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/70833f19aaab/entropy-21-00581-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/bb7a16a15034/entropy-21-00581-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/7e9d805d6586/entropy-21-00581-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/e9bfe19a22dd/entropy-21-00581-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/29f3872db6af/entropy-21-00581-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/59367091df6b/entropy-21-00581-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/db89c856cdb2/entropy-21-00581-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/baed8c4ecf6c/entropy-21-00581-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/cfd4906146cf/entropy-21-00581-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/5b598659de88/entropy-21-00581-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/70833f19aaab/entropy-21-00581-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/bb7a16a15034/entropy-21-00581-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/7e9d805d6586/entropy-21-00581-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/e9bfe19a22dd/entropy-21-00581-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/29f3872db6af/entropy-21-00581-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/59367091df6b/entropy-21-00581-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/db89c856cdb2/entropy-21-00581-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/baed8c4ecf6c/entropy-21-00581-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/cfd4906146cf/entropy-21-00581-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/5b598659de88/entropy-21-00581-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d416/7515070/70833f19aaab/entropy-21-00581-g010.jpg

相似文献

1
Multifractal Spectrum Curvature of RR Tachograms of Healthy People and Patients with Congestive Heart Failure, a New Tool to Assess Health Conditions.健康人和充血性心力衰竭患者RR心动图的多重分形谱曲率:一种评估健康状况的新工具
Entropy (Basel). 2019 Jun 11;21(6):581. doi: 10.3390/e21060581.
2
Multifractal Properties of Time Series of Synthetic Earthquakes Obtained from a Spring-Block Model.从弹簧-滑块模型获得的合成地震时间序列的多重分形特性。
Entropy (Basel). 2023 May 9;25(5):773. doi: 10.3390/e25050773.
3
Mortality Prediction in Severe Congestive Heart Failure Patients with Multifractal Point-Process Modeling of Heartbeat Dynamics.基于心跳动力学多重分形点过程模型预测严重充血性心力衰竭患者的死亡率。
IEEE Trans Biomed Eng. 2018 Oct;65(10):2345-2354. doi: 10.1109/TBME.2018.2797158. Epub 2018 Jan 23.
4
Further study of the asymmetry for multifractal spectra of heartbeat time series.心跳时间序列多重分形谱不对称性的进一步研究。
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1450-3. doi: 10.1109/IEMBS.2006.260166.
5
Changes in multifractality with aging and heart failure in heartbeat interval time series.心跳间隔时间序列中多重分形随衰老和心力衰竭的变化。
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:6981-4. doi: 10.1109/IEMBS.2005.1616112.
6
Analysis of correlations in heart dynamics in wake and sleep phases.
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:1992-5. doi: 10.1109/IEMBS.2007.4352709.
7
Multifractal Analysis Reveals Decreased Non-linearity and Stronger Anticorrelations in Heart Period Fluctuations of Fibromyalgia Patients.多重分形分析揭示纤维肌痛患者心率变异性波动的非线性降低及更强的反相关性
Front Physiol. 2018 Aug 17;9:1118. doi: 10.3389/fphys.2018.01118. eCollection 2018.
8
Wavelet p-Leader Non Gaussian Multiscale Expansions for Heart Rate Variability Analysis in Congestive Heart Failure Patients.小波 p-Leader 非高斯多尺度扩展在充血性心力衰竭患者心率变异性分析中的应用。
IEEE Trans Biomed Eng. 2019 Jan;66(1):80-88. doi: 10.1109/TBME.2018.2825500. Epub 2018 Apr 12.
9
Entropy-Based Multifractal Testing of Heart Rate Variability during Cognitive-Autonomic Interplay.认知-自主神经相互作用期间心率变异性的基于熵的多重分形测试
Entropy (Basel). 2023 Sep 21;25(9):1364. doi: 10.3390/e25091364.
10
Carvedilol can restore the multifractal properties of heart beat dynamics in patients with advanced congestive heart failure.卡维地洛可恢复晚期充血性心力衰竭患者心跳动力学的多重分形特性。
Auton Neurosci. 2007 Mar 30;132(1-2):76-80. doi: 10.1016/j.autneu.2006.10.008. Epub 2006 Dec 8.

引用本文的文献

1
Utility of nonlinear analysis of heart rate variability in early detection of metabolic syndrome.心率变异性非线性分析在代谢综合征早期检测中的应用
Front Physiol. 2025 Jun 24;16:1597314. doi: 10.3389/fphys.2025.1597314. eCollection 2025.
2
Entropy-Based Multifractal Testing of Heart Rate Variability during Cognitive-Autonomic Interplay.认知-自主神经相互作用期间心率变异性的基于熵的多重分形测试
Entropy (Basel). 2023 Sep 21;25(9):1364. doi: 10.3390/e25091364.
3
Multifractal Properties of Time Series of Synthetic Earthquakes Obtained from a Spring-Block Model.

本文引用的文献

1
The critical Barkhausen avalanches in thin random-field ferromagnets with an open boundary.具有开放边界的薄随机场铁磁体中的临界巴克豪森雪崩。
Sci Rep. 2019 Apr 19;9(1):6340. doi: 10.1038/s41598-019-42802-w.
2
Mechanisms of self-organized criticality in social processes of knowledge creation.社会知识创造过程中自组织临界性的机制。
Phys Rev E. 2017 Sep;96(3-1):032307. doi: 10.1103/PhysRevE.96.032307. Epub 2017 Sep 5.
3
Detecting abnormality in heart dynamics from multifractal analysis of ECG signals.从 ECG 信号的多重分形分析中检测心脏动力学异常。
从弹簧-滑块模型获得的合成地震时间序列的多重分形特性。
Entropy (Basel). 2023 May 9;25(5):773. doi: 10.3390/e25050773.
4
Visibility Graph Analysis of Heartbeat Time Series: Comparison of Young vs. Old, Healthy vs. Diseased, Rest vs. Exercise, and Sedentary vs. Active.心跳时间序列的可见性图分析:年轻人与老年人、健康与患病、静息与运动、久坐与活跃状态的比较
Entropy (Basel). 2023 Apr 18;25(4):677. doi: 10.3390/e25040677.
5
Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal Wavelet Leaders.基于多重分形小波首曲线的正常和病态婴儿哭声信号在倒谱域的非线性统计分析
Entropy (Basel). 2022 Aug 22;24(8):1166. doi: 10.3390/e24081166.
6
Entropy Analysis of RR-Time Series From Stress Tests.压力测试中RR时间序列的熵分析
Front Physiol. 2020 Aug 12;11:981. doi: 10.3389/fphys.2020.00981. eCollection 2020.
Sci Rep. 2017 Nov 9;7(1):15127. doi: 10.1038/s41598-017-15498-z.
4
Multifractal to monofractal evolution of the London street network.伦敦街道网络的多重分形到单分形演化
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Dec;92(6):062130. doi: 10.1103/PhysRevE.92.062130. Epub 2015 Dec 17.
5
Aging in autonomic control by multifractal studies of cardiac interbeat intervals in the VLF band.自主控制中的衰老:通过 VLF 带中心搏间期的多重分形研究。
Physiol Meas. 2011 Oct;32(10):1681-99. doi: 10.1088/0967-3334/32/10/014. Epub 2011 Sep 19.
6
Sleep in congestive heart failure.充血性心力衰竭患者的睡眠问题。
Med Clin North Am. 2010 May;94(3):447-64. doi: 10.1016/j.mcna.2010.02.009.
7
Fractal and multifractal analysis: a review.分形与多重分形分析:综述
Med Image Anal. 2009 Aug;13(4):634-49. doi: 10.1016/j.media.2009.05.003. Epub 2009 May 27.
8
Levels of complexity in scale-invariant neural signals.尺度不变神经信号中的复杂程度
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Apr;79(4 Pt 1):041920. doi: 10.1103/PhysRevE.79.041920. Epub 2009 Apr 21.
9
Methods derived from nonlinear dynamics for analysing heart rate variability.源自非线性动力学的用于分析心率变异性的方法。
Philos Trans A Math Phys Eng Sci. 2009 Jan 28;367(1887):277-96. doi: 10.1098/rsta.2008.0232.
10
Scale-invariant aspects of cardiac dynamics. Observing sleep stages and circadian phases.心脏动力学的尺度不变特征。观察睡眠阶段和昼夜节律阶段。
IEEE Eng Med Biol Mag. 2007 Nov-Dec;26(6):33-7. doi: 10.1109/emb.2007.907093.