基于Poincaré差值散点图的心率变异性分析方法研究

霍铖宇; 庄建军; 黄晓林; 侯凤贞; 宁新宝

doi:10.7498/aps.61.190506

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摘要

在心率变异性的非线性分析中, Poincaré散点图分析是一种重要手段.本文基于Poincaré差值散点图(modified Poincaré plot)提出了两个参数——区域分布熵和区域分布系数, 用于定量描述所考察区域内散点的分布趋势, 并提出对散点在4个象限中的分布进行分别计算.通过对MIT-BIH数据库中健康年轻人、健康老年人和充血性心力衰竭患者样本数据的分析, 发现两参数值均呈现显著的组间差异;同时, 不同象限的分析结果显示了四个象限具有不同的区分敏感性, 而其中尤以第一象限的区分度为最高, 反映出充血性心力衰竭患者相对健康人迷走神经调控功能的改变最为显著, 与以往的生理学研究结论相符.经验证, 该方法可用于短时数据, 更易于扩展至临床应用.

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作者及机构信息

1.
南京大学电子科学与工程学院, 生物医学电子工程研究所, 近代声学教育部重点实验室, 南京 210093;

2.
常熟理工学院物理与电子工程学院, 常熟 215500

基金项目: 国家自然科学基金(批准号：60701002)、江苏省自然科学基金 (批准号: BK2011565)和江苏省"六大人才高峰"高层次人才项目(批准号: 2011-DZXX-035)资助的课题．

参考文献

[1]	Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology 1996 Circulation 93 1043
[2]	Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim C, Suri J 2006 Med. Biol. Eng. Comput. 44 1031
[3]	Ning X B, Bian C H, Wang J, Chen Y 2006 Chinese Sci. Bull. 51 385
[4]	Huang X L, Ning X B, Wang X L 2009 Chinese Sci. Bull. 54 3784
[5]	Huang X L, Cui S Z, Ning X B, Bian C H 2009 Acta Phys. Sin. 58 8160 (in Chinese) [黄晓林, 崔胜忠, 卞春华 2009 物理学报 58 8160]
[6]	Ivanov P C, Amaral L A N, Goldberger A L, Havlin S, Rosenblum M G, Struzik Z R, Stanley H E 1999 Nature 399 461
[7]	Bogaert C, Beckers F, Ramaekers D, Aubert A E 2001 Auton. Neurosci. 90 142
[8]	Bian C H, Ning X B 2004 Physica A 337 149
[9]	Song A L, Huang X L, Si J F, Ning X B 2011 Acta Phys. Sin. 60 020509 (in Chinese) [宋爱玲, 黄晓林, 司峻峰, 宁新宝 2011 物理学报 60 020509]
[10]	Claudia L, Oscar I, Héctor P, Marco V J 2003 Clin. Physiol. Funct. I 23 72
[11]	Mourot L, Bouhaddi M, Perrey S, Rouillon J D, Regnard J 2004 Eur. J. Appl. Physiol. 91 79
[12]	Brennan M, Palaniswami M, Kamen P 2001 Ieee T. Bio. Med Eng. 48 1342
[13]	Li F J, Zhang P, Liu Y, Chen Y Q 2004 Journal of Clinical Eletrocardiology 13 58 (in Chinese) [李方洁, 张平, 刘艳, 程英茜 2004 临床心电学杂志 13 58]
[14]	Cohen M E, Hudson D L, Deedwania P C 1996 Ieee Eng. Med. Biol. 15 97
[15]	Liu J S, Bai Y, Li Y C 2004 Chinese Journal of Medical Physics 21 223 (in Chinese) [刘家寿, 白云, 李迎春 2004 中国医学物理学杂志 21 223]
[16]	Costa M, Goldberger A L, Peng C K 2005 Phys. Rev. Lett. 95 198102
[17]	Porta A, Guzzetti S, Montano N, Gnecchi-Ruscone T, Furlan R, Malliani A 2006 Computers in Cardiology 33 77
[18]	Cammarota C, Rogora E 2007 Chaos Soliton. Frac. 32 1649
[19]	Porta A, Casali K R, Casali A G, Gnecchi-Ruscone T, Tobaldini E, Montano N, Lange S, Geue D, Cysarz D, Leeuwen P V 2008 Am. J. Physiol-Reg. I 295 550
[20]	Hou F Z, Ning X B, Zhuang J J, Huang X L, Fu M J, Bian C H 2011 Med. Eng. Phys. 33 633

施引文献

[1]	Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology 1996 Circulation 93 1043
[2]	Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim C, Suri J 2006 Med. Biol. Eng. Comput. 44 1031
[3]	Ning X B, Bian C H, Wang J, Chen Y 2006 Chinese Sci. Bull. 51 385
[4]	Huang X L, Ning X B, Wang X L 2009 Chinese Sci. Bull. 54 3784
[5]	Huang X L, Cui S Z, Ning X B, Bian C H 2009 Acta Phys. Sin. 58 8160 (in Chinese) [黄晓林, 崔胜忠, 卞春华 2009 物理学报 58 8160]
[6]	Ivanov P C, Amaral L A N, Goldberger A L, Havlin S, Rosenblum M G, Struzik Z R, Stanley H E 1999 Nature 399 461
[7]	Bogaert C, Beckers F, Ramaekers D, Aubert A E 2001 Auton. Neurosci. 90 142
[8]	Bian C H, Ning X B 2004 Physica A 337 149
[9]	Song A L, Huang X L, Si J F, Ning X B 2011 Acta Phys. Sin. 60 020509 (in Chinese) [宋爱玲, 黄晓林, 司峻峰, 宁新宝 2011 物理学报 60 020509]
[10]	Claudia L, Oscar I, Héctor P, Marco V J 2003 Clin. Physiol. Funct. I 23 72
[11]	Mourot L, Bouhaddi M, Perrey S, Rouillon J D, Regnard J 2004 Eur. J. Appl. Physiol. 91 79
[12]	Brennan M, Palaniswami M, Kamen P 2001 Ieee T. Bio. Med Eng. 48 1342
[13]	Li F J, Zhang P, Liu Y, Chen Y Q 2004 Journal of Clinical Eletrocardiology 13 58 (in Chinese) [李方洁, 张平, 刘艳, 程英茜 2004 临床心电学杂志 13 58]
[14]	Cohen M E, Hudson D L, Deedwania P C 1996 Ieee Eng. Med. Biol. 15 97
[15]	Liu J S, Bai Y, Li Y C 2004 Chinese Journal of Medical Physics 21 223 (in Chinese) [刘家寿, 白云, 李迎春 2004 中国医学物理学杂志 21 223]
[16]	Costa M, Goldberger A L, Peng C K 2005 Phys. Rev. Lett. 95 198102
[17]	Porta A, Guzzetti S, Montano N, Gnecchi-Ruscone T, Furlan R, Malliani A 2006 Computers in Cardiology 33 77
[18]	Cammarota C, Rogora E 2007 Chaos Soliton. Frac. 32 1649
[19]	Porta A, Casali K R, Casali A G, Gnecchi-Ruscone T, Tobaldini E, Montano N, Lange S, Geue D, Cysarz D, Leeuwen P V 2008 Am. J. Physiol-Reg. I 295 550
[20]	Hou F Z, Ning X B, Zhuang J J, Huang X L, Fu M J, Bian C H 2011 Med. Eng. Phys. 33 633

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基于Poincaré差值散点图的心率变异性分析方法研究

1. 南京大学电子科学与工程学院, 生物医学电子工程研究所, 近代声学教育部重点实验室, 南京 210093;

2. 常熟理工学院物理与电子工程学院, 常熟 215500

基金项目:

国家自然科学基金(批准号：60701002)、江苏省自然科学基金 (批准号: BK2011565)和江苏省"六大人才高峰"高层次人才项目(批准号: 2011-DZXX-035)资助的课题．

收稿日期: 2012-02-16

修回日期: 2012-05-14

摘要: 在心率变异性的非线性分析中, Poincaré散点图分析是一种重要手段.本文基于Poincaré差值散点图(modified Poincaré plot)提出了两个参数——区域分布熵和区域分布系数, 用于定量描述所考察区域内散点的分布趋势, 并提出对散点在4个象限中的分布进行分别计算.通过对MIT-BIH数据库中健康年轻人、健康老年人和充血性心力衰竭患者样本数据的分析, 发现两参数值均呈现显著的组间差异;同时, 不同象限的分析结果显示了四个象限具有不同的区分敏感性, 而其中尤以第一象限的区分度为最高, 反映出充血性心力衰竭患者相对健康人迷走神经调控功能的改变最为显著, 与以往的生理学研究结论相符.经验证, 该方法可用于短时数据, 更易于扩展至临床应用.

关键词:

Heart rate variability analysis based on modified Poincaré plot

1.
Key Laboratory of Modern Acoustics of Ministry of Education, Institute of Biomedical Electronic Engineering, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China;

2.
School of Physics and Electronic Engineering, Changshu Institute of Technology, Changshu 215500, China

Fund Project:

Project supported by the National Natural Science Foundation of China (Grant No. 60701002), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2011565), and the "Six Talents Peak" High-Level Personnel Project of Jiangsu Province (Grant No. 2011-DZXX-035).

Received Date: 16 February 2012

Accepted Date: 14 May 2012

Abstract: Poincaré plot is an important method in nonlinear analysis of heart rate variability(HRV). Based on the modified Poincaré plot, two arguments-the regional distribution entropy and regional distribution coefficient are put forward for the quantitative description of the scatter distribution trends in the studied area. And the distributions of the Poincaré plot in the four quadrants are calculated separately. Through the analysis of the HRV sample data from healthy young people, older people and congestive heart failure(CHF) sufferers in MIT-BIH database, we find that the two parameters show a significant difference between the groups. Meanwhile, the analysis results in different quadrants show that the sensitivities of the four quadrants are different, and especially in the first quadrant, the sensitivity is best. This phenomenon shows that the changes of vagal control function are most significant between healthy people and CHF sufferers, which is consistent with previous physiological research conclusion. Experimental results also show that the method can be used for short-term data, and thus is easier to extend to clinical applications.

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