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一种新的心率变异性度量方法
Alternative TitleA novel method of heart rate variability measurement
邵士亮1,2,3; 王挺2,3; 宋纯贺2,3; 崔婀娜1; 赵海1; 姚辰2,3
Department机器人学研究室
Source Publication物理学报
ISSN1000-3290
2019
Volume68Issue:17Pages:1-13
Indexed BySCI ; EI ; CSCD
EI Accession number20194607682401
WOS IDWOS:000484835600034
CSCD IDCSCD:6586638
Contribution Rank1
Funding Organization重大科技创新项目(批准号: N161608001)
Keyword心率变异性 改进的自适应噪声完备集合经验模态分解(ICEEMDAN) bubble熵 复杂网络
Abstract

心率变异性的复杂波动反映了心脏的自主调节功能.本文提出了一种新的心率变异性度量方法—ICBN方法,该方法通过改进的自适应噪声完备集合经验模态分解方法对心率变异性信号进行分解,得到多个模态分量,计算每个模态分量的bubble熵得到熵值向量,把该向量映射成复杂网络,通过计算网络的特征参数,对心率变异性在不同时频尺度状态下的非线性特征之间的耦合关系进行度量.首先,采用时域、频域和ICBN分析方法对29名充血性心力衰竭病人和29名正常窦性心律对象的心率变异性进行分析,结果表明:时域指标三角指数HRVTi,频域指标LF/HF,网络层级加权值WB,平均点权值PW,特征路径长度CL具有统计学差异;基于网络层级加权值WB,特征路径长度CL,频域指标LF/HF和Fisher判别方法的识别模型对充血性心力衰竭病人的识别正确率达到89.66%.然后,又对43名房颤心律失常患者和43名正常窦性心律对象的心率变异性进行分析,结果表明:时域指标SDNN, pNN50, RMSSD,频域指标LF/HF,网络层级加权值WB,平均点权值PW具有统计学差异;时域指标pNN50, RMSSD,频域指标LF/HF和网络层级加权值WB,平均点权值PW作为特征向量, Fisher判别方法作为分类器,对房颤心律失常患者的识别正确率达到91.86%.综合以上实验结果可知,本文为心率变异性的度量研究提供了一种新的思路.

Other Abstract

The complex fluctuation of heart rate variability reflects the autonomous regulation function of the heart. In this paper, a novel method of measuring the heart rate variability is proposed. Firstly, the heart rate variability signal is decomposed by the improved complete ensemble empirical mode decomposition with adaptive noise method, and the multiple intrinsic mode functions are obtained, and the bubble entropy of each intrinsic mode function is calculated to obtain an entropy value vector. Then, the vector is mapped to a network based on a limited penetrable horizontal visibility graph method. By calculating various characteristic parameters of the network, the coupling relationship between the nonlinear features of heart rate variability in different time-frequency scale states are studied. The characteristic parameters include mean value of aggregation coefficient (MC), the characteristic path length (CL), the topological entropy of network (TE), the network level weighted bubble value(WB), and the pseudo mean value of node weight(PW). Firstly, the heart rate variabilities of 29 patients with congestive heart failure and 29 normal sinus heart rhythm subjects are analyzed by time domain, frequency domain and ICBN analysis method, the T test is used for statistical analysis, and Fisher discriminant method is used for classification. The results show that the time domain triangular index HRVTI, frequency domain index LF/HF, WB, PW and CL in ICBN have statistical differences. The accuracy rate of recognition model based on WB, CL, frequency domain index LF/HF and Fisher discriminant method is 89.66%. Secondly, the heart rate variabilities of 43 patients with atrial fibrillation arrhythmia and another 43 normal sinus heart rhythm subjects are analyzed by the same methods, including the time domain analyzed method, frequency domain analyzed method, and ICBN analyzed method. Then, the T test is also used for statistical analysis, and Fisher discriminant method is used for classification. The results show that using the time domain index pNN5 and RMSSD, frequency index LF/HF, ICBN index WB and PW as the feature vectors, and the Fisher discriminant mode as the classifier, the accuracy rate of recognition for atrial fibrillation arrhythmia is 91.86%. From these results it is concluded that the ICBN method provides a new idea for the heart rate variability measurement.

Language中文
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/25479
Collection机器人学研究室
Corresponding Author邵士亮
Affiliation1.东北大学计算机科学与工程学院
2.中国科学院沈阳自动化研究所机器人学国家重点实验室
3.中国科学院机器人与智能制造创新研究院
Recommended Citation
GB/T 7714
邵士亮,王挺,宋纯贺,等. 一种新的心率变异性度量方法[J]. 物理学报,2019,68(17):1-13.
APA 邵士亮,王挺,宋纯贺,崔婀娜,赵海,&姚辰.(2019).一种新的心率变异性度量方法.物理学报,68(17),1-13.
MLA 邵士亮,et al."一种新的心率变异性度量方法".物理学报 68.17(2019):1-13.
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