基于第四统计的房颤与正常窦性心律区分方法研究
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上海理工大学医疗器械与食品学院,上海,200093

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Method for Distinguishing Atrial Fibrillation From Normal Sinus Rhythm Based on the Fourth Statistics Theory
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School of Medical Instrument & Food Engineering,University of Shanghai for Science and Technology,Shanghai,200093,China

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    摘要:

    房颤(Atrial fibrillation,AF)的患病率会随年龄的增加而增加,复发率也极高,因此提出一种快速准确检测AF的算法十分必要。本文基于第四统计力学原理,结合心脏系统的混沌性质与阴阳特性,提出区分AF和正常窦性心律(Normal sinus rhythm,NSR)的量化方法。首先以R-R间期数据构建嵌入维度为6、延时从1至30的相空间,依次得到对应的概率密度函数(Probability density function,PDF)图;然后以PDF图的横轴作为强度ξ,纵轴概率的累加和作为分布函数x,利用ξ-x的对应关系拟合出第四统计力学参数k值;最后将得到的k值做微分累加得到Ksd值,发现Ksd=0.3可作为区分AF和NSR的重要参数。本研究不仅能以阴阳特性描述的方式区分出AF和NSR,也为第四统计力学的探索打开了新途径,并且对未来准确快速检测AF提供重要依据,对AF早期干预与改善患者预后至关重要。

    Abstract:

    The prevalence of atrial fibrillation (AF) increases with the age,and the recurrence rate is very high.It is necessary to propose an accurate and fast algorithm to distinguish AF.Based on the fourth statistical theory,a quantitative method for distinguishing AF from normal sinus rhythm (NSR) is proposed in this paper combining the chaos character and Yin Yang nature of heart system.Firstly,the phase space with embedding dimension of 6 and delay time from 1 to 30 is constructed by using R-R interval data.The probability density function (PDF) graph is obtained in turn.Then the horizontal axis of PDF graph is taken as strength ξ,the cumulative sum of longitudinal axis is taken as distribution function x,and the fourth statistical theory parameter k value is fitted by the corresponding relation of ξ-x.Finally,differential summation with k and the result is defined as Ksd. From the experiment, Ksd=0.3 can be an important parameter to distinguish AF from NSR.This study can not only distinguish AF and NSR by describing Yin and Yang,but also open a new path for exploration of the fourth statistical theory and provide an important evidence for the accurate and rapid detection of AF in the future.

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王星月,陈兆学.基于第四统计的房颤与正常窦性心律区分方法研究[J].数据采集与处理,2020,35(4):693-701

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  • 收稿日期:2019-10-16
  • 最后修改日期:2020-03-15
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  • 在线发布日期: 2020-08-07