矢量心电信号的建模与统计处理方法

Q3 Computer Science

Open Bioinformatics Journal Pub Date : 2021-11-19 DOI:10.2174/1875036202114010073

I. Lytvynenko, S. Lupenko, Petro Onyskiv, A. Zozulia

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引用次数: 2

摘要

我们开发了一种研究人类心率的新方法，该方法基于矢量韵律信号的使用，该信号包括心电图中心动周期持续时间序列形式的经典韵律信号作为其组成部分。大多数现代自动心率分析系统都是基于心律图的统计分析，心律图是记录心电图中R-R间期持续时间的有序集合。然而，这种方法的信息量不是很大，因为R-R间期只反映心动周期持续时间随时间的变化，而不是反映所有相位的心电信号单相值之间的整个时间间隔。本文的目的是以韵律心信号的平稳和永久连接随机序列的向量的形式提出一个数学模型，以提高其处理问题的分辨率。它展示了矢量韵律信号是如何在诊断系统中形成和处理的。记录该模型的概率特征结构，用于现代心脏诊断系统中心率的统计分析。基于一个新的矢量韵律信号数学模型，该模型以平稳和永久连接的随机序列的矢量形式存在，开发了一种新的方法来统计估计心率的频谱相关性特征，并提高了分辨率。在现代心脏诊断系统中进行心律分析时，矢量心律信号分量的频谱功率密度被证明是新的诊断特征，补充了已知信号，并增加了现代心脏诊断体系中心率分析的信息价值。研究了所提出的用于现代心脏诊断系统中心率分析的数学模型的概率特征结构。展示了矢量韵律信号是如何形成的，并在所提出的数学模型和所开发的方法的基础上对其进行了统计处理。

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Modeling and Methods of Statistical Processing of a Vector Rhytmocardiosignal

We have developed a new approach to the study of human heart rate, which is based on the use of a vector rhythmocardiosignal, which includes as its component the classical rhythmocardiosignal in the form of a sequence of heart cycle durations in an electrocardiogram. Most modern automated heart rate analysis systems are based on a statistical analysis of the rhythmocardiogram, which is an ordered set of R-R interval durations in a recorded electrocardiogram. However, this approach is not very informative, since R-R intervals reflect only the change in the duration of cardiac cycles over time and not the entire set of time intervals between single-phase values of the electrocardiosignal for all its phases. The aim of this paper is to present a mathematical model in the form of a vector of stationary and permanently connected random sequences of a rhythmocardiosignal with an increased resolution for its processing problems. It shows how the vector rhythmocardiosignal is formed and processed in diagnostic systems. The structure of probabilistic characteristics of this model is recorded for statistical analysis of heart rate in modern cardiodiagnostics systems. Based on a new mathematical model of a vector rhythmocardiosignal in the form of a vector of stationary and permanently connected random sequences, new methods for statistical estimation of spectral-correlation characteristics of heart rate with increased resolution have been developed. The spectral power densities of the components of the vector rhythmocardiosignal are justified as new diagnostic features when performing rhythm analysis in modern cardiodiagnostics systems, complementing the known signs and increasing the informative value of heart rate analysis in modern cardiodiagnostics systems. The structure of probabilistic characteristics of the proposed mathematical model for heart rate analysis in modern cardiodiagnostics systems is studied. It is shown how the vector rhythmocardiosignal is formed, and its statistical processing is carried out on the basis of the proposed mathematical model and developed methods.

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来源期刊

Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)

CiteScore

2.40

自引率

0.00%

发文量

期刊介绍： The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.