Role of editing of R-R intervals in the analysis of heart rate variability.
Role of editing of R-R intervals in the analysis of heart rate variability.
复制标题
DOI：
10.3389/fphys.2012.00148
复制
发表时间：
2012
影响因子：
4
通讯作者：
Peltola MA
中科院分区：
文献类型：
--
作者：
Peltola MA
本文综述了用于编辑R-R间期时间序列的方法以及这种编辑如何影响心率（HR）变异性分析的结果。从短期和长期心电图（ECG）记录中测量HR变异性是一种评价心脏自主调节的无创方法。HR变异性提供了关于交感神经-副交感神经自主神经平衡的信息。一个重要的临床应用是测量急性心肌梗死患者的HR变异性。然而，从动态ECG记录的R-R间期时间序列中提取的HR变异性信号通常包含不同量的伪影。这些假搏动可以是生理性的，也可以是技术性的。例如，技术伪影可能是由于电极紧固不良或由于受试者的运动造成的。异位搏动和心房颤动是生理伪影的示例。由于异位搏动和其他假搏动在R-R间期时间序列中很常见，它们使HR变异性的可靠分析复杂化，有时使其不可能。结合HR变异性分析的使用增加，几项研究已经证实需要不同的方法来处理R-R间期时间序列中存在的假搏动。R-R间期时间序列的编辑过程已成为这些分析的一个组成部分。然而，已发表的文献不包含编辑方法及其对HR变异性分析的影响的详细综述。已经引入了几种不同的编辑和HR变异性信号预处理方法，并对伪影校正进行了测试。有几种可用的方法，即，使用涉及删除、插值或过滤系统的方法。然而，这些编辑方法可能对HR变异性测量产生不同的影响。编辑的影响取决于研究设置、编辑方法、用于评估HR变异性的参数、研究人群类型和R-R间期时间序列的长度。本文的目的是总结这些预处理方法的心率变异性信号，特别是对编辑的R-R间期时间序列。
This paper reviews the methods used for editing of the R–R interval time series and how this editing can influence the results of heart rate (HR) variability analyses. Measurement of HR variability from short and long-term electrocardiographic (ECG) recordings is a non-invasive method for evaluating cardiac autonomic regulation. HR variability provides information about the sympathetic-parasympathetic autonomic balance. One important clinical application is the measurement of HR variability in patients suffering from acute myocardial infarction. However, HR variability signals extracted from R–R interval time series from ambulatory ECG recordings often contain different amounts of artifact. These false beats can be either of physiological or technical origin. For instance, technical artifact may result from poorly fastened electrodes or be due to motion of the subject. Ectopic beats and atrial fibrillation are examples of physiological artifact. Since ectopic and other false beats are common in the R–R interval time series, they complicate the reliable analysis of HR variability sometimes making it impossible. In conjunction with the increased usage of HR variability analyses, several studies have confirmed the need for different approaches for handling false beats present in the R–R interval time series. The editing process for the R–R interval time series has become an integral part of these analyses. However, the published literature does not contain detailed reviews of editing methods and their impact on HR variability analyses. Several different editing and HR variability signal pre-processing methods have been introduced and tested for the artifact correction. There are several approaches available, i.e., use of methods involving deletion, interpolation or filtering systems. However, these editing methods can have different effects on HR variability measures. The effects of editing are dependent on the study setting, editing method, parameters used to assess HR variability, type of study population, and the length of R–R interval time series. The purpose of this paper is to summarize these pre-processing methods for HR variability signal, focusing especially on the editing of the R–R interval time series.
登录
查看更多内容
影响因子：
--
作者：
CHESS, GF;TAM, RMK;CALARESU, FR
通讯作者：
CALARESU, FR
影响因子：
39.2
作者：
BIKKINA, M;LARSON, MG;LEVY, D
通讯作者：
LEVY, D
影响因子：
168.9
作者：
Bauer, Axel;Kantelhardt, Jan W.;Schmidt, Georg
通讯作者：
Schmidt, Georg
影响因子：
3.7
作者：
BERNTSON, GG;QUIGLEY, KS;BOYSEN, ST
通讯作者：
BOYSEN, ST
影响因子：
37.8
作者：
Bigger, JT;Steinman, RC;Cohen, RJ
通讯作者：
Cohen, RJ