Peltola Mirja A
Department of Internal Medicine, Institute of Clinical Medicine, University of Oulu Oulu, Finland.
Front Physiol. 2012 May 23;3:148. doi: 10.3389/fphys.2012.00148. eCollection 2012.
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.
本文回顾了用于编辑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变异性是评估心脏自主神经调节的一种非侵入性方法。HR变异性提供了有关交感-副交感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，从动态心电图记录的R-R间期时间序列中提取的HR变异性信号通常包含不同数量的伪差。这些早搏可能源于生理或技术原因。例如，技术伪差可能是由于电极固定不牢或受试者的运动所致。异位搏动和心房颤动是生理伪差的例子。由于异位搏动和其他伪差在R-R间期时间序列中很常见，它们使HR变异性的可靠分析变得复杂，有时甚至无法进行。随着HR变异性分析应用的增加，几项研究证实需要采用不同的方法来处理R-R间期时间序列中存在的伪差。R-R间期时间序列的编辑过程已成为这些分析中不可或缺的一部分。然而，已发表的文献中没有关于编辑方法及其对HR变异性分析影响的详细综述。已经引入并测试了几种不同的编辑和HR变异性信号预处理方法来进行伪差校正。有几种可用的方法，即使用涉及删除、插值或滤波系统的方法。然而，这些编辑方法对HR变异性测量可能有不同的影响。编辑的效果取决于研究设置、编辑方法、用于评估HR变异性的参数、研究人群的类型以及R-R间期时间序列的长度。本文的目的是总结这些HR变异性信号的预处理方法，尤其侧重于R-R间期时间序列的编辑。
