US EPA

3249648 

Journal Article 

Role of editing of R-R intervals in the analysis of heart rate variability 

Peltola, MA 

2012 

Yes 

Frontiers in Physiology
ISSN: 1664-042X 

3 

10.3389/fphys.2012.00148 

WOS:000209173000145 

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. 

heart rate variability; artifact; editing; R-R intervals