Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method

PLoS One. 2015 Jul 14;10(7):e0133148. doi: 10.1371/journal.pone.0133148. eCollection 2015.

Abstract

The analysis of heart rate variability (HRV) has been performed on long-term electrocardiography (ECG) recordings (12~24 hours) and short-term recordings (2~5 minutes), which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV). The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping) was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping). The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Dogs
  • Electrocardiography / methods
  • Heart Rate / physiology*
  • Humans
  • Pilot Projects
  • Systems Analysis
  • Time Factors

Grants and funding

This work was partly supported by the National Key Basic Research Program of China (#2013CB329505), the National Natural Science Foundation of China under grants (#61135004), the Shenzhen Governmental Basic Research Grant (#JCYJ20130402113127532), and the Guangdong Innovation Research Team Fund for Low-cost Healthcare Technologies. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.