Open Source Software Tools for Sequential Analysis and Comparison of Heart Rate Variability in Large Cohort Studies

Abstract

Heart rate variability (HRV) is commonly used to assess the function of the autonomic nervous system, which is linked to diseases such as cardiovascular disease, diabetes, hypertension, respiratory diseases, and stress. Many studies of the relationship between these diseases and HRV indices have been reported. Generally, the computation of HRV indices is relatively complicated. Moreover, recent researches regarding HRV have employed increasing numbers of electrocardiogram records. Thus, the computation and data processing required are even more complex. Therefore, we propose computer programs for visualizing and analyzing HRV. The proposed programs are developed under MATLAB GUIDE and are available as open source software tools for researchers to develop or modify. We evaluate the programs with MIT-BIH database. The results show that the proposed software tools facilitates the computation of HRV in batch processing mode and the visualization of all of the details, as well as the properties and trends, of HRV indices over long successive epochs. Especially, the software allows us to divide signals into groups for comparing HRV indices. Therefore, the tools are useful for researchers who deal with large cohort ECG signals. HIGHLIGHTS The authors introduce open source software tools for analyzing heart rate variability The software tools are intended for analyzing large cohorts of ECG data Many records' trend and detail of raw ECG, HRV time series, and RR interval time series can be viewed at the same time