HRVTool – an Open-Source Matlab Toolbox for Analyzing Heart Rate Variability

Motivation: Many software tools for ECG processing are commercial. New innovative and alternative features for heart rate variability analysis (HRV) and improved methods in ECG preprocessing cannot be incorporated. Moreover, software manuals are lacking of clarity and often conceal the exact calculation methods that makes clinical interpretation difficult, and reproducibility is reduced.Software description: HRVTool provides an open-source and intuitive user-friendly environment for the HRV analysis in Matlab. The software is available at http://marcusvollmer.github.io/HRV and supports the processing of ECG, pulsatile waveforms and RR intervals from various sources (mat and text files containing raw data, Polar, PhysioNet, Hexoskin, BIOPAC, European Data Format, ISHNE Holter Standard Format, and Machine-Independent Beat files). An integrated heart beat detector locates R peaks or pulse waves. Visual inspection, and manual adjustments of beat locations are possible and the corresponding annotation file can be saved in a standard Matlab format or as a delimited text file. HRV statistics are computed in a sliding window to evaluate the alteration over time. HRV metrics can be exported. An animation of intervals supports pattern identification. Moreover the Matlab class (HRV.m) includes functions for windowed HRV computation that can be used for batch processing.

1. Introduction

Heart Rate Variability (HRV) analyzes the physiological phenomenon of heart beat variation over time and is used to determine autonomic activity of the heart [1]. Disorders in the regular heart rate as a result of disturbances in the electrical system of the heart are called arrhythmia. Expert cardiologists can identify such a physiological variation of the heart rate by analyzing the ECG leads (electrocardiogram) and thereby diagnose different cardiac disorders. In contrast to arrhythmia screening, HRV as a measure of neurovegetative activity is used in remedial medicine for prognostic purposes, performance objectification and risk stratification for cardiovascular events. HRV biofeedback methods are established and heart rate analysis and continuous assessment of HRV as objective features are widely used beyond the medical environment, e.g. for assessing the fitness status, physical and mental stress level.