Benchmarking heart rate variability toolboxes.

Background: Heart rate variability (HRV) metrics hold promise as potential indicators for autonomic function, prediction of adverse cardiovascular outcomes, psychophysiological status, and general wellness. Although the investigation of HRV has been prevalent for several decades, the methods used for preprocessing, windowing, and choosing appropriate parameters lack consensus among academic and clinical investigators.

Methods: A comprehensive and open-source modular program is presented for calculating HRV implemented in Matlab with evidence-based algorithms and output formats. We compare our software with another widely used HRV toolbox written in C and available through PhysioNet.org.

Results: Our findings show substantially similar results when using high quality electrocardiograms (ECG) free from arrhythmias.

Conclusions: Our software shows equivalent performance alongside an established predecessor and includes validated tools for performing preprocessing, signal quality, and arrhythmia detection to help provide standardization and repeatability in the field, leading to fewer errors in the presence of noise or arrhythmias.