Benchmarking heart rate variability toolboxes

Adriana N Vest; Qiao Li; Chengyu Liu; Shamim Nemati; Amit Shah; Gari D Clifford

doi:10.1016/j.jelectrocard.2017.08.006

Benchmarking heart rate variability toolboxes

J Electrocardiol. 2017 Nov-Dec;50(6):744-747. doi: 10.1016/j.jelectrocard.2017.08.006. Epub 2017 Aug 8.

Authors

Adriana N Vest¹, Qiao Li², Chengyu Liu³, Shamim Nemati⁴, Amit Shah⁵, Gari D Clifford⁶

Affiliations

¹ Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Bldg, Suite 4100, 101 Woodruff Circle, Atlanta, GA, United States; Department of Epidemiology, Rollins School of Public Health at Emory University, 1518 Clifton Road NE, Room 3053, Atlanta, GA, United States. Electronic address: adriana.vest@emory.edu.
² Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Bldg, Suite 4100, 101 Woodruff Circle, Atlanta, GA, United States. Electronic address: qiao.li@emory.edu.
³ Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Bldg, Suite 4100, 101 Woodruff Circle, Atlanta, GA, United States. Electronic address: chengyu.liu@emory.edu.
⁴ Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Bldg, Suite 4100, 101 Woodruff Circle, Atlanta, GA, United States. Electronic address: shamim.nemati@emory.edu.
⁵ Department of Epidemiology, Rollins School of Public Health at Emory University, 1518 Clifton Road NE, Room 3053, Atlanta, GA, United States; Division of Cardiology, Department of Medicine, Emory University School of Medicine, 101 Woodruff Circle Suite, 319 Woodruff Memorial Research Building, Atlanta, GA, United States. Electronic address: ajshah3@emory.edu.
⁶ Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Bldg, Suite 4100, 101 Woodruff Circle, Atlanta, GA, United States; Department of Biomedical Engineering, Georgia Institute of Technology, 1760 Haygood Drive, HSRB Suite W200, Atlanta, GA, United States. Electronic address: gari@gatech.edu.

Abstract

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.

Keywords: Heart rate variability; Peak detection; Physiological signal processing; Toolbox benchmarking.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural

MeSH terms

Algorithms
Arrhythmias, Cardiac / physiopathology*
Benchmarking*
Electrocardiography / methods*
Heart Rate / physiology*
Humans
Signal Processing, Computer-Assisted
Software*

Abstract

Publication types

MeSH terms

Grants and funding