Adriana N Vest1, Qiao Li2, Chengyu Liu3, Shamim Nemati4, Amit Shah5, Gari D Clifford6. 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.
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.
Authors: Alistair E W Johnson; Joachim Behar; Fernando Andreotti; Gari D Clifford; Julien Oster Journal: Physiol Meas Date: 2015-07-28 Impact factor: 2.833
Authors: Jeremy Levy; Daniel Álvarez; Aviv A Rosenberg; Alexandra Alexandrovich; Félix Del Campo; Joachim A Behar Journal: NPJ Digit Med Date: 2021-01-04