In this paper, a LabView-based virtual instrument for quantitative estimation of heart rate entropy is proposed. Quantitative estimation is obtained from spectral entropy of ordered time range intervals between RR-intervals. Spectral entropy is defined as a modified Shannon information entropy with power spectral density as a probability density function. The choice of power spectral density allows to overcome the task of interval width selection for probability density. We demonstrate block diagrams of the virtual instrument for estimation of spectral entropy of intervalograms and clinical trial results. Experiments proved that patients with normal sinus rhythm have spectral entropy Н_ср = 2.8 while patients with supraventricular arrhythmia have spectral entropy Н_ср = 3.1. Statistical significance of spectral entropy differences is obtained in accordance with t-Student criteria. Correlation analysis of ellipse area of scattergrams and spectral entropy of RR-intervalograms demonstrates that spectral entropy is not related to traditionally used ellipse area of scattergrams and, thus, can be utilized as an independent parameter in a heart rate evaluation process.