Filter properties of root mean square successive difference (RMSSD) for heart rate

• Published in: Psychophysiology Vol. 42; no. 2; pp. 246 - 252
• Main Authors: Berntson, Gary G., Lozano, David L., Chen, Yun-Ju
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing 01.03.2005; Blackwell
• Subjects: Adult; Algorithms; Behavioral psychophysiology; Biological and medical sciences; Data Interpretation, Statistical; Electrocardiogram; Female; Fundamental and applied biological sciences. Psychology; Heart Rate - physiology; Heart rate variability; Humans; Male; Methods; Models, Statistical; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Respiratory sinus arrhythmia; Root mean square successive differences; Successive difference; Vagus Nerve - physiology; Human; Methodology; Root mean square successive differences; Variability; Cardiovascular disease; Successive difference; Cardiorespiratory control; Heart rate; Heart disease; Electrocardiogram; Electrocardiography; Measurement method; Respiration; Heart rate variability; Respiratory sinus arrhythmia
• ISSN: 0048-5772; 1469-8986; 1540-5958
• DOI: 10.1111/j.1469-8986.2005.00277.x

The root mean square successive difference (RMSSD) in heart period series is a time domain measure of heart period variability. The RMSSD is sensitive to high‐frequency heart period fluctuations in the respiratory frequency range and has been used as an index of vagal cardiac control. By transfer function simulations, the RMSSD statistic is shown to represent a high‐pass filter that effectively captures respiratory sinus arrhythmia but also passes lower frequency fluctuations that can include sympathetic influences. These simulations, together with analysis of actual heart period series, reveal that the RMSSD is biased by basal heart period. Although between‐subjects levels of RMSSD covary highly with spectral estimates of high‐frequency variability, within‐subject RMSSD change scores account for only 50–60% of the variance in spectral estimates. The present findings raise caveats in the applications and interpretation of the RMSSD statistic.