Reminder: RMSSD and SD1 are identical heart rate variability metrics

Abstract

Assessment of heart rate variability (HRV) is a common approach to examine cardiac autonomic nervous system modulation that has been employed in a variety of settings. Frequently, both the root mean square of successive differences (RMSSD) and SD1, which is a Poincaré plot component, have been used to quantify short-term heart rate variability. It is not typically appreciated, however, that RMSSD and SD1 are identical metrics of HRV. As a reminder to clinicians and researchers who use and study HRV, we show both empirically and mathematically that RMSSD and SD1 are identical metrics. Because the homology between RMSSD and SD1 is not commonly known, the inclusion of both measures has been reported in many recent publications. The inappropriate use of such redundant data may affect the interpretation of HRV studies. Muscle Nerve 56: 674-678, 2017.

Ultra‐short heart rate variability recording reliability: The effect of controlled paced breathing

“…the rMSSD values are poorly influenced by fluctuations in heart rate values, making the measurement more stable even in periods with different heart oscillations (Saboul, Pialoux, & Hautier, 2013). The identical mathematical metrics between rMSSD and SD1 explains the similar reliability of these indices (Ciccone et al, 2017). Furthermore, indices such as SDNN or those of the frequency domain that are not derived from the difference between RR intervals, have a direct influence on fluctuations of heart rate values, so that small changes in one specific period of the record are not replicable in the others (Nussinovitchet al, 2011).…”

The use of heart rate variability analysis to detect arrhythmias in horses undergoing a standard treadmill exercise test

“…The SDRR, TI, and TIRR are considered parameters of overall HRV. The parameters RMSSD and SD1 are considered markers of short‐term HRV (ie, variability in instantaneous HR) and are mathematically identical; therefore, only RMSSD is reported in the manuscript. The parameter SD2 is considered an indicator of long‐term HRV.…”

Impact of functional training on geometric indices and fractal correlation property of heart rate variability in postmenopausal women

“…In this study, we chose to perform the analyzes using nonlinear methods, which allow a broader understanding of the physiological impact on autonomic modulation, since there is evidence that the mechanisms involved in cardiovascular regulation probably interact in a nonlinear manner (De Rezende Barbosa et al., 2016a,b). Besides that, a recent study by Ciccone et al., presented that RMSSD and SD1 are identical metrics of HRV and because the homology between them is not commonly known, the inclusion of both measures has been reported in many recent publications and the redundant data may affect the interpretation of HRV studies (Ciccone et al., ).…”