Signal processing
RMSSD: Vagal Tone Metric from PPG
RMSSD (Root Mean Square of Successive Differences) calculates the square root of the mean squared differences between consecutive interbeat intervals, providing the primary time-domain estimate of parasympathetic (vagal) cardiac modulation. It is the most widely used HRV metric in consumer wearables.
How it works
Schematic summary of this guide. Waveforms are illustrative, not measured data.
RMSSD is computed as
RMSSD is preferred over frequency-domain metrics for short recordings (<5 minutes) because it requires no spectral estimation and is more robust to non-stationarity.
RMSSD is highly individual, so trends against a person's own baseline are more informative than population cut-offs.
In validation studies, Stone et al. (2021, doi:10.3389/fspor.2021.585870) found Oura resting RMSSD within a mean absolute percent error of 6.84% of ECG (CCC 0.91). In Miller et al. (2022, doi:10.3390/s22166317), overnight RMSSD agreement with ECG ranged from ICC 0.63 (Oura Gen 2) and 0.67 (Apple Watch S6) to 0.99 (WHOOP 3.0, raw data supplied by the manufacturer).
Frequently Asked Questions
What is a good RMSSD score?
RMSSD is highly individual. Rather than absolute thresholds, tracking your 7-day moving average trend is more informative. Generally, higher RMSSD indicates better recovery and parasympathetic tone, but values must be interpreted relative to personal baseline and age.
Why do wearables measure RMSSD during sleep?
Sleep provides the most artifact-free recording condition for PPG. Overnight RMSSD captures peak vagal tone during deep sleep without confounding effects of posture changes, stress, caffeine, or physical activity that affect daytime measurements.
Can RMSSD detect overtraining?
Sustained RMSSD suppression below a person's own baseline can accompany incomplete recovery. However, acute post-exercise RMSSD suppression is normal and not indicative of overtraining.