In plain English
A way of calculating HRV from the differences between consecutive heartbeats. It mainly reflects parasympathetic activity and is what WHOOP, Oura and many HRV apps report.
What it is
RMSSD stands for root mean square of successive differences. Take the gap between each pair of neighbouring heartbeats, find how much each gap differs from the next one, square those differences, average them and take the square root. The result is in milliseconds.
Because it looks at beat-to-beat changes, RMSSD mostly picks up fast, breathing-linked swings in heart rate driven by the vagus nerve. That’s why it’s treated as a marker of parasympathetic activity.
Why it matters for training decisions
RMSSD is a practical HRV metric for daily monitoring. It’s widely used in sport because it can be calculated from short recordings. As with any HRV measure, a single morning matters less than your rolling average against your own normal range.
How wearables measure it, and the limits
WHOOP and Oura calculate RMSSD from overnight heartbeats picked up by an optical sensor. Chest straps paired with HRV apps often use a short morning reading instead. Overnight and morning values aren’t interchangeable, and optical sensors can be thrown off by movement or poor contact.
RMSSD is not the same as SDNN, which is what Apple Health stores. If you switch between an Apple Watch and a WHOOP or Oura, expect different numbers for the same night.
How P247 uses it
P247’s iPhone app reads HRV from Apple Health, which records it as SDNN rather than RMSSD. If your WHOOP or Oura writes HRV into Apple Health, P247’s HRV status label keeps values from different sources apart rather than mixing them into one baseline.
Related terms
Read more on the P247 blog
Sources
- Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation, 1996.
- Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Frontiers in Public Health, 2017.
- WHOOP: Heart rate variability: how to read and improve your HRV.
- Liang T, et al. Deriving accurate nocturnal heart rate, rMSSD and frequency HRV from the Oura Ring. Sensors, 2024.
- Apple Developer Documentation: heartRateVariabilitySDNN (HealthKit).
This glossary is general information to help you understand your training data. It isn't medical advice, diagnosis or treatment. For injury, illness, medication, blood test results or any health concern, speak to a qualified health professional.
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