HRV

This content is for informational purposes only and is not a substitute for professional advice.

Heart Rate Variability measures the variation in time between heartbeats and is used to gauge recovery status.

How HRV is Measured

RMSSD captures rapid, beat-to-beat variability driven almost entirely by the parasympathetic (vagal) branch of the autonomic nervous system, whereas SDNN measures the overall spread of all “normal-to-normal” intervals across the recording window and therefore reflects combined sympathetic + parasympathetic influence and is strongly affected by how long you record.

In practice that means wearables aimed at nightly recovery (Oura, Whoop) report RMSSD, while Apple Watch logs SDNN during short 1- to 5-minute optical heart-rate samples.

RMSSD Highlights Fast Shifts

The root-mean-square of successive differences squares each gap between adjacent R-R intervals, averages those squares, then takes the square root; that math suppresses slow drifts and magnifies beat-to-beat swings, which are almost entirely vagally mediated. Because it needs only ~30 s–5 min of clean data and tracks breath-to-breath changes, RMSSD is popular for recovery scores, meditation feedback, and overnight readiness metrics.

SDNN Shows Overall Spread

SDNN computes the standard deviation of all normal R-R intervals in the sample; when measured over 24 h it is considered the clinical benchmark for cardiac-risk stratification because it catches circadian swings, activity bursts, and autonomic balance in one number. Shorter SDNN snapshots—such as the 1- to 5-minute readings taken by Apple Watch—still reflect global variability but are more sensitive to time-of-day and movement noise, so Apple recommends comparing them only to your own trend.

Device HRV Algorithm

DeviceTime-domain metric reportedPrimary use-case justification
Apple WatchSDNNCaptures whole-sample variability in quick optical scans, matching HealthKit’s legacy SDNN field and aligning with clinical 5-min standards.
Oura RingRMSSDNight-long, five-minute rolling windows focus on parasympathetic recovery during sleep, reducing movement artefacts.
Whoop StrapRMSSDOvernight RMSSD feeds its Recovery and Strain models, emphasizing vagal rebound after training or stress.

Related