RMSSD vs SDNN: which HRV number your app shows

RMSSD (root mean square of successive differences) is a heart rate variability metric that measures how much each heartbeat interval differs from the next. It mainly reflects parasympathetic (vagal) activity and is the number most rings, straps and phone camera apps report. SDNN (standard deviation of normal-to-normal intervals) measures overall spread and is what Apple Health has long stored. The two are not interchangeable.

HRV (heart rate variability) is the variation in time between heartbeats. This guide shows how each metric is calculated, what each reflects, and which one your device uses. For what a good number is, see the pillar guide what is a good HRV.

What is RMSSD?

RMSSD is the root mean square of successive differences between normal heartbeats, measured in milliseconds. It looks only at the change from one beat interval to the next, so it captures fast, beat-to-beat variation. Shaffer and Ginsberg (2017) call it "the primary time-domain measure used to estimate the vagally mediated changes reflected in HRV."

To calculate RMSSD:

1. Measure each interval between normal heartbeats (the NN or RR interval) in milliseconds.
2. Subtract each interval from the next one.
3. Square each difference.
4. Average the squares.
5. Take the square root.

Because it uses only neighboring beats, RMSSD is less affected by slow drifts in heart rate, such as a gradual rise when you sit up. It also works well on short recordings. In 3,387 adults, RMSSD from a 30-second ECG agreed closely with a 5-minute reading, and RMSSD outperformed SDNN at every length tested (Munoz et al., 2015).

What is SDNN?

SDNN is the standard deviation of all normal heartbeat intervals in a recording, measured in milliseconds. It captures total variation, both fast beat-to-beat changes and slower swings over minutes or hours. Shaffer and Ginsberg note that both sympathetic and parasympathetic activity contribute to SDNN, and that it is linked to morbidity and mortality in research.

To calculate SDNN:

1. Measure each normal interval in milliseconds.
2. Calculate the mean interval.
3. Subtract the mean from each interval and square the result.
4. Average the squares (dividing by n minus 1 for a sample).
5. Take the square root.

SDNN depends strongly on recording length. A 24-hour SDNN includes day and night rhythms and is much larger than a 5-minute SDNN. The two should never be compared directly.

How do RMSSD and SDNN compare?

RMSSD and SDNN both measure heartbeat variation in milliseconds, but they answer different questions. RMSSD asks how much each beat differs from the last, which tracks vagal activity. SDNN asks how spread out all beats are, which mixes vagal, sympathetic and slower rhythms. RMSSD is more stable on short readings; SDNN grows with recording length.

	RMSSD	SDNN
Full name	Root mean square of successive differences	Standard deviation of normal-to-normal intervals
What it captures	Beat-to-beat change	Total spread of intervals
Main influence	Parasympathetic (vagal)	Both autonomic branches plus slower rhythms
Short recordings	Valid even from a single 10 s ECG	30 s or several 10 s ECGs recommended
5-min resting norm, healthy adults	Mean 42 ms (study means 19 to 75)	Mean 50 ms (study means 32 to 93)
Change with age (24-h ECG)	Falls fast, to about 47% of teenage level by the 50s	Falls slowly, to about 60% by the 90s
Typical devices	Rings, straps, phone camera apps	Apple Health (Apple Watch)

Sources: Shaffer and Ginsberg, 2017; Munoz et al., 2015; Nunan et al., 2010; Umetani et al., 1998; Apple HealthKit documentation.

What does a worked example look like?

A short example makes the difference concrete. Take five heartbeat intervals: 1,000, 1,040, 980, 1,020 and 960 ms. The heart rate is 60 bpm on average. RMSSD comes out at about 51 ms, SDNN at about 32 ms and pNN50 at 50%. Same heart, three different numbers.

Step	Values
Intervals (ms)	1,000, 1,040, 980, 1,020, 960
Successive differences (ms)	+40, -60, +40, -60
Squared differences	1,600, 3,600, 1,600, 3,600
RMSSD	Square root of 2,600 = about 51 ms
Mean interval	1,000 ms
Deviations from mean (ms)	0, +40, -20, +20, -40
SDNN (sample)	Square root of 4,000 / 4 = about 32 ms
pNN50	2 of 4 differences above 50 ms = 50%

Example values are illustrative, not from a study.

Here RMSSD is larger than SDNN because the intervals zigzag from beat to beat. If the same intervals rose slowly instead (960, 980, 1,000, 1,020, 1,040), SDNN would stay at about 32 ms but RMSSD would drop to 20 ms. That is the core difference: RMSSD responds to beat-to-beat alternation, SDNN to overall spread.

Which HRV metric does my device use?

Apple Health stores Apple Watch HRV as SDNN. Apple's HealthKit documentation states that it "uses SDNN heart rate variability." Many rings, chest strap apps and phone camera apps report RMSSD. Check your device's help pages, because the label "HRV" alone does not tell you the formula.

Source	Metric
Apple Health (Apple Watch samples)	SDNN
Phone camera HRV apps	Usually RMSSD
Chest strap apps	Usually RMSSD
Rings and other wearables	Varies; check the maker's documentation

Source: Apple HealthKit documentation; device maker pages.

As of October 2026, Apple's developer documentation also lists a separate HealthKit data type for RMSSD, available from iOS 27, next to the SDNN type. Apple Watch Series 12 and Ultra 4 show a "Recovery HRV" value. Apple's support page does not state the formula behind it, so check which data type an app reads. More on this in Apple Watch HRV.

Why can't you compare SDNN and RMSSD?

You cannot compare SDNN and RMSSD because they apply different formulas to the same heartbeats and respond differently to breathing, posture, slow rhythms and recording length. An SDNN of 40 ms and an RMSSD of 40 ms describe different states. Switching metrics or devices means starting a new baseline.

Recording conditions add more differences. Shaffer and Ginsberg warn that 24-hour, short-term and ultra-short norms "are not interchangeable." An Apple Watch SDNN from a background reading, an overnight ring average and a morning camera RMSSD are three different measurements, even for the same person on the same day.

The practical rule: pick one metric from one device, measured the same way, and track it against itself.

Which metric is better for tracking recovery?

For daily recovery tracking, RMSSD is a common choice because it reflects vagal activity and stays reliable on short readings (Munoz et al., 2015). SDNN is the metric most linked to morbidity and mortality in long clinical recordings. Either metric can show a trend if you measure consistently.

Whatever the metric, a 7-day average against your own baseline is more informative than a single value. For age norms, see the HRV chart by age. To record RMSSD without a watch, see measure HRV with your iPhone camera.

How Svanu handles both metrics

Svanu keeps the two metrics apart. Apple Watch HRV arrives through Apple Health as SDNN. Camera HRV, a 20 to 30 second reading with your finger on the rear camera and flash, is computed as RMSSD. Camera readings are compared only with camera readings, never with the watch's overnight SDNN.

The recovery score compares this morning's HRV and resting heart rate with your own recent baseline, plus sleep. Every score shows its inputs and what moved it, so you can see which HRV value was used. Learn more on the Svanu home page.

The short answer

RMSSD measures beat-to-beat change and mainly reflects vagal activity. SDNN measures the total spread of heartbeat intervals and grows with recording length. Apple Health stores Apple Watch HRV as SDNN (iOS 27 adds an RMSSD type); many other apps report RMSSD. The numbers are not comparable, so track one metric from one device over time.