A norm table can tell you roughly where your HRV sits among people like you, but only if it measured HRV the same way you do. Age shifts typical values more than anything else. Sex and fitness make smaller differences, and much of the spread between people has no known cause.
This lesson shows you how to read a norm table without being misled by it, and how to use the HRV checker as a worked example.
What a norm table tells you
A norm table describes a group of people who were measured in one study. Usually everyone in the group was healthy, so the table cannot sort values into healthy and unhealthy. Most tables give one of two kinds of summary:
- Percentiles. The 50th percentile (the median) is the middle value: half the group measured lower, half higher. The 25th and 75th percentiles mark the middle half of the group.
- Mean and standard deviation (SD). The mean is the average. The SD says how spread out the values are around it.
Picture the whole group lined up from lowest to highest HRV. A percentile tells you where in that line your number would stand. It does not tell you whether standing there is good or bad.
Check the small print first
A norm table only applies to your number if it used the same metric, a similar kind of device and similar measuring conditions. Before you compare, check five things.
| Check | Why it matters | Example |
|---|---|---|
| Metric | RMSSD RMSSD Root mean square of successive differences: an HRV metric built from how much each heartbeat interval differs from the next. It mainly reflects vagal activity. More about RMSSD and SDNN SDNN The standard deviation of all NN intervals in a recording, in milliseconds. It measures overall variability, and its value depends strongly on how long the recording lasts. More about SDNN are different numbers | Apple Watch shows SDNN; most tables list RMSSD |
| Conditions | Lying down, sitting, asleep and awake all give different values | A 5-minute reading lying down is not an overnight average |
| Device | Chest ECG ECG A recording of the heart's electrical activity, taken with electrodes on the skin. ECG-based RR intervals are the reference standard for measuring HRV. More about ECG and wrist or finger optical sensors can differ | Research norms mostly come from ECG |
| Population | Age, health and country of the group shape the values | A study of 25–74-year-olds says little about a 20-year-old |
| Statistic | Percentiles and mean ± SD are read differently | In one table the checker uses, the SD describes spread between study averages |
Age: the biggest single factor
Typical HRV falls steadily across adult life, and the checker’s main data set shows the pattern. Voss and colleagues (2015) measured 1,906 healthy adults aged 25 to 74 in the KORA S4 study in southern Germany, using a 5-minute ECG while people lay down after resting. For men aged 25 to 34 the median RMSSD was 36.2 ms. For men aged 55 to 64 it was 17.5 ms, less than half. Women showed the same pattern: 38.4 ms at 25 to 34 and 18.9 ms at 55 to 64.
Larger data sets agree. In about 8 million Fitbit users, HRV measures fell with age, and the measures linked to the vagus nerve Vagus nerve The main nerve of the parasympathetic nervous system, running from the brainstem to the heart, lungs and gut. Its fast signals to the heart drive most beat-to-beat HRV. More about Vagus nerve fell fastest (Natarajan and colleagues, 2020). In 28,175 people who measured their RMSSD on waking with a phone app, age was the population factor most clearly linked with HRV (Altini and Plews, 2021).
The full tables by age and sex are on the normal HRV by age page.
Sex: a smaller difference than you might think
Differences between men and women are small, and their direction depends on the metric. In the Voss data, RMSSD and SDNN did not differ significantly between men and women; the differences showed up mainly in frequency measures and faded in older age groups. A meta-analysis of 63,612 people found that women, on average, had a slightly lower SDNN but more high-frequency power HF power The share of heart rate variability in fast rhythms of 0.15 to 0.40 Hz, the range of normal breathing. It mainly reflects vagal activity when breathing is 9 to 24 breaths a minute. More about HF power , a vagal measure, despite a faster heart rate (Koenig and Thayer, 2016). In the app data above, RMSSD was not linked with sex at all (Altini and Plews, 2021).
If you menstruate, your HRV can also shift across the cycle. Lesson 10 shows how to allow for that in your baseline Baseline Your own usual HRV level and range, built from weeks of readings taken the same way. Comparing a reading with your baseline says more than comparing it with other people. More about Baseline .
Fitness and everything else
More active people tend to have higher HRV. In the Fitbit data, more daily activity went with better HRV measures, in a dose-dependent way (Natarajan and colleagues, 2020). In the app data, the link with activity level was real but weak (Altini and Plews, 2021).
Most of the difference between people remains unexplained. In that same study, age, sex, activity level and body mass index together explained only 15% of the differences in RMSSD between people. The rest comes from things the study did not measure. Two healthy people of the same age, sex and fitness can have very different HRV.
The checker asks for your activity level for this reason. Its reference data does not split people by fitness, so if you train most days, you may sit higher than the group.
Try it: where does your number sit?
The checker can give you one of five kinds of result:
- A percentile band, such as “around the 25th–50th percentile for men aged 35–44”. This comes from the Voss tables and needs an RMSSD or SDNN value, an age from 25 to 74 and your sex. If you enter lnRMSSD lnRMSSD The natural logarithm of RMSSD. Taking the log evens out the spread of RMSSD values, which makes day-to-day changes easier to compare and analyze. More about lnRMSSD , it converts it to RMSSD first.
- A comparison with adults in general. If you leave out your sex, or your age falls outside 25 to 74, the checker uses averages from a review of 44 studies by Nunan and colleagues (2010), as summarised by Shaffer and Ginsberg (2017): about 42 ms for RMSSD and 50 ms for SDNN. The spread in that table is the spread between study averages, which is much narrower than the spread between people. Treat this result as a rough guide.
- “Not comparable.” You chose “My app’s HRV score”. Apps measure at different times and some use their own formula or scale, so the checker explains what your device measures instead of comparing.
- Out of range. The number is outside what a person’s RMSSD or SDNN plausibly is, often because of a typo or the wrong metric.
- No comparison under 18. The reference data covers adults only.
What your percentile does and doesn’t mean
A percentile tells you your place in the line. If you sit at the 30th percentile, about 30 in 100 people in that group measured lower than you, and 70 measured higher. In a study of healthy adults, a quarter of them sit below the 25th percentile by definition. A high value is not always a good sign either, as lesson 4 showed.
The checker’s percentile bands also come from a 5-minute reading lying down. If your number is an overnight average from a ring or watch, the match is rough at best. Read what is a good HRV and what a low HRV means for more, and talk to a doctor if you have symptoms such as chest pain, fainting or a racing heart, whatever your number says.
For day-to-day use, your own trend matters more than any table. Lesson 10 shows you how to build one.
Next: Why your devices disagree.