HRV: what heart rate variability measures, and how to read your own trend
HRV, or heart rate variability, is the variation in time between one heartbeat and the next. As Shaffer and Ginsberg put it in their 2017 overview, a healthy heart is not a metronome: even at a steady 60 beats a minute, the gaps between beats differ by a few milliseconds. Most watches and rings report it as RMSSD, the main measure of the influence of the vagus nerve, the brake of the nervous system. The figure is useful only against your own history. A review of 44 studies with 21,438 healthy people by Nunan and colleagues found very large differences between individuals, so a number that is low for one person can be normal for another. Day to day, resting values also move by 4 to 17% for no visible reason. The sensible way to use HRV is to measure it the same way every morning and compare today with your seven-day average, as the calculator above does.
Today's HRV against your seven-day average
Enter your seven-day average RMSSD, your usual day-to-day variation and this morning's reading, all from the same device and position.
- Today against your 7-day average
- -7 ms (-15.6%)
- Your usual range
- 39 to 51 ms
- Reading
- Below your usual range: an easier day is reasonable, check sleep and stress
A training cue, not a medical measurement. Compare only readings taken the same way.
What the number actually measures
Your heart rate is set moment by moment by two branches of the nervous system. One accelerates; the other, through the vagus nerve, slows the heart down and lets it vary from beat to beat. When you are rested and calm, that braking influence tends to dominate, and the intervals between beats vary more.
RMSSD, the root mean square of successive differences, captures exactly that beat-to-beat variation. Shaffer and Ginsberg describe it as the primary time-domain measure of vagally mediated changes in heart rate variability. It is the figure most consumer devices show, usually in milliseconds.
The standards for measuring heart rate variability were set in 1996 by a task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Medical use relies on long recordings and careful conditions. A watch reading taken in bed is a simplified version of the same idea.
Why you should not compare yours with anyone else's
Three facts make comparisons between people misleading.
- Individuals differ enormously. Nunan and colleagues found variations between healthy people of up to 260,000% on some spectral measures. Time-domain measures such as RMSSD vary less, but the spread is still wide.
- Age lowers it. In 24-hour recordings by Umetani and colleagues, RMSSD had fallen to about 47% of its second-decade value by the sixth decade of life, and then stabilised.
- Norms depend on the recording. Shaffer and Ginsberg caution that 24-hour, short-term and ultra-short-term values are not interchangeable. A five-minute reading and a 60-second watch sample cannot be judged against the same table.
So there is no good HRV for a 50-year-old. There is only your own usual range, and whether today sits inside it.
Measuring it so that the trend means something
Martin Buchheit's 2014 review of athlete monitoring recommends near-daily resting recordings of a few minutes, read against the measurement's own error and the smallest change that matters. For anyone using a device at home, that translates into a short routine.
- Measure on waking, before coffee and before checking your phone.
- Use the same position each time, lying or sitting, and the same device.
- Record for the same length each morning, ideally a few minutes, breathing normally.
- Write down the value, or let the app store it, and look at the seven-day average rather than the single reading.
Some devices measure overnight instead. That also works, provided you do not switch between night and morning values. Dobbs and colleagues found that portable devices differ only slightly from an electrocardiogram on average, but with large variation between devices, positions and metrics. Consistency matters more than the brand.
Reading the seven-day trend
A single morning tells you little. Al Haddad and colleagues measured resting HRV in the same people day after day and found a coefficient of variation of 4 to 17% for time-domain measures, even when nothing had changed. A 10% drop on one morning can be noise.
The rolling average reduces that noise. Plews and colleagues followed elite triathletes with a seven-day rolling average of the logarithm of RMSSD; in one athlete, a steady decline in that average came before a period of non-functional overreaching. That study compared only two athletes, so it supports the method rather than any threshold.
The calculator asks for three figures: your seven-day average, your usual day-to-day variation, and today's reading. To estimate the variation, look at your last ten mornings and note how far a typical day sits from the average; many apps show this as a normal range. The tool then tells you whether today is inside that range, below it or above it.
An example from research shows how a rule can work. In a trial by Kiviniemi and colleagues, 26 moderately fit men trained hard unless their HRV fell below the ten-day mean minus one standard deviation, or declined two days running; then they trained easily or rested. It is a research rule, not a standard, but it is a sensible model.
Higher is not always better
It is tempting to read every rise as good news. Plews and colleagues, reviewing elite athletes in 2013, found that both increases and decreases in HRV have been linked to poor adaptation, and recommended appropriate averaging. A sudden jump well above your range, especially with heavy legs or poor sleep, deserves the same attention as a fall.
Everyday factors move the reading: alcohol the night before, a short night, an illness starting, some medicines. That is part of its value, and also why it should be read alongside how you feel. The guide to resting heart rate offers a simpler morning check, and recovery after training explains how sleep and load interact.
Does training by HRV make you fitter?
Somewhat, and less than the marketing suggests. A meta-analysis by Granero-Gallegos and colleagues found a small positive effect of HRV-guided training on VO2max. Another, by Düking and colleagues, found a medium effect on submaximal physiological measures, but only a small and non-significant effect on performance and peak oxygen uptake, with fewer people failing to respond.
For a busy executive, the main benefit is different. The trend gives an objective reason to ease off after a week of short nights and dinners, when pride says otherwise. Slow breathing practice also raises HRV during and just after a session, as explained in coherent breathing.
What a low number does not mean
At population level, low HRV is associated with higher mortality: in a pooled analysis by Jarczok and colleagues, people in the lowest quarter of five-minute RMSSD had a hazard ratio of 1.56. That is an observational finding across groups. It does not mean that a low reading on your watch is a diagnosis, nor that raising the figure will make you live longer.
HRV is a training cue, not a diagnosis. Alcohol, illness, poor sleep and some medicines change it. See a doctor about palpitations, chest pain or fainting, whatever the app shows.
Using it without becoming its servant
Look at the weekly trend, not the daily score. When the average drifts down for several days, protect sleep, lower the intensity and see whether it recovers. When it is stable, train as planned. The coaches of the Club adapt each session to the state you arrive in, with or without a device, and record it in the report that follows. Open your space with one email. For a wider view of the levers that lower stress, see reduce stress.
Questions
What is a good HRV for my age?
There is no reliable answer, which is why this guide does not give one. Healthy people differ hugely, HRV falls with age, and values from 24-hour, five-minute and shorter recordings are not interchangeable. The useful comparison is with your own seven-day average, measured the same way each morning, not with a table or another person's watch.
Why is my HRV lower this morning?
Often for ordinary reasons: alcohol the evening before, a short or broken night, an illness starting or a medicine. Day-to-day readings also vary by 4 to 17% without any cause. Look at the seven-day average. If it drifts down for several days, ease off training and protect sleep.
Are watch and ring HRV readings accurate?
Reasonably, on average, and with wide differences between devices. A meta-analysis by Dobbs and colleagues found a small mean difference from an electrocardiogram but high heterogeneity, depending on the device, body position and metric. Use one device, in one position, at the same time each day, and compare the device only with itself.
Should I skip training when my HRV is low?
Not automatically. One low morning can be noise. A reading below your usual range is a reason to choose an easier session and check sleep and stress, not to cancel the week. In one trial, men trained easily only when HRV fell below their ten-day mean minus one standard deviation, or declined two days in a row.
Sources
- Task Force of the ESC and NASPE: heart rate variability, standards of measurement (Circulation, 1996)
- Shaffer and Ginsberg: an overview of heart rate variability metrics and norms (Front Public Health, 2017)
- Nunan, Sandercock and Brodie: normal values for short-term heart rate variability in healthy adults, a review (Pacing Clin Electrophysiol, 2010)
- Umetani et al.: 24-hour time domain heart rate variability and heart rate, relations to age and gender over nine decades (J Am Coll Cardiol, 1998)
- Al Haddad et al.: reliability of resting and postexercise heart rate measures (Int J Sports Med, 2011)
- Buchheit: monitoring training status with heart rate measures (Front Physiol, 2014)
- Plews et al.: heart rate variability in elite triathletes, is variation in variability the key? (Eur J Appl Physiol, 2012)
- Plews et al.: training adaptation and heart rate variability in elite endurance athletes (Sports Med, 2013)
- Dobbs et al.: the accuracy of acquiring heart rate variability from portable devices, a meta-analysis (Sports Med, 2019)
- Granero-Gallegos et al.: HRV-based training for improving VO2max in endurance athletes, a meta-analysis (Int J Environ Res Public Health, 2020)
- Düking et al.: HRV-guided endurance training with wearables, a systematic review with meta-analysis (J Sci Med Sport, 2021)
- Kiviniemi et al.: endurance training guided individually by daily heart rate variability measurements (Eur J Appl Physiol, 2007)
- Jarczok et al.: heart rate variability in the prediction of mortality, a meta-analysis (Neurosci Biobehav Rev, 2022)
- Laborde et al.: effects of voluntary slow breathing on heart rate and heart rate variability, a meta-analysis (Neurosci Biobehav Rev, 2022)