For anyone interested in their health and fitness, heart rate variability (HRV) matters: in basic terms, it measures the variation in time between your heartbeats and how those timings fluctuate slightly, by fractions of a second.
HRV can tell you a lot about your heart, and your overall health. It’s a potential indicator of issues such as heart disease and cognitive decline, but it can also show how adaptable and able to cope with stress your heart is, whether you’re exercising or resting. Higher is usually better, showing a more dynamic and capable cardiovascular system.
Read more: Heart rate variability explained
Dig a little deeper into HRV, and you’ll find two key metrics talked about: RMSSD (Root Mean Square of Successive Differences) and SDNN (Standard Deviation of Normal-to-Normal intervals). That might sound jargon-y, but they’re essentially two different ways of interpreting the stats from HRV readings.
Understanding the difference between RMSSD and SDNN, and where it’s best to use them both, gives you improved insights into your heart health.
Why HRV metrics matter
Fitness devices and apps vary in terms of how they show HRV, so it’s important to know what the figures you’re looking at actually represent. With the Ultrahuman Ring AIR, both RMSSD and SDNN are used to compile scores for recovery and for sleep.
While these metrics both deal with HRV, they’re not interchangeable. They’re measuring different aspects of HRV, and giving you different clues about your body, so if you want to know about a specific aspect of your health, you need to know which HRV measurements you’re dealing with.
RMSSD and SDNN shouldn’t be compared with each other either, as they’re measuring two different phenomena. It’s similar to getting two numbers back for your blood pressure readings, which tell you two different things.
Read next: How to improve your heart rate variability (HRV)
At a glance guide
| Metric | Full Name | What It Measures | Timescale | Best For |
| RMSSD | Root Mean Square of Successive Differences | Beat-to-beat parasympathetic activity | Short-term (e.g. 5 min) | Recovery, readiness, wearable apps |
| SDNN | Standard Deviation of NN Intervals | Overall HRV (sympathetic + parasympathetic) | Long-term (e.g. 24 hr ideal) | Clinical, cardiac risk, long-term stress |
RMSSD explained
Let’s take RMSSD first, which is the measurement used by most consumer wearables. As you can see from the table above, it measures short-term variability in heart rate, and reflects changes in parasympathetic (or vagal) activity — the ‘rest and digest’ mode of your nervous system, when you’re recovering and relaxing.
As it works over the short term and quickly responds to changes in the body, RMSSD is perfect for wearables and fitness apps: you can see trends in recovery and sleep quickly. That helps if you want to know whether to continue a workout or take a break.
RMSSD does have its limitations too though. The data from it can be noisy and can be influenced by arrhythmias in the heart. As with any metric, RMSSD needs to be considered in the context of other signals.
SDNN explained
Then there’s SDNN, which takes in a broader range of variability figures over a longer time period. Here we’re dealing with a whole album’s worth of material, rather than a chorus or a bridge from a specific song — it’s more of an overall picture.
Ideally, SDNN needs a full 24-hour ECG (electrocardiogram) reading to work — the more data the better — and is sensitive to both parasympathetic and sympathetic (‘fight or flight’) activity in the nervous system.
With that in mind, you can see why it’s less often shown on wearables and in phone apps. This is a metric that’s been shown to be an accurate indicator of health complications in clinical research, but it’s not so useful for monitoring daily stress and recovery.
Which one should you use?
It’s relatively easy to choose between RMSSD and SDNN as they are so distinct, with no real overlap (other than that they’re measuring HRV). For daily readiness and short-term insights, you need RMSSD.
For longer-term stress load and health, SDNN is the stat to look to. It can tell you about your ongoing risk of issues such as heart disease, and is more exacting when it comes to the amount of data and the quality of data it needs.
Context matters as well. For daily training and a basic understanding of how exercise and sleep affect your body, look to RMSSD. When you’re dealing with clinical reports and wider research, use SDNN.
Conclusion
HRV is one of the most important metrics for understanding your health and fitness, and RMSSD and SDNN are two very useful ways of interpreting this data — for both short-term recovery and long-term heart and body health.
Whenever and wherever you see HRV readings, make sure you know whether they’re referring to RMSSD, SDNN, a combination of the two, or something else entirely: you’ll then be able to translate them into actionable steps much more effectively.
(Disclaimer) The contents of this article are for general information and educational purposes only. It neither provides any medical advice nor intends to substitute professional medical opinion on the treatment, diagnosis, prevention or alleviation of any disease, disorder or disability. Always consult with your doctor or qualified healthcare professional about your health condition and/or concerns before undertaking a new healthcare regimen including making any dietary or lifestyle changes.
