Amidst the many improvements to Apple's heart rate measurements with iOS 11 and Apple Watch, Apple also introduced a new measurement called an HRV (Heart Rate Variability) average.

Measuring HRV has been around the medical and exercise community for decades, but it's only just starting to take root in the larger tech community as a popular metric for tracking your everyday wellness and fitness.

As an actively-training athlete, I was particularly curious about HRV values and how they could help me better build my training and taper my workouts, so I did a bit of digging to try and better understand it — and why Apple is starting to track this information.

Obvious disclaimer here: I'm not a scientist, doctor, nor health expert; if you're interested in learning more on this topic beyond this overview, you can find more information at the bottom of this post.

What exactly is HRV, and why do you want to measure it?

When you measure your heart with an Apple Watch or passive electric chest strap (like some of our best external heart rate monitors), the metric you'll see most commonly is your heart beat: You're tracking the number and speed of your heartbeats (the contraction and inflation of your cardiac muscle) to estimate how many beats will occur in 60 seconds, which your device then shows you in BPM (beats per minute).

Monitoring your BPM is useful for a number of reasons, including knowing your basic heart health and making sure you're pushing yourself hard enough (but not too hard) during a workout.

HRV (heart rate variability) is another heartbeat-based metric, but it's not focused on your heart health: Instead, HRV aims to give you a whole lot more information on how a key component of your body — your nervous system — is functioning at any given point.

HRV gives you the pulse of your nervous system

So how do you measure HRV? In short, you track the time in between your heart beats in a given time period; this allows you to see how quickly your autonomic nervous system communicates with your heart. This data is one of the easiest ways for us to get information on how our body is doing on the whole, but it's a bit less straightforward than your standard heartbeat reading.

For one, HRV isn't a single number: The metric can encompass a grouping of time- and frequency-based tests, each with their own math behind them. To start, we'll look at the most common representation of HRV: average heart beat variation in milliseconds (the only value that Apple currently displays in the Health app).

When I first read about HRV, I figured you'd want to have a low average, as that would mean your heart would have a steady "beat beat beat," with little to no variation in pauses. If you were healthy, I figured 60BPM should equal (more or less) one beat per second.

In reality, it's the opposite: At rest, you should actually see high variability between your heartbeats. (In that same 60BPM example, that would shake out to having 0.7 seconds between some beats and 1.1 seconds between others; you'd still end up with 60 beats in a minute, but some of those beats can happen progressively faster or slower than others.)

A poorly-drawn example of heart rate variability during a heart reading, by the author.

This is because your nervous system is constantly adjusting to outside factors, whether they be caffeinated beverages, stress from being in a car, catching a cold, or even changes in your mental state as you watch a movie — if your brain doesn't tell your heart to adjust accordingly, the rest of your body may not get the blood it needs to work effectively.

Let's take sprinting: When you start moving from a standstill, your heart is probably near its resting rate (say, 60-70BPM). But once you go into a sprint, your nervous system has to very quickly adjust the rate that your heart pumps in order to help your legs, lungs, and body keep up.

Measuring heart rate variability lets us monitor the flexibility of our nervous system: Even when your body is at rest, a strong nervous system will adjust after each heartbeat, with millisecond variations between each.

Why tracking your nervous system's health is important

A really helpful overview of HRV from Welltory.

HRV metrics help us track one of the most important parts of our body: Our autonomic nervous system (ANS). This is responsible for helping your brain and its control centers send signals to your heart, muscles, and glands; it helps regulate your stress, digestion, heart functions, and more. Inside the ANS, there are two mini-systems at work: The sympathetic (which regulates your "fight or flight" stress impulses) and parasympathetic (which regulates your energy and helps your body recover during rest periods).

In an ideal world, the two work in harmony to give you the energy you need and conserve it when you don't. A high heart rate variability (HRV) average, for instance, indicates that your parasympathetic system is doing its job helping your body recover and regulate.

But let's be honest: We don't always live in an ideal world. We can take on too much stress, recover poorly, drink, overtrain, and generally fail to take care of our body. When that happens, our sympathetic system is doing more work, leading to lower HRV readings and often higher BPM while at rest.

HRV lets us spy on the balance between your sympathetic and parasynthetic nervous system at any given moment, giving us a peek into how our body is recovering from illness, stress, or workouts. Like tracking your BPM, you need context, which means tracking it regularly and comparing readings with your activities.

Tip: Your variability average is only the tip of the HRV-tracking iceberg; if you use a third-party app on your iPhone and an external heart rate monitor (or camera-based monitor), you can access more detailed metrics to help you better understand how your sympathetic and parasympathetic systems are working together.

Unlike BPM and blood pressure, there's no "healthy" or "unhealthy" general number for a high or low HRV average: It varies depending on the person, which means that if you're interested in tracking your nervous system, you need to regularly take heart measurements to get a good picture of what "high" and "low" values look like for you; ideally, you'd want to take HRV measurements in the morning when you first wake up, so that you can establish a baseline.

What can you learn from HRV tracking?

At a basic level, you can see how well your body is recovering from exercise, illness, or general stress. If you're having a crazy week at work and your HRV average is lower than normal each morning, it can indicate that your body needs more rest and relaxation to balance out your stress.

What that rest looks like varies between people: hanging out with friends can help raise your parasympathetic system and your HRV average, as can engaging in activities you enjoy, deep breathing, yoga, meditation, and regular resting periods.

As an athlete, I find HRV monitoring particularly useful because it can help me tailor my workout programs: If my HRV average is too low the night after a hard workout or skate, I know I pushed myself too hard and will take it easy until my average stabilizes back to my baseline. It allows me to work hard when I know my body's ready for it, but take breaks when I need to so that I can prevent overtraining.

You can also use your HRV baseline to figure out when you prefer exercising, how certain food affects your body, when you start to get sick, and a lot more — it's all about context.

So how do you calculate your HRV average and other metrics?

Thankfully, you don't have to do all the complicated math yourself: There are multiple different wearables available that measure your heart and your HRV, including:

  • EKGs (expensive)
  • passive electric monitors like the Polar heart strap
  • the Apple Watch
  • Other photoplethysmography techniques (like camera-based heartbeat readings)

These different hardware options all have different software associated with them: Most HRV apps can produce your variation average (a time-based datapoint), but many programs also offer more thorough time- and frequency-based HRV metrics.

How Apple calculates HRV

Apple currently records HRV averages in your iPhone's Health app through Apple Watch readings (as well as any third-party apps that have chosen to write data to the repository). When you first put your Apple Watch on for the day, you'll trigger an HRV morning reading; the wearable monitors your heartbeat steadily for one minute, then uses under-the-hood calculations* to come up with your HRV average, displayed as ms (milliseconds) in the Health app for iPhone.

*Apple currently uses SDNN to track HRV in the Health app; it doesn't gather any other HRV data from your Apple Watch, nor does it allow third-party HRV apps to write anything but SDNN data to the Health app.

While Apple's average is useful to get a basic idea of your HRV patterns, the company doesn't yet offer you a more detailed look at any other time- or frequency-based HRV data (though it does store your beat-to-beat readings and timestamps). There's also no obvious way to force an HRV reading outside of the Apple Watch's automated morning and evening readings; starting a Breathe session on your Apple Watch will record the right data, but it's not noted anywhere for users curious about their HRV data and getting subsequent readings.

Elite HRV (a mainstay in the HRV-tracking space) had this to say about why its app doesn't yet support using the Apple Watch for HRV data:

The latest versions of Apple Watch now produce an "HRV" value that is primarily intended for the Apple "Breathe" app. The raw data behind these "HRV" values are not available for analysis and, to the best of our knowledge, are is not intended for calculating RMSSD, LnRMSSD, HF, LF or other trended HRV values.

To be sure, if you are moving your hand, wrist or arm at all, then there is a very low degree of confidence in the accuracy of the HRV calculations that could be produced from the Apple Watch at this time. Even if perfectly still, there are many circumstantial variables to address such as sensor positioning, skin contact, skin thickness/color, emitter spectrum, etc. Until the raw R-R interval data or full pulse waveform data is available for analysis, we will not be able to verify one way or the other.

Marco Altini, creator of HRV4Training, had similar things to say about why their app doesn't support the Apple Watch's metrics:

In HRV4Training we use rMSSD as it is well established that it is a marker of parasympathetic activity, and therefore the lower the value, the higher the level of stress, relative to your baseline / past data (obviously, an oversimplification). From a human physiology point of view, this links to the fact that parasympathetic activity is mainly the activity of the vagus nerve. The vagus nerve acts on receptors signaling nodes to modulate pulse on a beat to beat basis while sympathetic activity has different pathways with slower signaling hence beat to beat changes reflect parasympathetic activity and can be quantified using rMSSD or HF (see Nunan et al.).

Unfortunately Health right now does not allow developers to write features other than SDNN, because that is what the Apple Watch computes and reports. As Apple has been improving Health and the Watch in the past few months, hopefully more HRV features will also be added in the future.

It may well be that Apple is currently only interested in HRV tracking to help users with the Breathe app, or that it doesn't yet think the Apple Watch hardware is accurate enough to give deeper-dive measurements, but I'm excited to see it in the Health app nonetheless — it's a good start from Apple at tracking one of the more-fascinating wellness statistics out there, and I hope we see them add more HRV values as time goes on.

Other apps and devices that calculate HRV

If you want more information than simple HRV averages, there are several other apps that can take and analyze HRV, but you may need to pick up an external heart monitor to use them effectively.

The friendliest app out there for HRV tracking that I've found is Welltory; it breaks down your HRV results into easily-readable areas like Performance (which represents your average HRV), Energy (how your parasympathetic function is working), and Stress (same for the sympathetic). For basic measurements, you don't even need a proper passive electric chest strap — you can use your iPhone's rear camera instead (though this may produce a higher margin of error).

The app is free to use for these basic measurements; upgrade to a paid subscription, however, and you can access more detailed measurements from your HRV calculation (including your LF/HF, VLF, SDNN, and more).

It's worth noting given all the privacy and political concerns of late that Welltory began as a Russian startup. That said, it's currently based out of NY and has a pretty straight-forward privacy policy. Given that the data is analyzed on Welltory's servers, however, I wanted to mention it.

HRV4Training also lets you use either your iPhone's rear camera or an external heart monitor to measure your HRV, but the $8.99 app is designed specifically for the athletic crowd: It tracks the same metrics as Welltory, but uses a 30-day rolling scale to provide suggestions about your baseline and how you should train from day to day. (It is a little buggy on the UI side when running on my iPhone X, but I'm not sure if that's the iPhone model or the app as a whole at fault.)

The aforementioned Elite HRV app has a ton of scientific data behind it and many happy users, but you'll need an external heart rate monitor and a $4.99 in-app purchase to take full advantage of it. The app's UI also hasn't yet been updated for iPhone X.

The $13.99 SweetBeat HRV uses slightly different formulas than Elite HRV, but has the same pros (happy users, lots of data) and cons (older, requires a chest strap, out of date app).

I tried but was unimpressed by Alex Olsson's $3.99 HRV Score, which uses your Apple Watch to track HRV measurements; unfortunately, I couldn't get the app to take a reading without crashing.

More on HRV

Want to read more about HRV? Here are some more in-depth resources that talk about the science behind it, formulas, and some suggestions on how to use it.

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