Resting Heart Rate and Heart Rate Variability (HRV): What’s the Difference? — Part 1

In this 5-parts guide, I will try to clarify what are the main differences between resting heart rate (HR) and heart rate variability (HRV). I will cover both the basic physiology of heart rhythm regulation as well as show plenty of data at the population and individual levels.

I will also cover some important misconceptions about available technologies used to measure resting physiology, so that you can make more informed decisions. Most importantly, we will see how we can gain different insights from both HR and HRV, how they can at times capture the same processes, and how they can at times greatly differ (and why!).

You can find the other parts of this series at these links:

Check out my Twitter (@altini_marco) for updates.

Some context first (+why do we even care)

Both HR and HRV can be used for different applications and measured under different conditions. In these posts, our application of interest is determining chronic physiological stress level, which derives from combined strong acute stressors (e.g. a hard workout, intercontinental travel) and long-lasting chronic stressors (e.g. work-related worries, etc.).

By measuring the impact of various stressors (e.g. training or lifestyle) on our resting physiology (HR and HRV), we can make meaningful adjustments that can lead to better health and performance.

In this context, morning measurements (e.g. taken with HRV4Training via the phone camera or using a chest strap) and night measurements (e.g. using an Oura ring) are the only two well-established and reliable ways to assess your HRV. HR and HRV during exercise, or randomly sampled during the night or day, are still representative of autonomic activity (I’ll clear this up in a minute), but are of poor interpretability and therefore outside of the scope of these blogs. The only exception here are measurements during deep breathing exercises, which are particularly useful to better understand differences between resting HR and HRV, as illustrated below.

What are we talking about?

Heart rate (HR) refers to the number of heart beats over a period of time, typically a minute. On the other hand, HRV is a term that refers to ways to summarize in a number the variability between heartbeats, because even if we count 60 beasts in a minute, they do not happen exactly every second.

Both your HR (number of beats) and your HRV (variations in timing between consecutive beats) are modulated by the autonomic nervous system in response to stress. This means that the autonomic nervous system influences heart rhythm. What’s the autonomic nervous system? It’s the part of your nervous system that controls and regulates many functions in your body, from the heart beating to respiration, ~without conscious control. Thus, HR and HRV can indirectly capture changes in autonomic activity non-invasively.

In the next parts of this guide we will see how changes in HR and HRV are tightly coupled to various stressors, but let’s not get ahead of ourselves here.

Let’s start from the beginning.

Physiology: bird’s-eye view

How does the heart beat?

The heart has its own pacemaker, meaning that there’s a spot (called sinoatrial node) that generates electric potentials that initiate contractions, resulting in heart beats. If you had no other mechanism to modulate heart rhythm, our heart would beat at approximately 100 beats per minute (bpm), due to this pacemaker. This intrinsic firing rate is rather constant (hence ~no variability or HRV is present in this state).

On top of this basic mechanism the heart is innervated by the autonomic nervous system. If you are not new to HRV, you probably heard about the main two branches of the autonomic nervous system: the sympathetic and parasympathetic nervous systems. At this point you probably heard also that the sympathetic nervous system is responsible for stimulating the body’s fight or flight response (when we need action, resulting in increased heart rate and reduced HRV), while the parasympathetic nervous system is mainly responsible for the body’s resting functions (resulting in reduced HR and increased HRV).

This is all true, but we need to remember our context here: measuring physiology at rest. At rest, the body is predominantly parasympathetic. This means that what we measure and quantify is almost entirely parasympathetic activity, more than some sort of balance between the two branches. While this might sound a bit abstract right now, there are practical implications associated to the metrics used and conclusions we can derive, which I will cover in more detail in this blog.

If you have measured your HR, you have seen that most likely it is quite a bit lower than the intrinsic firing rate of 100 bpm. In the general population, anything around 60 or 70 is considered normal. If you exercise quite a bit, your HR is probably in the high 40s or low 50s, while if you are a pretty decent athlete, it can go down to the low 30s. This tells us already that at rest, parasympathetic activity is predominant, as HR is highly reduced with respect to the intrisinc rate of firing of the sinoatrial node. But let’s see how we can verify these considerations.

Understanding autonomic control of the heart

How do we know that heart rate (and HRV) are modulated by the autonomic nervous system? And most importantly for applied use of these metrics: how do we know that increased parasympathetic activity reduces HR and increases HRV while sympathetic activity has the opposite effect? At rest, how do we establish that parasympathetic control is dominant, while the sympathetic system has little impact?

All of these questions have been answered by pharmacological blockade. What’s pharmacological blockade? Let’s take a step back and cover basic communication first.

In a nutshell, the human body senses stress through its senses and sends information to the brain, which determines how to deal with them. Sources of stress (stressors) are disruptions that trigger certain reactions as the body tries to maintain a state of balance, also called homeostasis, which is key to ensure optimal functioning. So what happens when we face a stressor? Impulses from the brain, starting in the hypothalamus are sent to (among others) the heart, via the autonomic nervous system, and in particular, this communication happens via neurotransmitters.

The main neurotransmitter of the parasympathetic system is acetylcholine, while the sympathetic system relies mostly on norepinephrine. Thus, when acetylcholine is released, it binds to receptors near the sinoatrial node, and slows down heart rate. This process is pretty quick, with latencies in the order of milliseconds, which means that the parasympathetic system can slow down heart rate almost instantaneously, effectively delaying the next heart beat (and therefore increasing HRV).

Back to pharmacological blockade. Using drugs (in this case atropine), we can make the heart insensitive to acetylcholine, or in other words, we can inhibit the parasympathetic system’s effect on heart rate. What happens when we do so? Heart rate increases, and HRV reduces. In particular, HRV above frequencies of approximately 0.15 Hz is almost absent. In the next section, we’ll dig deeper into why this is the case (hint: it has to do with respiration).

To inhibit sympathetic activity, we can use another drug (propranolol). As expected, when we use this drug, HR decreases. However, the decrease in HR is very small, effectively highlighting how at rest, parasympathetic activity is predominant.

Let’s look at the figure below (from this paper, which is only 40 years old):

Here the authors administered the same drugs (propranolol and atropine) in different orders, but the outcome is always the same. When atropine was administered, HR jumps up (the parasympathetic system is inhibited), while when propranolol was administered, HR slightly reduces. This data, together with results from several other groups, has consistently shown the following:

These experiments highlight clearly how the autonomic nervous system modulates heart rhythm at rest.

A subtle but important difference between autonomic control of HR and HRV

In the figure above, we can see how using different drugs we can inhibit parasympathetic or sympathetic control on heart rhythm (or both). The figure shows the change in resting HR, but I have also covered how not only HR, but also HRV is highly impacted (to a point where we have almost ~no HRV after atropine injection, the drug that “blocks” the parasympathetic system influence on the heart).

However, there is another key point to highlight. Based on the above, we could for example speculate that parasympathetic activity is already entirely reflected on HR. This is not the case because the parasympathetic system doesn’t work like a faucet. The parasympathetic system is not on or off, but acetylcholine release and therefore the slowing down of heart rate, happens synchronously during respiration. In particular, during expiration vagal activity is higher, leading to a slowing down of heart rate that impacts HRV, but not necessarily average HR.

Below is a classic example, we can see beat to beat differences over time (called RR intervals) first during shallow breathing (small beat to beat changes), and then during deep breathing (large oscillations).

Deep breathing practice stimulates parasympathetic activity. This data was collected using HRV4Biofeedback.

If we compute the average HR in the two sections above, so the first ~45" vs the remaining 2'15", we obtain almost the same value (in fact, HR is even a bit lower during shallow breathing, 62 vs 67 bpm). Yet, HRV is much higher during the second part of the recording (doubled, with rMSSD going from 64 to 125 ms).

Let’s recap:

  • The vagus nerve activity on heart rhythm is quick, and therefore captured by high frequency HRV changes. In a matter of milliseconds, heart rate is slowed down. On the contrary, it takes several seconds for sympathetic activity to impact heart rhythm.
  • Vagal activity depends on breathing, with increased firing during expiration, and ~no firing during inspiration. This firing pattern originates in the brain and causes increased HRV, but are not captured by HR alone. This is a key peculiarity of HRV as low modulation of heart rhythm during breathing (read: low HRV) is associated to a number of adverse outcomes.

While beat to beat changes are exaggerated by deep breathing in the figure above, beat to beat variability at rest is always influenced by parasympathetic activity during each breathing cycle. Thus, HRV is more sensitive to parasympathetic activity than HR alone. In the next parts of this guide, we will see how the higher sensitivity of HRV to different stressors is clearly captured in the data.

This is the beauty of our times. While the theory covered here is key to understanding why certain processes are typically better captured by HRV, you don’t have to take my word for it, we already have massive amounts of data backing this up.

Parasympathetic activity and HRV features

So far I have talked about HRV in broader terms, without getting into the specific of the different ways it can be quantified (called features).

It follows from what I have described above, that if we want to quantify parasympathetic activity, and therefore capture high frequency changes in beat to beat differences, we should use mathematical methods able to capture such changes. The most commonly used HRV feature is called rMSSD and is what you can find in HRV4Training, Oura, Whoop, etc. — because it is a simple mathematical way to quantify fast beat to beat changes. Similarly, the high frequency power (HF) captures the ~same mechanisms.

Personally, I consider rMSSD a better choice for various reasons (less dependent on the exact breathing frequency, more reliable across applications, and a few other reasons that you can find here, should you be interested). The key point here is that common HRV features such as rMSSD and HF capture mathematically the fast changing nature of parasympathetic activity, which means that a reduction in these features is typically associated with higher stress.

Takeaways

Let’s try to recap the whole physiological mechanism in a few sentences: as the body tries to maintain a state of balance so that it can function optimally, heart rhythm is influenced by a series of processes going from the brain to the heart via the autonomic nervous system. These processes reflect the level of stress on the body. In particular, we have seen how parasympathetic influence on heart rhythm via acetylcholine release causes HR to reduce. Additionally, acetylcholine release has an almost immediate effect on HR, delaying instantaneously the following heartbeat. This instantaneous effect, combined with increased parasympathetic activity during the exhale, makes it so that HRV, more than HR, can capture resting parasympathetic activity, and thus physiological stress.

Many studies have used pharmacological methods to clearly highlight these pathways and how they impact measurements of HR and HRV, for example by blocking acetylcholine receptors (or parasympathetic activity) and quantifying the resulting drop in HRV and increase in HR. While there is an obvious relationship between HR and HRV, the exact same HR can result in dramatically different HRV. HR does not say anything about beat-to-beat variation (by definition, it is an average) and therefore fails to capture dynamics of the (fast-acting) parasympathetic system. This does not mean that HR is less relevant, but it is simply different, and impacted by other processes. We will see in the next parts of this guide that HR is still extremely valuable, and can at times be even more insightful than HRV (spoiler: for example in the context of cardiorespiratory fitness level).

To conclude:

  • Heart rhythm (both HR and HRV) is influenced by the autonomic nervous system in response to stress.
  • At rest, parasympathetic activity is predominant, which results in lowered HR and increased HRV, with respect to the heart’s intrinsic firing rate.
  • Due to the timing of parasympathetic activity (which is fast and coupled to breathing), HRV analysis captures information not present in average HR alone, highlighting an important difference at the physiological level.

In the next posts, we’ll learn more about available technologies and dig into the data both at the population and at the individual level.

Stay tuned.

Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.

He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.

Marco is the founder of HRV4Training, data science advisor at Oura, and guest lecturer at VU Amsterdam. He loves running.

Twitter: @altini_marco

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Founder HRV4Training.com, Data Science @ouraring Lecturer @VUamsterdam. PhD in Machine Learning, 2x MSc: Sport Science, Computer Science Engineering. Runner

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Marco Altini

Marco Altini

Founder HRV4Training.com, Data Science @ouraring Lecturer @VUamsterdam. PhD in Machine Learning, 2x MSc: Sport Science, Computer Science Engineering. Runner

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