What is heart rate variability?

Content of essentials article

• Article summary
• What is heart rate variability?
• Why should we care about heart rate variability?
• How to collect accurate data
• How to collect meaningful data
• Interpreting the normal range
• What’s the difference between resting heart rate and HRV?
• What affects HRV?
• Making HRV actionable: Training prescription

Article summary

• Heart rate variability (HRV) differs from heart rate as it quantifies the variability between heartbeats, reflecting the body’s response to stress modulated by the autonomic nervous system.
• The body’s autonomic nervous system, through neurotransmitters, impacts HRV by altering heart rate in response to stressors, making HRV a sensitive marker of physiological stress.
• Effective use of HRV data involves three key steps: collecting accurate data, collecting meaningful data, and interpreting the data in relation to individual normal values.
• HRV is more sensitive than heart rate in reflecting physiological responses to various stressors like training intensity, alcohol intake, sickness, and menstrual cycle changes.
• HRV data can be utilized for training prescription, helping to tailor training stimuli based on individual stress responses, thus aiding in performance improvement and health management.

What is heart rate variability?

While heart rate is the number of heart beats over a period of time, typically a minute, heart rate variability (HRV) refers to ways to quantify the variability between heartbeats: even if we count 60 beats in a minute, they do not happen exactly every second.

The autonomic nervous system modulates both your heart rate and your HRV in response to stress, just as it controls and regulates many bodily functions in response to the stressors we face.

We typically think of the autonomic nervous system in the context of its two branches, the sympathetic and parasympathetic nervous systems. While the sympathetic nervous system is responsible for stimulating the body’s fight or flight response, the parasympathetic nervous system is mainly responsible for the body’s resting functions ^{[1, 3]}. Both resting heart rate and HRV are mediated by neurons with parasympathetic and sympathetic origins. Thus, changes in resting heart rate and HRV can reflect our response to stress.

Resting physiology is a proxy for physiological stress, due to the relationship between stress, the autonomic nervous system and heart rhythm.

Why should we care about heart rate variability?

The human body detects stress through its senses and sends information to the brain, which determines how to respond. Sources of stress (stressors) are disruptions that trigger specific responses as the body tries to maintain a state of balance, also called homeostasis, which is key to ensuring optimal functioning in general health and performance, alike.The autonomic nervous system, which is regulated by the hypothalamus, conducts impulses from the brain and spinal cord to smooth muscles and the heart .

The heart has its own pacemaker, the sinoatrial node, that generates electric potentials that initiate contractions resulting in heartbeats. 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 – there is no HRV rooted in the sinoatrial node.

On top of this basic mechanism, the heart is innervated by the autonomic nervous system. If you have measured your resting heart rate, 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 – 70 bpm is normal, while lower heart rates are common in athletes. This tells us already that, at rest, parasympathetic activity is predominant, as heart rate is much lower than the intrinsic firing rate of the sinoatrial node ^[4].

When we face a stressor, impulses from the brain are sent to the heart, among other locations, via neurotransmitters and the autonomic nervous system.

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 quick, with latencies in the order of milliseconds. The parasympathetic system can slow down heart rate almost instantaneously ^{[2, 4]}, effectively delaying the next heartbeat and, therefore, increasing HRV.

Due to the timing of parasympathetic activity, which is impacted by respiration and increases during the exhale, HRV captures information not present in average heart rate alone, highlighting an important difference at the physiological level. We will see later how these differences result in HRV being a more sensitive marker of stress ^{[4, 5]}.

Three steps to make use of HRV data: collect accurate data, collect meaningful data, interpret the data (normal values)

Given the myriad of apps, sensors and wearables that promise to measure HRV today, we need to be able to identify the ones that can give us useful insights.

In particular, there are three key steps to make use of HRV data:

• Collecting accurate data
• Collecting meaningful data
• Interpreting the data

Collecting accurate data

Technology for HRV measurement at rest is getting better every day. At HRV4Training, we have developed the first camera-based approach to collect HRV data accurately, which has been independently validated ^{[6, 7]}. Additionally, other devices have been recently validated through spot checks or night-long recordings.

Collecting accurate data means that the data we obtain has a degree of accuracy that is similar to reference systems, such as an electrocardiogram (ECG). This boils down to being able to measure the RR intervals (or PP intervals, for optical methods) correctly.

When you pick an app or sensor, the question to ask is: has this app or sensor been validated, showing that the reading of an HRV measurement is equivalent to that from an ECG or Polar chest strap? If there is no data showing this level of accuracy for the device you are interested in, don’t bother.

Here are a few options, with citations to their validations:

• HRV4Training using the phone camera ^{[6, 7]}
• Oura ring ^[7]
• Polar Vantage V2 ^[8]
• Apple Watch ^[9]
• Polar H7 or H10, paired to HRV4Training ^{[6, 7]}

Collecting meaningful data

Using an app or a sensor to measure accurately is only the first step. In order to make use of HRV data, we need to make sure that the data is measured at a meaningful time. This is where many sensors that automatically measure HRV fail.

Collecting meaningful data is a bit of a new problem, mostly introduced by wearables. Until a few years ago, all we had to do was to show that HRV could be measured accurately, as it was taken for granted that you had to measure it first thing in the morning ^[4]. The morning routine, where you take the reading as soon as you wake up, while relaxed, and before breakfast or exercise, is the optimal way to collect meaningful data, well understood both in research and in applied settings.

Now that we have wearables measuring everything automatically, things can get messy. This is very important because a device that is accurate, but measures at the wrong time, will provide you with data that is of little use.

Depending on when the data is sampled, it might capture very large stressors dramatically affecting your physiology, such as sickness or excessive alcohol intake, but miss more subtle changes. Observing those subtle changes should be the whole point of using these technologies.

If you use a device that measures automatically during the night, you need to make sure the data is collected during the entire night, and not just for a few minutes. This is where the Apple Watch (and others) fail. Collecting a few 5-minute samples per night, or trying to isolate a single 5-minute sample in a specific sleep stage, will provide noisy data that is of little or no use. HRV increases overnight due to the influence of the circadian rhythm, and sleep stages affect autonomic activity, resulting in very high minute-by-minute variability in HRV.

Depending on your preference (cost, interest in wearables, etc.), you might go for a morning or a night measurement. The latest research ^[10] shows that full night and morning measurements are equivalent, hence there is no advantage in using one or the other. Just be consistent with the method you use.

Interpret the normal range

Assuming that we use an accurate sensor and we either measure first thing in the morning or our sensor is able to provide an average of many hours during the night, we have only one more step: interpreting the data.

HRV data has an inherently high day-to-day variability, with large fluctuations between consecutive days. To make effective use of the data, we need to be able to determine what changes are trivial, or just part of normal day-to-day fluctuations, and what changes truly matter. Those might require more attention or simply represent an adaptation – positive or negative – to training and other stressors.

This is where pretty much any software out there fails. They show you a number for today, and you can look at your previous numbers… but then what?

Is my HRV lower because of a serious stressor or is it a bit lower just because of normal day-to-day variability? A software that interprets any HRV increase as a good sign, or any HRV decrease as a bad sign, or simply can’t interpret the change for you, is failing to represent correctly the fact that there are normal variations in physiology, and that only variations outside of this normal range should potentially trigger concern or more attention. Or, again, they may simply be actual changes in heart rate variability.

In the published literature this is called the Smallest Worthwhile Change ^[11].

What’s the difference between resting heart rate and HRV?

Measuring HRV is much more complex than measuring heart rate. For example, any minimal disruption in the signal (either a measurement artefact or an actual ectopic beat) can dramatically change HRV, with minimal or no impact on heart rate. Thus, you should be able to justify going through the trouble of measuring HRV.

But what are the differences between these two measurements of resting physiology?

I mentioned earlier how the heart rate slows down synchronously during respiration, an effect that impacts HR but not average heart rate. Thus, HRV is more sensitive to parasympathetic activity than heart rate alone.

What affects HRV?

HRV becomes particularly useful when we move away from comparisons between individuals or even groups of individuals and start looking at data from the same individual longitudinally in response to various stressors. This process has finally become practical and inexpensive in the past few years, thanks to recent technological developments.

In our latest study, together with Dr. Plews, we analysed data collected using HRV4Training in more than 28,000 people with at least one year of data per person, a total of nine million measurements. Then we looked at the change in resting heart rate and HRV in response to various stressors such as training at different intensities, alcohol intake, sickness and the menstrual cycle ^[5].

Interestingly, the change in HRV with respect to training at different intensities was 4.6%, while the change in heart rate was only 1.3%, highlighting how HRV is more sensitive to this stressor. Additionally, as we can see in the figure below, the change in HRV does not reduce across age groups, indicating that HRV captures training stress equally well for older individuals, while the change in heart rate decreases.

The change in heart rate and HRV in different phases of the menstrual cycle was also in line with changes due to training, with an increase of 1.6% in heart rate between the follicular and the luteal phases, and a reduction in HRV of 3.2%. Once again, HRV is more sensitive.

When we look at alcohol intake and sickness, we have changes in resting physiology that are 3-4 times larger than changes due to training or the menstrual cycle: 6% change in heart rate and 10-12% change in HRV. This is important to remember if we want to use HRV for training guidance. Lifestyle is key, and poor lifestyle or health issues will take over. We need to take a holistic approach to health and performance if we want to make use of these metrics.

If we contextualise the percentage changes reported in this paper with what we know from literature, that the smallest practical or meaningful change in heart rate is 2% and in HRV is 3%, we can see how changes in heart rate are below this threshold, and therefore smaller than normal day-to-day variability. This means that heart rate is not sensitive enough unless we have very strong stressors (e.g. alcohol intake or sickness), and therefore is not particularly useful as we can hardly distinguish signal from noise.

On the other hand, HRV is more sensitive but also less specific to various stressors. Hence, higher stress will be reflected on HRV data no matter where it comes from ^[5].

Making HRV actionable: Training prescription

HRV helps us to quantify individual responses to stress. The idea behind HRV-guided training is that by providing the most appropriate training stimuli in a timely manner when your body is ready to take it, positive adaptations will occur and you will be able to improve performance. Normally, a timely manner means when your daily HRV or baseline HRV is not suppressed with respect to your historical data.

In their research, Alejandro Javaloyes and co-authors showed how HRV-guided training could lead to better performance. They reported:

“[H]ypothesis for this greater adaptation to training for the HRV guided group is in line with the idea of performing high intensity training when the athlete is in optimal conditions to perform it. Therefore, these differences … may be due to a better timing in the programming of high intensity training” ^[12].

Needless to say, our capacity to handle stress is limited. While periodization is an important starting point, we need to be able to add flexibility and provide the right stimulus at the right time, which HRV allows us to do.

Conclusion

As the body tries to maintain a state of balance so 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. Thus, we can use HRV as a generic proxy of stress.

To make use of HRV data, we need to collect accurate data at a meaningful time, and interpret the data with respect to an individual’s normal values.

Make sure the tools you use are validated, can be used for a morning measurement or sample for the entire night, and provide data that is properly contextualised. Once we have collected data for a few weeks, which is necessary to establish our normal range, the data will reflect different stressors, both acute and chronic. Strong stressors, associated with our health and lifestyle (e.g., sickness, alcohol intake or intercontinental travel), can have a dramatic impact on resting physiology. Thus, making use of HRV data requires a holistic approach, considering more than just training.

Finally, capturing stress responses before they develop into negative chronic states can be key in making adjustments leading to improved health and performance.

HRV can be a useful tool for day-to-day load and stress management, for example, by reducing the intensity of the training stimulus when HRV is suppressed below an athlete’s normal values, as we have seen in HRV-guided training research.