Enjoyed chatting with Ross and Mike about the physiology, measurement and application of heart rate variability (HRV) for the latest Real Science of Sport podcast.

Thank you for having me.

You can find it here.

About one year ago, following a few interesting exchanges via email with Sander Berk at Dutch Triathlon, as well as with Raúl Celdrán, Alan Couzens and James Cobb on Twitter, I got more interested in HRV analysis during exercise.

Early research from Thomas Gronwald and co-authors had shown that you could potentially identify the aerobic threshold using this method. This looked like a potentially useful way to assess exercise intensity without the need for indirect calorimetry, lactate meters or even knowing our maximal heart rate. 

A few months later I added DFA alpha 1 to our general purpose research app, the Heart Rate Variability Logger, which became the first tool able to offer this analysis in real-time. I had also released code for others to use, which was indeed picked up by many, developing the various options currently available. 

The proliferation of these tools, led to many more people trying out the method, more research groups collecting and analyzing data, and more insights on the strengths and limitations of DFA alpha 1. This is exactly how research should work.

As scientists, we need to be able to look at the data and the new evidence, and update our view accordingly. Otherwise, we are doing a really poor job.

Given the data that I have seen in the past months, both anecdotally from users and in published literature, it is undeniable now that we cannot promote the use of a universal threshold (0.75) to detect the aerobic threshold at the individual level. 

In this post, I cover in more detail current issues and potential applications of this type of analysis, which certainly remains of interest, even though not for the reasons originally thought. 

always fun to talk to coaches and athletes that have been using HRV4Training for many years

check out my chat with Colin and Elliot, here

Thank you for having me!

We first need to define our application of interest.

Both heart rate and HRV can be used for different applications and measured under different conditions. In this blog, 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.).
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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.

Back to morning vs night. Apart from my anecdotal data above showing a very good match between the two, what does the research say?

​In the latest paper looking at this exact question, "Evaluation of nocturnal vs. morning measures of heart rate indices in young athletes", Christina Mishica and co-authors report that "heart rate and RMSSD obtained during nocturnal sleep and in the morning did not differ".

We can even look at the data for both heart rate and rMSSD, a marker of parasympathetic activity (the same feature used in HRV4Training or in the Oura ring), which indeed show great agreement:

You can find the full text of the paper here.

As I have tried to cover in this and other blog posts, morning and night measurements can be used to capture baseline physiological stress in response to acute and chronic stressors. Both methods have been used in different studies resulting in the same outcomes in terms of the relationship between HRV, training load, and recovery (see an overview here).
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While long term trends will be similar between these two methods, there are a few differences to keep in mind, mainly linked to these aspects:

• Workout (or other stressors) timing: if you exercise in the evening (or experience a late stressor, such as a large late dinner or alcohol intake), your HRV will take some time before going back to normal, and therefore it might be lower during the night, even if in the morning it’s all back to normal. This means that if you work out at different times of the day (sometimes in the morning and sometimes in the evening) a morning measurement might be better suited for you. On the other hand, if your training schedule is fairly similar across days, then night measurements will not reflect any differences and will work as well as morning measurements. Long-term trends will be similar between methods, but the acute or day-to-day response might differ based on stressor timing. Associated to this, it is my opinion  that it might make more sense to measure your physiological stress after the restorative effect of sleep, and not during, if we want to use the data for daily guidance (actionability) more than retrospectively. 
• Arrhythmias: in the context of measuring HRV, arrhythmias are artifacts. As I have described elsewhere, a single beat out of place will cause a disruption and artificially increase HRV. Normally, when we have such isolated events, we can deal with them and provide accurate estimates of HRV. However, if the issues are more frequent, and happen every few seconds, there is nothing to do and simply HRV cannot be correctly determined. Unfortunately, if your arrhythmia is frequent during the night, there is no point using a device that measures as you sleep. In this case, the only way to measure HRV is to take a morning measurement during a period in which you have no or fewer ectopic beats. This is not to say that devices using night measurements are inferior in terms of artifact detection or removal. However, in the morning you have control, you can wait a bit, you can assess if the measurement was artifacted, etc. — in the night your data will be impacted by ectopic beats and there is really nothing we can do. These issues should be carefully evaluated in sports settings as athletes tend to have a higher prevalence of ectopic beats, especially in the context of endurance sports.
• Parasympathetic saturation: parasympathetic saturation refers to a situation in which parasympathetic activity is particularly high, but this is not reflected accurately in HRV data. Parasympathetic saturation is a rare event that can happen in elite endurance athletes during high load training blocks, and you can learn more here. Depending on how you measure your HRV, you could be proactive and collect data that is less likely to be affected by the issue of parasympathetic saturation. In particular: if you measure your HRV during the night, there isn’t anything you can do. Hence you should use the procedure explained in the blog post here to determine if parasympathetic saturation is likely in your own case. In this case, it might be preferable to use a morning measurement. If you measure in the morning, you can measure while sitting (or standing), so that you add a little stress on your body and potentially prevent the issue of parasympathetic saturation, as recommended by Andrew Flatt

What are the takeaways here?

In my opinion, when it comes to the data, there is no advantage in using one method or the other. However, if you prefer to wear something over the night, get a device that does so. If you prefer not to wear something during the night and just to take a measurement in the morning, then go that way.

If your athlete can’t be bothered to take a morning measurement, get a device that tracks HRV during the night. If you are not sure this is for you, you can use your phone camera and invest as little as 10$ in measuring your physiology daily with an independently validated HRV app such as HRV4Training.
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Once again, if you like wearables, they can clearly capture high-quality HRV data as we sleep. Just make sure to use one that gives you the full night of data, as otherwise HRV measurements won't be reliable (as I discuss in greater detail here). My recommendation would be the Oura ring for this exact reason: most other sensors will provide automatically collected sporadic data points (e.g. 5 minutes during the night, like the Apple Watch does), which unfortunately are noisy and do not reflect underlying physiological stress very well.

As an alternative, you can get the same data with a morning measurement taken with HRV4Training, the only validated camera-based app. Pretty simple and cost effective, as long as measuring in the morning works in your daily routine.

This is great news as we all have different reasons to use one method or the other (cost, preference for passive measurements, etc.), but as long as we use valid tools, the same physiological processes can be captured over time.

This consistency will help us move forward in many areas of research in which these sensors or apps are currently deployed.

Stay in touch.

I have recently joined the editorial board of IEEE Pervasive Computing Magazine.

​Here you can find our first article, written with Lucy Dunne, and covering future trends in wearable technology

​Enjoy the read

Professor Maria Carrasco-Poyatos and co-authors at the University of Almería just published the latest paper on HRV-guided training, titled "Heart rate variability-guided training in professional runners: effects on performance and vagal modulation"

Thank you Maria and co-authors for using HRV4Training and for involving me in this work. You can find the paper, here, including the main highlights:

• HRV-guided training allows professional runners to achieve higher training intensities.
• This is reflected in their cardiovascular performance and HRV enhancement.
• The increment in HRV scores suggest better cardiovascular adaptations.
• A polarized training is recommended to improve performance and vagal modulation.