Parasympathetic saturation
yet another good reason to measure your HRV while sitting
In this blog, I discuss parasympathetic saturation and cover a feature we have released in HRV4Training Pro to allow you to determine the likelihood of parasympathetic saturation in your data or your athlete's data.
What's parasympathetic saturation?
Parasympathetic saturation refers to a situation in which parasympathetic activity is particularly high, but this is not reflected accurately in HRV data.
As Kiviniemi et al. explain in [1], "possible physiological mechanisms underlying saturation could be due to the dose response of the heart to the acetylcholine secreted by vagal nerve ending. The dose response to acetylcholine has been considered to be linear until its concentration reaches the level at which a further increase in acetylcholine concentration does not produce a change in the response" - which basically means that despite an increase of parasympathetic control on heart rhythm, variability does not increases.
Daniel Plews adds [3]: "a heightened vagal tone may give rise to sustained parasympathetic control of the sinus node, which may eliminate respiratory heart modulation and reduce HRV" - giving a possible explanation for the decoupling between increased parasympathetic activity and increased HRV, i.e. it could be that an important part of HRV, due to respiratory modulation, is somewhat suppressed or canceled out when parasympathetic control is particularly high.
It follows that, as reported in another of Daniel's papers when discussing tapering [2], "in some circumstances, such as vagal saturation, decreases in cardiac parasympathetic indices of HRV during this particular training phase can be related to positive performance outcomes and consequently reductions in HRV, so should not be viewed negatively".
In practical terms, it could be that sometimes HRV is suppressed, but this suppression is not associated with increased stress.
How can we identify parasympathetic saturation?
A way to identify possible parasympathetic saturation is to look at the relationship between HRV and RR interval length.
Let’s first not forget that parasympathetic saturation is a rare event that can typically happen in endurance athletes, during high training load blocks. While parasympathetic saturation is an important aspect to consider, it is important that we also recognize that it is a relatively rare situation.
Under these circumstances, you can look at the relationship between HRV and the average RR interval length (basically the inverse of heart rate), to determine the likelihood of saturation.
Normally, higher HRV is associated with lower heart rate (see data below for an example), and therefore we expect a linear relationship. However, if you are in a period of high training load and HRV is low, together with low heart rate, and therefore the correlation between HRV and the average RR interval length is small or negative (we lose the linear relationship that we were just discussing), parasympathetic saturation is plausible (below I'll show how you can look at this in our platform).
In fact, parasympathetic saturation is one of the reasons why I stopped measuring my HRV while lying down, and started measuring while sitting. If you switched as well, and your HRV is higher when sitting, it is possible that the data was saturated when lying down (as you would otherwise expect the opposite, with higher HRV when lying down with respect to sitting or standing).
As sitting adds a little stress, it becomes less likely that you encounter a situation of saturation. Please see the blog below if you’d like to learn more about measurement position and why sitting is in my view the ideal position for HRV measurements.
Heart rate variability (HRV) measurement position: lying down, sitting or standing?
In the past year, I’ve started recommending measuring HRV while sitting, as opposed to lying down. I came to this conclusion after several conversations with a trusted expert in the field (Andrew Flatt), self-experimentation in different positions over an entire year (so that I could look at the relationship between the data and various acute and chroni…
What can you do about it?
Depending on how you measure your HRV, you could be pro-active 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 below to determine if parasympathetic saturation is likely in your own case. If there is a weak correlation between resting heart rate (or RR interval length) and HRV, 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 [4].
Use HRV4Training Pro to determine the likelihood of parasympathetic saturation for you and your athletes
As mentioned earlier, if you are in a period of high training load and HRV is low, together with low heart rate, and therefore the correlation between HRV and the average RR interval length is small or negative, parasympathetic saturation is plausible.
We have developed a feature in HRV4Training Pro to help you analyze this relationship. In the plot below, you would see the darker dots in the lower right corner (low HRV, low heart rate or high RR interval length). In this case, the suppression in HRV should not be interpreted negatively, as reported by Plews et al.: "the lack of correlation between the R-R interval and Ln rMSSD indicate that athletes are more likely to undergo parasympathetic saturation".
You can find the plot below under Insights / Resting Physiology in HRV4Training Pro, we also report the correlation between HRV and the RR interval length for the past 2 and 6 weeks, so that you can more easily spot any recent changes.
In this first example, you can see a high, positive correlation between HRV and RR interval length both over 2 and 6 weeks:
in this second example, the correlations are lower, but still positive:
Saturation would likely show no correlation (near zero, as shown in Daniel Plews’ paper).
I hope this was informative, and thank you for reading!
References
[1] Kiviniemi AM, Hautala AJ, Seppanen T, Makikallio TH, Huikuri HV, Tulppo MP. Saturation of high-frequency oscillations of RR intervals in healthy subjects and patients after acute myocardial infarction during ambulatory conditions. American Journal of Physiology-Heart and Circulatory Physiology. 2004 Nov;287(5):H1921-7
[2] Plews DJ, Laursen PB, Buchheit M. Day-to-day heart-rate variability recordings in world-champion rowers: appreciating unique athlete characteristics. International journal of sports physiology and performance. 2017 May 1;12(5):697-703
[3] Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sports medicine. 2013 Sep 1;43(9):773-81
[4] Andrew Flatt's blog: https://hrvtraining.com/
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.
He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
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Fascinating as I have on a handful occasions experienced this myself.
I love how we continue to learn about HRV and its metrics.
Interesting read once again, Marco!