Blog post by Marco Altini
In this blog I briefly discuss parasympathetic saturation and introduce a new 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 , "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", or in Daniel Plews' words : "a heightened vagal tone may give rise to sustained parasympathetic control of the sinus node, which may eliminate respiratory heart modulation and reduce HRV".
It follows that as reported in another of Daniel's papers , "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".
How can we identify parasympathetic saturation?
Looking at the relationship between HRV and RR interval length you can identify possible parasympathetic saturation. Parasympathetic saturation is a rare event which can happen in elite endurance athletes during high load training blocks.
In particular, parasympathetic saturation typically requires:
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 to lower HR (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 HR, 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).
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.
New feature in HRV4Training Pro to determine 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 HR, and therefore the correlation between HRV and the average RR interval length is small or negative, parasympathetic saturation is plausible.
We have developed a new 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 HR 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:
Finally, we have added Possible parasympathetic saturation as an automatically detected trend, hence the system will try to do the math for you:
Is this something that should concern you?
In general, parasympathetic saturation is a rare event. Over the years, I have received a few emails from users reading online that they should be sitting instead of lying down when measuring, and I just want to make something clear here: this is typically a non-issue.
If you are an elite endurance athlete, and you have experienced periods of suppressed HRV, low HR, and performed well in training or racing under high loads while your HRV was low, then you are a good candidate and it would be beneficial to measure while sitting or standing.
Otherwise, please do not obsess over something that most likely will never happen, and keep taking your measurements in a consistent manner, so that you can benefit the most from analyzing the data in the long term, as shown in many case studies here.
If you have any doubts, you can login in Pro at HRV4T.com and check your own data.
I hope you will enjoy the new feature, take care!
 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
 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
 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
 Andrew Flatt's blog: https://hrvtraining.com/
Comments are closed.
Register to the mailing list
and try the HRV4Training app!
This blog is curated by
Marco Altini, founder of HRV4Training
The Ultimate Guide to HRV
1: Measurement setup
2: Interpreting your data
3: Case studies and practical examples
1. Intro to HRV
2. How to use HRV, the basics
3. HRV guided training
4. HRV and training load
5. HRV, strength & power
6. Overview in HRV4Training Pro
7. HRV in team sports
1. Context & Time of the Day
3. Paced breathing
4. Orthostatic Test
5. Slides HRV overview
6. Normal values and historical data
7. HRV features
1a. Acute Changes in HRV
1b. Acute Changes in HRV (population level)
1c. Acute Changes in HRV & measurement consistency
1d. Acute Changes in HRV in endurance and power sports
2a. Interpreting HRV Trends
2b. HRV Baseline Trends & CV
3. Tags & Correlations
4. Ectopic beats & motion artifacts
5. HRV4Training Insights
6. HRV4Training & Sports Science
7. HRV & fitness / training load
8. HRV & performance
9. VO2max models
10. Repeated HRV measurements
11. VO2max and performance
12. HR, HRV and performance
13. Training intensity & performance
14. Publication: VO2max & running performance
15. Estimating running performance
16. Coefficient of Variation
17. More on CV and the big picture
18. Case study marathon training
19. Case study injury and lifestyle stress
20. HRV and menstrual cycle
21. Cardiac decoupling
22. FTP, lactate threshold, half and full marathon time estimates
23. Training Monotony
Camera & Sensors
1. ECG vs Polar & Mio Alpha
2a. Camera vs Polar
2b. Camera vs Polar iOS10
2c. iPhone 7+ vs Polar
2d. Comparison of PPG sensors
3. Camera measurement guidelines
4. Validation paper
5. Android camera vs Chest strap
6. Scosche Rhythm24
7. Apple Watch
9. Samsung Galaxy
1. Features and Recovery Points
2. Daily advice
3. HRV4Training insights
4. Sleep tracking
5. Training load analysis
6a. Integration with Strava
6b. Integration with TrainingPeaks
6c. Integration with SportTracks
6d. Integration with Genetrainer
6e. Integration with Apple Health
6f. Integration with Todays Plan
7. Acute HRV changes by sport
8. Remote tags in HRV4T Coach
9. VO2max Estimation
10. Acute stressors analysis
11. Training Polarization
12. Lactate Threshold Estimation
13. Functional Threshold Power(FTP) Estimation for cyclists
14. Aerobic Endurance analysis
15. Intervals Analysis
16. Training Planning
17. Integration with Oura
18. Aerobic efficiency and cardiac decoupling
1. HRV normal values
2. HRV normalization by HR
3. HRV 101