Blog post by Marco Altini One of my favorite guest posts on our blog was written a few years back by Andrew Flatt. Andrew is a brilliant scientist and coach and has dedicated much of his time to investigating the relationships between HRV, training load and other stressors, in a variety of sports and athletes. The full article focuses mostly on strength and power athletes, and can be found here. However, I believe some aspects are really applicable to any sport, and I'd like to report them here and show a little example using my own data collected with HRV4Training and the Pro platform. Quoting Andrew: "Highly trained individuals are more likely to see a pronounced decrease in HRV the following morning in response to a training session if: 1. The training stimulus is considerably greater than the individual typically experiences (an abrupt increase in load 2. The training stimulus is novel or different from what the individual is accustomed 3. Training is otherwise normal, but non-training related stressors are affecting recovery" Point 3 is the one I'd really like to focus on in this post. Non-training related stressors are key. There's a whole body of research looking for example and how injury risk can increase due to high stress regardless of any changes in training, see psychophysiological models of injury for example. Needless to say, our capacity to handle stress is limited, and this exactly why HRV measurements are useful: they provide an overall marker of stress In my view, non-training related stressors are an often overlooked great reason to use HRV monitoring, despite the fact we all understand well that if something is bothering us (issues at work, at home, financial concerns, etc) we can hardly focus and perform optimally. As a recreational runner, I love to try to make a bit of progress, pushing myself to higher loads from time to time. When I manage to do so gradually and consistently, over longer periods of time ( > than a year for example), I do not expect my HRV to drop during an acute high-load block, as my body is well conditioned, and should assimilate the stimulus properly. When we add other stressors though, the situation can easily change, and this is exactly why it is important to objectively monitor physiological stress and individual responses to stress (in a generic way), so that we can get the full picture. It would be really naive to think that the only thing that matters is training, and all we do in the remaining 22-23 hours of our day is irrelevant. Lets look at some data: Above we can see three plots, with daily measurements collected over 3 months, first thing in the morning using the HRV4Training app:
We can also look at the correlation between physiological data and subjective metrics, in the Explore Correlations page that you can find under Insights in HRV4Training Pro: In the plot above we can see again the strong baseline correlation between heart rate variability measured first thing in the morning, and lifestyle stress. As you can see "work stress" for me is typically the largest factor behind drops in HRV, especially when looking at the big picture (baseline more than day to day correlations).
Alright, hopefully this post gives you a more practical view of what to expect and how to interpret the data, always remember that multiple stressors play a role at the same time, and it is therefore beneficial to look at the data over longer periods of time, including normal values and baseline changes, and contextualizing physiological data (HRV or HR) with respect to your subjective annotations and training load. This is all computed for you in HRV4Training Pro. take care! Comments are closed.
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Marco Altini, founder of HRV4Training Blog Index The Ultimate Guide to HRV 1: Measurement setup 2: Interpreting your data 3: Case studies and practical examples How To 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 HRV Measurements Best Practices 1. Context & Time of the Day 2. Duration 3. Paced breathing 4. Orthostatic Test 5. Slides HRV overview 6. Normal values and historical data 7. HRV features Data Analysis 1a. Acute Changes in HRV (individual level) 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 8. CorSense 9. Samsung Galaxy App Features 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 Other 1. HRV normal values 2. HRV normalization by HR 3. HRV 101 |