Blog post by Marco Altini I often talk about your "normal values" as the only meaningful way to make use of Heart Rate Variability (HRV) data. But what are these normal values? Why are they important? Simply put, your normal values are a representation of your historical data. They allow you to understand if acute (daily) and chronic (weekly) HRV responses are showing meaningful changes or just small variations that you should not worry about. Normal values make the data actionable. Why do we need normal values? This has to do with the high day to day variability in HRV data. It might be easier to show this with an example. Let's look at the data below. This is typical HRV data, there is much variability between consecutive days. Should the highlighted reduction trigger concerns and adjustments in our plans or not? Many tools will allow you to at least look at your baseline, computed as a weekly average, or smoother version of your daily HRV. Does this solve the problem? Not really, we get a better understanding of the recent value, but still, are these reductions meaningful? The solution to these issues, is to establish your normal range, or normal values. In HRV4Training we build your normal values based on your past 60 days of data (more info, here). There are no population values for these, you need to collect data for a while in order to be able to determine your own range. Your normal values make it easy to capture meaningful acute drops as well as longer-term, chronic reductions below what is considered normal variability for you. This is based on what we call the Smallest Worthwhile Change in the scientific literature. In HRV4Training, you can see your normal values for both heart rate and HRV, on the homepage. This way, you can quickly check if there were any abnormal physiological responses on a given day (acute change), or with respect to your baseline (chronic change). This is the approach currently used by state of the art research on HRV-guided training, which I discuss in this blog. Remember that using HRV requires a mindset shift: from higher is better, to normal is better.
Outside of training, the same applies. While many tools out there started converting your physiological and behavioral data in 0 to 100 scores, physiology does not work that way, and it makes little sense to do so. Use a tool that clearly shows you when day to day and weekly changes are outside of your normal range, to make the most of the data. A boring, within-normal HRV is ideal. I discuss these aspects in this blog as well, in point 3, together with other considerations covering:
If you are using HRV4Training Pro, you can see your normal range visually in the baseline page as well. Enjoy! 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 |