Blog post by Marco Altini
HRV4Training just got a new look (both on Android and iPhone). While we have made quite a few changes, some of the most important are in the homepage, which now displays:
In this post, I will provide an overview of the parameters above, trying to highlight how you can use them to better understand your body's response to training and lifestyle stressors.
Today's score and the daily advice: capture acute changes
The top part of the screen shows your daily HRV and HR, right after the measurement.
Today's score typically captures well strong acute stressors. What’s an acute stressor? Acute stressors are events that affect your physiology in the immediate future. Think about an intense workout, an intercontinental flight, a night out with too many drinks, high caffeine intake, etc. - anything that has an effect on your physiology which lasts from a few minutes up to 24–48 hours. Check out our ultimate guide to HRV, part 2, for some examples.
Typically, strong acute stressors limit our capacity to handle additional stress, and therefore to perform optimally, both mentally and physically. Thus, the daily advice in the app will analyze your daily HRV and determine if today's score is outside of your normal range, to provide you with meaningful advice.
I will cover in the next section the concept of the normal range, but the important bit to remember for now, is simply that HRV data is highly individual and has an inherently high day-to-day variability. This means that it is not meaningful to compare to others, and that in your own data there can be large fluctuations between consecutive days.
What are the implications? To make effective use of the data, we need to be able to determine what changes are trivial, or just part of normal day to day fluctuations (what we call your normal range), and what changes do matter and might require more attention or simply truly represent a positive (or negative) adaptation to training and other stressors.
This is exactly what you see in the homepage with the daily advice which is constructed from today's score and your normal range. Check out an example below, where you can see the daily HRV score below normal in the first two cases, and within the normal range in the third case:
In the three days shown above, the normal range is always the same (7.4 to 7.9 HRV). However, the daily score highlights high acute stress in the first two screenshots, as the values of 7.2 and 7.3 are below the normal range.
In the third screenshot, we have an HRV of 7.8, a score close to the higher end of the normal range, which we can interpret as either lack of strong acute stressors or a positive response to stress.
HRV4Training combines the daily score, normal values and your questionnaire's data to determine the color coding and daily advice message. In particular, the following parameters are used: sleep quality, muscle soreness, motivation to train, perceived performance in your last training (or a subset of these if you do not use all of these tags).
More on your normal range
Your normal range is a representation of your historical data. Currently, we use the past 60 days of your measurements to build your normal range. As soon as you start using the app, HRV4Training will start learning what day to day changes are normal for you, and what changes are outside your normal range. As you gather more data, the app will get better at this job, eventually giving you the best estimate when having all the 60 days of data.
The normal range is always kept current, so that you are not stuck in older data, but at any given time, the most recent 60 days are always used. Over the years, we made a few adjustments to this method, but we believe that 60 days is a great trade-off between the following:
For heart rate and HRV, 60 days of data seems to be just right. Remember that a software that interprets any HRV increase as a good sign, or any HRV decrease as a bad sign, is failing to correctly represent the fact that there are normal variations in physiology, and that only variations outside of this normal range, should trigger concern or more attention or simply be interpreted as actual changes. The new interface in HRV4Training should make it easier to capture changes outside of normal.
Finally, if you are a Pro user, you will also see the normal values in the Baseline page, together with some of your annotations.
Below you can see an example of altered physiology during the menstrual cycle (both HRV and heart rate) as well as a period of higher stress in the third screenshot (several days with suppressed HRV, below normal range).
What about the baseline?
In this post, I have talked about the daily advice, daily score and normal range. However, there is one extra bit of information that can be helpful in keeping track of recent progress, the recent trend or baseline.
In particular, the baseline can give us a more stable indication of how things are trending. A low daily score with a baseline within range could be less problematic than a couple of low daily scores, which will take the baseline also below normal, highlighting a more serious form of stress.
Recent research on HRV-guided training for example relies on the baseline to implement changes in training. If the baseline is below the normal range, then an easier training session or rest are prescribed. Obviously, research studies are often oversimplifications of more complex processes, and while a simple rule (such as "reducing intensity when the baseline is below normal") allows researchers to analyze systematically the impact of this protocol, we might not want to ignore a daily low score either (even if the baseline is still within normal).
In my view, it makes sense in general to focus on the baseline and look at the big picture, this is exactly why we now report trends (both the arrow and numerical value of the baseline) in the homepage for heart rate and HRV. Intuitively, only larger stressors will affect the baseline. However, on days in which we have a lower score, I believe it is important to use that information as well. Try to assess how you feel, also subjectively (of course!), and determine if the acute HRV drop is something transitory (maybe associated to poor sleep) or if it might be something more serious to be cautious about (for example getting sick).
Finally, HRV4Training combines multi-parameter trends to help you better understand the big picture. Looking at baseline changes in HRV, heart rate and the coefficient of variation of HRV, the app can automatically determine if your recent trends are changing in a trivial way, or if the change is something to take more seriously, based on your historical data. Once the various trends have been analyzed, HRV4Training will determine your physiological response to training as one of the following categories:
You can find this analysis under Menu / Insights / HRV Trends, once you have collected at least 40 days of data
Alright, that's all for this post, I hope you are enjoying the new interface and finding it useful to better understand how your physiology is changing both at the acute and at the chronic level. Thank you for your support
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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