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On Heart Rate Variability (HRV), training load and subjective metrics

2/17/2020

 
Blog post by Marco Altini

Part 4 of our Ultimate Guide to Heart Rate Variability is all about common misconceptions (full post coming soon). In this post, I am covering an important misconception on HRV and subjective data. 

Misconception 7: HRV is less useful than subjective data to capture how an athlete responds to training

This misconception is mostly deriving from a paper that a few years back stated that subjective metrics are better than objective ones in monitoring athlete training response. 

But let’s look at what was actually analyzed in the paper.

The authors looked at how training load related to both subjective and objective metrics, hence according to the paper, the reference to determine if a metric is a valid metric, is how it correlates to training load. 
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In my opinion, the whole assumption that you should find the metric that “correlates the most” with training load, makes very little sense. Why? Because you are already measuring training load, so what is the point of having another metric that gives you the exact same information? Well, none. By definition, if a metric is perfectly correlated to training load, then it is a useless metric, as it does not add any information to the training and recovery equation (but ironically, it would have been interpreted by the study as the best metric).

I’ve already discussed before how the notion that increased load should trigger a reduction in HRV is very simplistic. As a matter of fact, we have seen we can have stable or increased HRV when increasing load (a sign of positive adaptation) as well as reduced HRV with low load because of other stressors (travel, work, etc.). HRV tells you how you are responding and coping with stress, and you can use that information as part of your decision-making process (you can find many case studies here). 

Finally, don’t get me wrong, it is fairly obvious that subjective metrics are also extremely important. This is why we include a questionnaire after the measurement so that you can take a minute to pause, and self-assess how you are feeling subjectively, a key part of the process.

A smart coach, educator or athlete, understands that training load, HRV, and subjective metrics all provide important information that needs to be integrated daily, to decide the better course of action. 

There is no winner between objective and subjective metrics, they all serve a purpose. ​Isn't that obvious?

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    This blog is curated by
    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
    2​b. 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

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