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In-app HRV trends analysis

10/4/2015

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Blog post by Marco Altini.
In the last post, I've introduced HRV trends analysis and covered the main parameters of interest as well as a few conditions that can be automatically identified using HRV data and some extra information on the current training plan.

In particular, we looked at using HRV (ln rMSSD), HR, HRV/AVNN and CV ln rMSSD as the parameters of interest to analyze HRV trends. We used all of these parameters together to identify the following conditions: no relevant trends detected, coping well with training, maladaptation to training and accumulated fatigue.

I've implemented the same analysis directly in the app, so that you can get the same insights I showed using my own data. Here are a few things you need to know.

What will you get?

The trends analysis will be accessible under Menu - Insights, similarly to the analysis of acute HRV changes.

​The app will analyze your historical data to determine how the different parameters change over time in your specific case. This is necessary to understand what trends are trivial and should not be considered, and what trends are worth investigating. Then, the non-trivial trends will be used to determine your current condition, based on the last two weeks of data.
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The screens above show my condition right now. I've been trying to do intense trainings and intervals in preparation for a race (half marathon coming up in 10 days), however at the same time I got a cold and my data shows indeed that HRV is not looking good and varying a lot on daily basis (non-trivial increase in CV).
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We can see from the trends plot that it's taking me two days every time I train, to get back to normal (each bar with a training indicated at the bottom is followed by two bars with lower HRV values). This situation is probably due to both higher intensity and being partially ill. 

The trends analysis above automatically captures my current struggle with training, reporting that I am showing trends representative of maladaptation to training.

How much data do you need?

The trends analysis will always report your current trend, which is detected using the last 2 weeks of moving averages for the parameters above.

However, the app asks for at least 40 measurements in the past 60 days for the analysis to be performed. Why? The reason for using more data is that the trends analysis needs to understand what trends are just noise (i.e. natural variations in HRV that are not particularly interesting) and what trends are non-trivial and should be part of the analysis.

​You can see this process better in the figure below, the red and yellow segments follow variations that are non-trivial and should be analyzed further (pointed by the blue arrows). There are clearly variations in the rest of the data as well, but they are not considered by the analysis. This procedure requires more data and is the reason why you will need at least 2 months of measurements before you can start using this feature.
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Please note that this analysis is meant to be used as an additional aid for a user or coach, and should be considered in the context of all other non-autonomic (e.g. muscular fatigue) and subjective (e.g. stress, sleep) parameters. Most importantly, the specific training program and training phase need to be considered when analyzing trends. ​By tagging your trainings in HRV4Training (training intensity and phase) you will provide more context around your current training program, and help automating this analysis

The automated trend analysis is an experimental feature and will most likely evolve over time. For questions of feedback on this feature either comment below or contact me on twitter. Your feedback will be of great help to further improve this analysis.
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    This blog is curated by
    Marco Altini, founder of HRV4Training


    ​Blog Index
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    The Ultimate Guide to HRV
    1: Measurement setup
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    Data Analysis
    1a. Acute Changes in HRV
    (individual level)

    1b. Acute Changes in HRV (population level)
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    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
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    13. Training intensity & performance​
    14. Publication: VO2max & running performance
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    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
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    6d. Integration with Genetrainer
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    6e. Integration with Apple Health
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    ​6f. Integration with Todays Plan
    7. Acute HRV changes by sport
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    18. Aerobic efficiency and cardiac decoupling
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    Other
    1. HRV normal values​
    ​2. HRV normalization by HR
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    3. HRV 101

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