Blog post by Marco Altini.
In the past few months we've been introducing different features under the Insights section of HRV4Training, aiming at providing more systematic and practical analysis of the relation between physiological parameters and training as well as more freedom to explore your own data, beyond the daily advice provided in the home screen. In particular, we currently provide the three following Insights:
In this post we cover the latest changes that are coming to the app in the next few weeks.
Acute HR(V) Changes
The Acute HRV Changes analysis used to provide insights on the change in Recovery Points following training days, and also a breakdown by training intensity.
From the next version of HRV4Training, you will be able to pick different physiological metrics (e.g. heart rate, rMSSD) and analyze how they change with respect to training. Typically, we expect small changes in HR, with increases in HR on days following intense training in the order of a few beats, as well as reductions in HRV (rMSSD or Recovery Points) on days following intense trainings. See below for an example: The same functionality is also available in HRV4Training Coach, and you can run it on all your athletes, if you are a user of the Coach platform: This analysis is one of the easiest and more practical ways to benefit from HRV analysis and analyze systematically day to day variations to better understand if we can use HRV to guide training in the long term. We are also excited to announce that we've been performing such acute HRV changes analysis on a dataset of almost 800 HRV4Training users that recorded data for periods of 3 weeks to 5 months, and recently submitted a paper highlighting our findings (to the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society): We will discuss the results of this paper later on when it is published. However, reductions in HRV and increases in HR on days following more intense trainings, with respect to rest or easy trainings, were detected consistently on a large population, regardless of age group and gender, indirectly validating the effectiveness of tools like HRV4Training in capturing training load information in unconstrained free-living settings. You can perform the same analysis inside the app when you have more than 40 days of data. Ideally, 3 months of data are required. As usual, remember that your physiological data (HR/HRV) is affected by many parameters, and if your lifestyle is very stressful (much traveling, or other major sources of stress), you might not be able to see the relations explained above. Here are a few useful suggestions if you see unexpected results. HRV Trends
We made limited changes to the HRV Trends page, mainly to provide more flexibility around the training load plot. You can now choose between Distance, TSS, training intensity and RPE as metric to be displayed. We also smoothed out a bit the baselines (they are still 7 days moving averages):
The HRV trends feature is one of the most experimental. Currently, we are trying to determine your physical activity condition trend based on common multi-parameter trends highlighted in state of the art research up to date. However, our goal is to use HRV4Training data and your own self-reported physical condition to develop new models able to determine with higher accuracy at the individual level what is your current physical condition. As you collect more data and provide insights on your perceived physical condition, we will be updating these models to learn from your past data and hopefully provide more accurate results. Correlations and Tags
A few weeks ago we introduced a complete redesign of our Tags, providing much more flexibility. You can now pick only the Tags you are interested in, and most importantly you can create your own custom Tags (up to 3 numerical variables).
Here is an example of how I used the custom tags to track sleep quality as measured by Beddit. First, you need to go in "Configure TAGS" that you can find either right after the measurement or in Settings. Then you can enter whatever name for your variable, and at that point it will be shown every time you fill in your Tags after the measurement: You can use any numerical variable. From the next version of HRV4Training, you will be able to select your custom Tags for the correlation analysis as well. Additionally, the app will now remember your last choice of parameters, and load them by default when you open the Correlations page: As you can see we can now select custom Tags (e.g. beddit score). However I haven't used my Beddit for long enough to look at correlations, since a minimum of 20 measurements are required. I'll have to do with subjective sleep quality for now ;) What's next in HRV4Training
This is all for now on the Insights. The next updates will focus on providing more flexibility for triathletes and everyone doing more than one sport, with History icons that differ based on the sport performed and the possibility to tag double trainings in a single day. Stay tuned.
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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 |