Case study: physiological stress in response to training (running a marathon) and lifestyle1/17/2020
Blog post by Marco Altini Physiological stress comes from different sources, all having an impact on our ability to deal with additional stress and therefore of maintaining or improving our health and performance. In this post we'll see an example of how a morning measurement of your physiology taken with HRV4Training using the phone's camera, can be a very effective way to capture changes in physiological stress in response to such training and lifestyle stressors. We will also see how the visualizations and analytics available in HRV4Training Pro make it really easy to identify periods of higher stress. In particular, we can see in the image two large drops below normal values, highlighting significant stress on the body:
Between the two major stressors, I kept training hard (after about a week of recovery from the marathon), and responded very well as you can see from the stable or increasing HRV during most of November and December. A stable HRV (within your normal values), is typically a good sign, indicating a positive response, especially when increasing training load: The data above is my own, but we can see a very similar physiological response in Alessandra's data: In her case the second drop is even larger, which is linked to the fact that multiple stressors piled up (getting a cold for a few days and the menstrual cycle), see for example the annotations here for sick days: Finally, here we can see HRV4Training's trends analysis at work. In this analysis we combine various parameters (heart rate variability, the coefficient of variation, resting heart rate and training load), to automatically determine individual responses in the medium term. We can see how the analysis is able to detects periods in which we were not coping well with the various stressors, which can be useful information to make a few adjustments (e.g. avoid high intensity workouts which might put you in a even worse situation, physiologically speaking, and therefore further delaying recovery and potentially compromising performance, or simply give priority to good sleep): Physiological stress comes from different sources, all having an impact on our ability to deal with additional stress and therefore of maintaining or improving our health and performance.
In this post we have seen how stress can be captured easily with a morning measurement taken in a standard context (as soon as you wake up, while still lying in bed, in just 60 seconds), using your phone camera. As the data clearly shows, this is all that is required to capture changes in stress in response to both training and lifestyle stressors, as well as positive adaptation to increased training load. Take it easy. 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 |