If you have any questions, comments, or inquiries, please contact Fuminori here. This work was partially supported by the research grant from Japanese Society for Running. Profile of Asuka TanakaBorn in 1989 in Fukuoka, Japan. His career as a long-distance runner began in junior high school. He had competed in several famous Japanese University Ekiden races (e.g., Hakone Ekiden). After a career in several corporate running teams, he is currently working as a professional runner, aiming to compete in the Paris Olympics. His personal record for a full marathon is 2:10:13. Twitter: @asuka8675 Data collectionThe data shown below was collected with an Oura ring, hence it is night HRV, and then read in HRV4Training and analyzed in HRV4Training Pro in the long term. Heart rate variability during the past seasonBelow we can see some valuable data about Asuka Tanaka from May to November 2022. He is a Japanese professional runner with a marathon personal record of 2:10:13. He is currently running independently, not on a corporate running team— typical of professional runners in Japan. As shown in box 1, he broke his 5000 meters personal record for the first time in 10 years in July (14:12 → 14:08). He conducted high-intensity training (e.g., VO2max interval and temp running) twice a week and did one or two easy runs on other days from April to July. In addition to these running training programs, he introduced heavy-weight strength training. The strength training session was typically held twice weekly. However, the frequency was changed to once per week if both the HRV (usually decreased) and subjective fatigue were high. The S&C coach thought that these approaches may contribute to a stable HRV (not increased HRV) and thus his superior performance. Now let's look at the second box. He held a high-altitude training camp to train at a high intensity while avoiding the scorching heat in Japan. The HRV tended to drop during this camp (but did not deviate from the normal range), which can be an expected acute response. Next up is the third box. As you can see, the HRV in September was on the rise. However, this does not appear to be a good trend for several reasons. First, the value deviated from the normal range. An increase in HRV typically indicates a positive adaptation of training. However, an increase above the normal range is an exception. Second, the increased trends in summer would be observed regardless of whether performance and conditions are good or bad. In fact, a similar case was observed in other elite Japanese endurance athletes. Finally, his training during this period did not go smoothly. Therefore, both the runner and the S&C coach did not perceive this period as "coping well". In the final box, number 4, we can see that Asuka got sick after working as a 30-km race pacemaker. Eventually, sickness has had a big impact on his training and marathon-race plans for this season. However, because he suffered from several orthopedic problems in his lower extremities, this period offered an opportunity for physical and mental recovery. In fact, the figure shows that the HRV went back to the normal range in this phase. Fortunately, he could recover from the sickness and resume training little by little. His current aim is to get a seat for the Qualifying Championship for the Paris Olympics in Japan. For elite runners, it is difficult to judge the boundary between training loads leading to improved performance and overdoing that load to injury or overtraining.
A runner’s condition is also affected by various factors other than training. Regularly reviewing HRV, training status, subjective feeling, daily life events, etc. is important to optimize the condition of all runners. 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 |