We have released a new integration in HRV4Training, which allows you to read sleep data and whole night HR and HRV from your Oura ring (or more specifically, from Oura Cloud). How does it work?To setup the integration, go to Menu / Settings in your iPhone or Android device, and scroll down until you see the Link to Oura entry. After you have authorized Oura, we will set up the connection to automatically read wakeup time, bedtime and sleep quality. Additionally, you will be able to also read resting heart rate and HRV using the ring's data instead of the morning measurement (more on this later). No data foundOnce you have linked Oura and set the parameters you'd like to read, we will read the data when you take the measurement or in case you read also HRV from Oura, when you tap the Read from Oura button (which will replace the 'Measure HRV button"). Make sure to have your data in Oura Cloud, before using HRV4Training. Note that you might have synched your ring and app, and have the data in the app, but that is not sufficient as we read from Oura Cloud, hence you need to make sure to have the data there, or we won't be able to access it. Here is how to get your data to Oura Cloud from your Oura app: how to. Reading HRV from OuraIn case you prefer to use your night data instead of taking the morning measurement, you can do so by enabling the Heart rate and HRV check box in the Oura Settings in HRV4Training. In this case you can also read data later on during the day instead of right when you wake up, as we will be using your night's average heart rate and HRV to determine Recovery Points and other metrics in our app, but there are some caveats to consider (see next section). Morning measurements vs night measurementsMorning measurements have been used for a long time in the context of tracking chronic physiological stress in response to training and lifestyle stressors. On the other hand, mainly because of the difficulties in acquiring such data, night data has been used a little less. This being said, as scientists have been active in this field for decades, you can find several papers looking at the relation between nocturnal HRV and training load, for example here, or here, similarly to what we have shown for morning measurements here. In our recent overview of HRV in team sports we covered studies that collected data both in the morning and in the night, you can read it here. In our opinion, there is little doubt that night HRV is reflective of physiological stress, similarly to morning measurements, and therefore we believe both approaches are valid in terms of acquiring data representative of chronic stress and helping you making sense of the data over time. It is of course key that the sensor used to measure night data is reliable, and this is the case for Oura, which shows extremely good agreement with ECG in this validation where rMSSD was computed from night recordings. However, while both methods are able to capture changes in physiology relative to your baseline and normal values over time, the absolute values will most likely differ. What does this mean? Simply put, that you cannot interchangebly use one method or the other, but you have to stick to one, either morning measurements or night measurements, and then use always the same method so that data can be analyzed meaningfully over time. Here is an example of our data showing for example two dips due to a marathon and a few days slacking off around new year's, plus getting sick: We can see:
Similarly, in HRV4Training (data, in this case, was collected first thing in the morning using the phone camera) we can clearly see the two dips in HRV below normal values after the marathon — November 3rd and around new year's, as well as a stable HRV between the two events): In HRV4Training we have a few added benefits that make it easier to analyze the data:
Hopefully the figures above make it quite clear that physiology needs to be contextualized (both in terms of external factors, such as training, traveling etc. - and in terms of what changes are significant, as shown by the normal values band), otherwise it is hard to derive meaningful insights. Recommended configurationGiven what is discussed above, we recommend taking the measurement in the morning as you normally do, and use the ring mainly to track sleep. If you decide to use the ring also for your HRV data, just keep in mind that you might need to acquire a new baseline and new normal values, which can take up to 2 months. In this case it might be simpler to start over by creating a new account. SummaryIn this post we highlighted our latest integration. In this case more than ever, we decided to move forward due to the overwhelming feedback received by our community. Thank you everyone for taking the time to provide your input and appreciation for how we analyze and interpret the data in HRV4Training. It is our belief that helping you making sense of the data is what we do best here, and therefore we are happy to expand the set of compatible devices for the ones that prefer to collect data passively in the night. Enjoy. Look at the big picture by easily analyzing your recent trend with respect to your hsitorical data. Try HRV4Training Pro at HRV4T.com
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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 |