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Oura ring integration: read sleep data, whole night heart rate and HRV in HRV4Training

3/27/2019

 
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.
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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).
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Once 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 Oura

In 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).
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Morning measurements vs night measurements

Morning 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:
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We can see:
  • a few low days at the beginning of the recording (around the marathon, and post marathon, some data here is missing)
  • a stable or increasing HRV in the middle part of the plot, with a dip for a single day
  • a few days with lower values again around new year's eve (towards the end of the plot)

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):
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In HRV4Training we have a few added benefits that make it easier to analyze the data:
  • The normal values range (horizontal band), shows what changes in physiology are significant and what changes are just normal day to day variations, hence here it is easier to identify the two big dips happening with the marathon and around new year's eve. Learn more about normal values here.
  • The possibility to highlight different aspects that you can log (menstrual cycle, sick days, traveling - which can be automatically tracked - etc.), as shown by the smaller color-coded figures above.
  • ​Here we also have the added benefit of HRV4Training's trend analysis, which looks at HRV, HR, coefficient of variation and training load to determine how you are responding to your current training block, and indeed highlights maladaptation and accumulated fatigue, in the second case even before HRV ends up below normal values.

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 configuration

Given 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.

Summary

In 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.
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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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    This blog is curated by
    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
    2​b. 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

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