Heart rate and heart rate variability (HRV) data cannot unequivocally be translated into your recovery, stress, physical or mental strain, or anything else, really.
Our physiology unfortunately is not so trivial that you can measure it and get a clear outcome measure the way it is often advertised.
What’s the use then of heart rate and HRV data?
Heart rate and HRV, with the required context, can show you if your physiology is normal with respect to your own historical data (by definition, this should be the case most of the time), or if there are abnormalities that might require some extra caution (acutely, e.g. sickness or chronically, e.g. a period of higher mental stress).
That is all there is.
We cannot separate the mental and physical components of stress (and certainly, we cannot determine a state of 'flow', as recently advertised). We cannot even be certain that a change in a given direction (e.g. a reduction in heart rate and increase in HRV) is necessarily good (this specific state could be associated with fatigue) or bad, and we have no idea about how an acute change, when repeated, impacts us chronically.
This is true both for resting physiology measurements (e.g. first thing in the morning or during the night) and exercise data (e.g. your heart rate as you run or ride). For example, a suppression in heart rate in all of those contexts can be representative of fatigue, even though most people tend to think it’s a good thing as it is also associated with an improvement in fitness (when it happens over longer time scales).
When we consider data that was not collected according to best practices for assessment of resting physiology (i.e. data that was not collected first thing in the morning or during the night), we need to remember that physical movement remains by far the main factor behind changes in heart rate and its variability (which is why physiology should be measured at rest, far from stressors). It doesn’t matter if you are resting when you measure it. Even if you are working at the office, if you were active hours before, physical activity will lead to changes in your physiology that are much larger than changes due to mental / psychological stress, which is another reason why it is impossible to build a ‘stress monitor’ that actually reflect what most of us perceive as stress. Acute physiological stress due to exercise will override most other stressors, and most importantly, it is not bad, but it gets interpreted that way by wearables that can only provide overly simplistic interpretations.
I believe there can be value in looking at how physiology changes, when properly contextualized in relation to various stressors, environments, etc. - but this is only the case if we understand and accept the limitations: optical sensors are inaccurate, continuous data is often unrelated to stress responses (please read this if interested in the topic), and even when we measure according to best practices, the only honest interpretation we can derive is "normal vs abnormal data" (in a given context).
This motivates how we use the data in HRV4Training. For example, in the morning, after you have measured your resting physiology according to best practices, you can see your daily heart rate and HRV with respect to your normal range, so that you can determine if your physiology is normal in relation to your historical data, or not.
A suppression might indicate that you have not bounced back from current stressors, despite ~24 hours since the last measurement, and a night of sleep. Note how stress this way is assessed far from stressors, not right after, so that we can ensure that what we capture is your response, and not just the acute stressor itself (which is what happens when you look at data continuously, every minute, and sometimes even when you use night data, as discussed here). A suppression when we collect data according to this protocol might show us signs of sickness, a poor response to changes in the environment (altitude, the heat), or in training (higher volume or typically, higher intensity), and we can learn from that and make adjustments.
Similarly, exercise data, acutely, might show us that we are getting fatigued or struggling to adapt to different stressors (again, environmental, training-related, etc.), something you can analyze with the aerobic endurance feature in HRV4Training Pro. Chronically, it can show us how we are progressing, by comparing internal load (heart rate) with external load (power or pace), which is what our aerobic endurance analysis does.
Either way, it’s about a normal response vs an abnormal response, understanding that there are always day-to-day differences and that most changes in the data are actually irrelevant (yes, boring, and hard to accept for wearable devices that optimize for engagement, as opposed to usefulness) and then, adding as much context as possible (subjectively too), so that we can make use of the data effectively, for example improving our self-awareness and better balancing the various stressors we face, both in terms of training and also non-training related stressors.
If you have an interest or simply curiosity in looking at how your body is responding to training and various stressors, or how your physiology changes in different environments or in relation to different behaviors, keep track of your resting heart rate and HRV, as well as your exercise heart rate, together with the required context, and pay attention to abnormalities, i.e. deviations from your normal range or lack thereof. This way, you might be able to learn a few things about yourself, and make meaningful adjustments to your routines. Similarly, you can use this approach to keep track of progress or aerobic conditioning as you build up your training (e.g. what causes a suppression in HRV today, might not cause it tomorrow, as we bounce back quicker when we are fitter).
The better you balance stressors, the more boring the data (i.e. the fewer abnormalities or day-to-day changes).
However, keep in mind that often there are no obvious answers and that most devices out there are over-interpreting the data in ways that do not represent how physiology works.
Most importantly, use this data and devices as an addition to your subjective feel and perception, not as a replacement for them (ideally, look at the measured data only after you have assessed how you feel subjectively, the way we do with the morning questionnaire in HRV4Training).
Until next time.
Here you can find a few articles related to aspects I’ve discussed in this blog:
Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.
He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
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Hey Marco, really appreciate your post! I’ve been feeling very frustrated and confused with oura’s daytime stress data and am curious if you have any insights here. I’m a very fit human with 35-40 bpm rhr and 125 avg hrv at night. I have this pretty much every night. However during the day Oura registers so many of my data points as stressed. To me this makes me wonder if it tries to do it against my insane baseline metrics at night which I’ll obviously deviate from further than the average human from theirs. Something feels off there and I’m not really sure how to interpret it, I’m curious if you have opinions on this!
What is your opinion about Garmin's Body Battery and Coros Wellness Check? It is a reflection of all-day HRV? There is a reason to wear the Garmin device consistently?
Thank you!
Chris Papadopoulos