You’ve got a new wearable and it reports your HRV.
You see the number and wonder, is this any good?
What does it mean when it changes?
In this short blog, I address these questions and give you a few pointers to better understand and (most importantly) use this metric.
Let’s start by discussing the number you see, or what we can call the absolute value of HRV (i.e. looking at the number for what it is, not in relation to your previous data or any stressor).
In terms of absolute values, HRV has a strong genetic component (i.e. there is only so much we can do to modify it), and while it is true that there are some associations with health outcomes, no causality is typically proven.
This means that the absolute value itself is not particularly informative. This is important to say because we are prone to putting much weight on absolute values (e.g. VO2max) but this approach might not be particularly useful or effective when it comes to HRV.
We could say that anything between 10 ms and 200 ms could be considered normal in terms of HRV (i.e. basically the entire range of values), even though most middle-aged people will be somewhere between 20 and 50 ms. While age is one of the main factors driving between-individual differences, there is so much overlap between age groups that given an HRV value, you can never tell the age of the individual (it is a weak relationship).
Hopefully, I’ve persuaded you not to focus too much on the absolute value, but if you’d like to learn more and look at some data, check out these blog posts:
How do we use HRV then, if we don’t care much about its absolute value?
If it's not absolute values, it's relative changes over time.
HRV is a marker of the stress response, hence it can help us track how our body is responding to stressors. One important aspect here is that what we look at when measuring at the right time (ideally, the morning, but the night is also fine typically, with differences that I discuss here), is not stress but the stress response.
That means that if your HRV is normal the morning after a hard workout, it doesn't mean that the workout wasn't stressful, but it means that you bounced back quickly from that stressor. Following this line of thought, a good response means that your HRV stays within your normal range, and therefore a good response is typically a stable HRV.
For example, good athletes tend to have a very stable HRV as they are used to high training loads for many years and the body can deal with it well. Sometimes in these cases, the data becomes more interesting with unexpected or non-training related stressors, e.g. travel, psychological stressors, family / work related concerns, etc. - as our capacity to handle stress is limited, changes in our stress response due to non-training related stressors can help us make meaningful adjustments at times, such as modulating training intensity or prioritizing other recovery strategies whenever possible.
The tools I build, like HRV4Training, focus on these principles: you are in control of your measurement (i.e. you measure intentionally, in the morning) and can easily see when your daily HRV (and resting heart rate) is within your individual normal range (based on your historical data), or not. A suppression might highlight a poor response to a recent stressor, and prompt some adjustments for the day ahead.
See also:
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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Twitter: @altini_marco (currently inactive)
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