Not All HRV Data is Created Equal
Why measurement timing (morning vs night) and body position (sitting vs lying down) are crucial to use HRV effectively: a case study.
I recently discussed the importance of the orthostatic stressor when measuring HRV (here). This concept is central to why we strongly recommend taking HRV measurements in the morning rather than relying on nighttime data.
While the blog covered the science behind this protocol and provided a few pointers to studies investigating its effectiveness, it always helps to get a bit more concrete and look at a case study, which is what we’ll do today.
In particular, about ten days ago, I was “fortunate” enough to get a respiratory infection, which allowed me to collect data that highlights many of the aspects I’ve discussed in the past.
In particular, we’ll see data showing that:
HRV is a more sensitive marker of stress than heart rate, therefore making it worth it to go through the trouble of measuring HRV as opposed to just resting heart rate (I’d say, unfortunately! it is indeed be much easier to measure reliably resting heart rate, but there is more useful information in HRV data).
See this blog for a breakdown of the physiology of HRV and resting heart rate.
Data collected with optical sensing (e.g., with a wearable) in the presence of movement is extremely poor quality, to the point that even on a night of acute sickness (high fever), it can report incorrect HRV.
See this blog for more considerations about the (lack of) usefulness of HRV outside of very controlled settings and protocols.
Measurement timing matters, and measuring HRV too close to a stressor (e.g., even just dinner when using a night measurement) leads to data that is not effective in capturing your baseline stress response - and that’s what we want to capture. When measuring in the night, we are just looking at things acutely and losing perspective on how the body is doing in relation to training and other underlying stressors (e.g., even sickness). The best moment to measure your response, in my opinion, is in the morning, when enough time has passed from previous stressors, and after the restorative effect of sleep.
See this blog for more considerations and examples in the context of measurement timing.
Measurement position matters: sitting up before measuring, i.e., exploiting the orthostatic stressor, allows you to capture subtle changes that are not present in data collected while lying down (i.e., during sleep). Sometimes, you need to stress the body to be able to capture any potential issue in how it responds to stress. Measuring in a condition of full rest (i.e., while asleep) cannot provide this information.
See this blog to learn more about the orthostatic stressor.
Let’s get to it, then. Below is my data for these past ten days. We can start with HRV data (in the figures, I am using showing, with its normal range and baseline, and provided by HRV4Training Pro).
The top plot is my morning HRV data, collected with HRV4Training first thing in the morning (iPhone, phone camera, 60 seconds). When I wake up, I normally go to the bathroom, then back to the living room. I lie down on a couch for less than a minute, then I sit up, and shortly after, I take a measurement while seated (this is what the orthostatic stressor is all about). The bottom plot is my night HRV data:
I have annotated the plot to make it easier to spot the relevant events, but here is also a breakdown:
March 29th - April 1st:
Event: Bronchitis.
Morning data: the orthostatic stressor used in the morning protocol makes it more sensitive to detect early signs of illness (bronchitis symptoms without fever), showing a sustained suppression for several days.
Night data: there is no change in HRV data: measuring in a condition of full rest is not sensitive enough to capture the stressor.
Night of April 1st:
Event: Acute sickness, fever, hospital visit.
Morning data: a significant decrease in HRV the morning after the hospital trip clearly indicates acute illness (probably an all-time low for me, with an rMSSD of 12 milliseconds).
Night data: we have high HRV at night due to poor-quality data (artifacts in HRV, like movement or even ectopic beats and very common - unharmful - arrhythmias, can only lead to higher HRV, due to the disruption in the natural oscillations between consecutive heartbeats). Optical sensors cannot be trusted outside of conditions of complete inactivity (not even typing!).
April 4th - April 8th:
Event: Recoverying.
Morning HRV: gradually returns toward normal values.
Night HRV: no meaningful changes were detected. See the next graph (heart rate) to understand why.
And now the resting heart rate data:
Here, resting heart rate shows no significant changes during initial illness, highlighting its lower sensitivity compared to HRV, even for morning measurements.
Even more interestingly, the nighttime resting heart rate data lacks any meaningful relationship to physiological stress or recovery. Why? Due to my heavily periodized nutrition strategy (all the details here), my nighttime resting heart rate has essentially become a "macronutrient-content meter," increasing notably when carbohydrate intake is high. This makes nighttime data of limited value when assessing underlying stress—precisely the actionable information needed to guide meaningful adjustments and enhance long-term performance. Make sure not to confuse acute and chronic changes, or you’ll end up avoiding (or worrying about) all stress - far from an effective strategy.
I hope this case study makes things a bit more concrete when it comes to why we recommend a morning measurement as opposed to more trendy alternatives.
For the data to lead to insights, protocols matter.
Thank you for reading, and all the best for your health and training!
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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 is a certified ultrarunning coach.
Marco has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, Endurance Coach at Destination Unknown, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine.
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Hello, I am new to HRV tracking. I have downloaded the HRV4training app and I was wondering if any wearable would be compatible with it fir morning HRV measurements. Which ones do you recommend, I am buying a Polar H10 for tracking HR during exercise, will that be OK? Thank you.