Discover more from Marco Altini’s Substack
Heart Rate Variability (HRV) measurement timing: morning or night?
a look at stressor timing and measurement position
In this blog, I would like to highlight two key aspects to consider when deciding which measurement protocol or device to use for heart rate variability (HRV) measurement.
In particular, both measurement protocols provide us with useful data to track long-term changes in physiological stress as it relates to training and health. However, there are differences.
For example, night measurements happen earlier, and therefore tend to be more tightly coupled with our behavior the previous night. On the other hand, morning measurements are more tightly coupled to our readiness for the day, as they happen after the restorative effect of sleep, and farther away from the previous day’s stressors. Similarly, orthostatic measurements (sitting or standing) are often recommended for HRV measurement but are unfeasible when measuring in the night.
Thus, in this blog, I’d like to discuss in more detail stressor timing and measurement position, since both these aspects impact the data’s sensitivity to stressors and its interpretation or actionability.
Let’s get to it then.
Thanks for reading my Substack! Subscribe for free to receive new posts and support my work.
We measure HRV because it is a marker of the body’s response to stress. If we want to capture such a response in a meaningful and actionable way, we need to measure it in a reproducible context, at rest, far from other transitory stressors that would confound the measurement. Typically, this means in the morning or the night.
Measuring right after a stressor would be less informative: we would have a suppression in HRV, or increase in HR (e.g. after exercise), and that would be normal. What we are interested in is not this immediate change, but how our system responded to that stressor, which can be better determined by measuring at rest, hours after the stressor (again, in the morning or the night). Failing to bounce back to normal from the stressors, for example, highlights a negative stress response, or the presence of additional stressors (e.g. lifestyle related).
If we experience late stressors (evening workouts, a large dinner, alcohol intake, etc.), this might impact our night data to a greater extent. The night comes first, and therefore our HRV is suppressed even if we might have bounced back by the morning. Wearables are convenient, and heavily marketed, but night data might in fact miss the point when it comes to morning readiness, due to measurement timing, especially if you work out in the afternoon or evening.
Analyzing a response to a workout at different time points (night, and then morning) simply shows how physiology gradually returns to normal, but this has implications for the interpretation and guidance provided.
Example: stressor timing
Below you can see an example of data I collected in the night after large stressors: a hard, long run in the heat, followed by a late dinner. We can see that HRV increases a bit overnight, and resting heart rate reduces, as expected (the typical post-stressor rebound):
In the first half of the night, we have:
HRV = 61 ms
heart rate = 49 bpm
In the second half of the night, we have:
HRV = 69 ms
heart rate = 44 bpm
Normally, I read the night averages in the HRV4Training app, which can then interpret them with respect to my historical data and normal range. Similarly, I use another HRV4Training app to measure first thing in the morning, while sitting, and also compare with respect to my historical data. Below you can see two screenshots of the apps using night data (left) and morning data (right), on the same days.
We can see that for the data collected in the night HRV is suppressed (left picture below, Oura ring night data), while HRV is back within normal range by the morning (right picture, measured while sitting using HRV4Training, phone camera), consistently with what we saw above, looking in more detail at the data during the entire night.
This shows how in the second part of the night physiology is back within normal range, just like in the morning, but we are somewhat penalized when using night data since the measurement is done earlier.
There is no right or wrong here (it’s just physiology!), but the data differs due to stressors and measurement timing, and we need to be aware of these aspects if we want to use the data for guidance or to interpret the body’s response to stress. Looking at this data, I believe I had a positive response (morning data within normal range despite large training stress), but night data might make you think otherwise.
Possibly the biggest difference between morning and night measurement is that in morning measurement, we can measure in different positions (lying down, sitting, or standing), while during the night, this is unlikely to happen.
Why is measurement position important? I have recently changed my mind about this after several conversations with a trusted expert in the field (Andrew Flatt), self-experimentation in different positions over an entire year (so that I could look at the relationship between the data and various acute and chronic stressors) as well as reading the available literature.
As Andrew explains, when lying down, HRV represents cardiac autonomic nervous system activity during undisturbed rest. On the other hand, sitting or standing HRV represents cardiac autonomic nervous system activity in response to physiological stress (orthostasis) with a strong influence from the baroreflex. The physiological challenge exacerbates your response so that if something is off (there is more stress, sickness, or anything else), there will be a much larger change in HRV (and resting heart rate) with respect to the change you would see if you are lying down (sleeping or in the morning).
Thus, an orthostatic stressor, which here means measuring while sitting or standing, makes it so that HRV becomes more sensitive to the stressors you are facing, and therefore more useful. This is why I now recommend measuring while sitting. For more details on these mechanisms, please check out Andrew’s great blog here.
Measuring while sitting or standing can be particularly beneficial if your heart rate is low, e.g. low 50s or lower, since parasympathetic activity is already high. Measuring while sitting or standing, you might also be less prone to another rare issue of measurements taken lying down, parasympathetic saturation (a situation in which your HRV measurement does not reflect parasympathetic activity, basically your HRV would be suppressed despite actual parasympathetic activity being elevated). This is particularly true if your training volume is high.
Personally, I now measure while sitting, and therefore can only do this first thing in the morning, as opposed to during the night.
Example: measurement position
Below is an example showing acute sickness, and how the orthostatic stressor (i.e. sitting in the morning for a measurement) captured very well the acute phase, possibly with an early warning, as well as the recovery phase, while night data failed to capture the recovery phase, and shows a change only during acute sickness (one day).
This is perfectly in line with what we expect: when we have a very large stressor, like the first day of acute sickness, our physiology is altered the entire day or night, and we can easily capture it. As I start feeling better, the following days, measuring in a highly parasympathetic state (while sleeping) provides no useful information, heart rate is only 1 or 2 bpm from where it was before the sickness.
On the other hand, adding a little stressor before a morning measurement (just sitting up), amplifies my response, and I can see very clearly how I am progressing towards renormalization. Despite my heart rate during the night being 50 bpm or 49 bpm every night, as soon as I sit up and measure, I have a marked difference in the response: the second day is 63 bpm, then 57 bpm, and then 54 bpm, clearly capturing my recovery from sickness. This is the orthostatic stressor at work.
What does the research say?
Early research comparing morning and night data is in line with what I have discussed in this blog.
In particular, Christina Mishica and co-authors looked at the correlation between night and morning data and found that “heart rate and RMSSD obtained during nocturnal sleep and in the morning did not differ” (see “Evaluation of nocturnal vs. morning measures of heart rate indices in young athletes”). This is expected when we look at the data at the group level, meaning that if a person has a relatively low HRV, it tends to be low both in the morning and during the night.
However, the analysis above does not look at how data changes in response to stressors, for example how morning and night data respond differently to a workout, something I’ve discussed above. A new article by Olli-Pekka Nuuttila and co-authors tries to address this issue, looking at how HRV collected in the morning and during the night relates to prior stressors. The authors report:
“It could be argued that the morning .. being further away from previous stressors and closer to the following, would provide more relevant information on the current state of homeostasis”
“Furthermore, it can be speculated that nocturnal recordings would rather reflect the physiological and psychological load of the previous day than the actual state of recovery and readiness to perform on the following day”
Stressor timing matters, and in the context of training, morning data might better represent your recovery and ability to assimilate additional stress on a given day.
The whole point of using HRV is to try to capture the body’s response to training or other stressors. Both morning and night data can capture similar long-term trends in our physiology (when measured using validated tools, and following best practices). However, there are some differences.
Night HRV can be very useful to better understand aspects of your behavior: eating habits, alcohol intake, weight loss, and exercise timing, for example. Similarly to morning measurements, night data can also track very well anything health-related (acute sickness). However, quite possibly, measuring after the restorative effect of sleep is a better time to assess your state and readiness for a new day. Measuring closer to the previous day’s stressors, we might not capture the response effectively (how we recovered after e.g. 10–15 hours, before the next workout).
Additionally, the high parasympathetic state during sleep might make the data less sensitive to stressors. Measuring while sitting adds a little orthostatic stressor that can make the data more representative of our capacity to assimilate additional stress on a given day.
Needless to say, there are practical considerations too, in terms of cost and compliance for example, which might motivate picking one method over the other. All good as long as we understand what we are doing beyond marketing claims :)
I hope this was informative, and thank you for reading!
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.