Blog post by Marco Altini.
In the last post I covered HRV measurement duration, and pointed out that very short HRV measurements are as good as 5 minutes recordings, when looking at rMSSD. Similar results were also shown in a recent study by Michael Esco and Andrew Flatt, which I partially replicated.
Other important aspects, beyond the duration of the measurement, are when to take the measurement, paced breathing, frequency (how often?) and type (lying, standing or orthostatic). In this post, I will cover measurement type.
When I built HRV4Training, I wanted to create a flexible tool that could allow users to configure the app according to their preferences. This is the main reason behind the different settings (1 to 5 minutes duration, single or orthostatic test, export of all HRV features, etc.). However, I've been asked many times a couple of questions, mainly related to test type; should I do orthostatic tests? What is the difference? Can I better understand my recovery using orthostatic tests?
In this post I will be looking at user generated data (more specifically this dataset of HRV4Training users) and try to answer some of these questions.
Background on orthostatic measurements
In HRV literature it's very common to come across studies where orthostatic tests are used to perform measurements, instead of measurements at rest while lying down. However, the terminology is used to indicate different types of measurement protocols, and it is important to understand how these protocols are performed and what kind of measurements are we talking about in this post. The two most common protocols for orthostatic measurements are the following:
For both protocols the duration of each phase is typically 3 to 5 minutes, with 15 seconds between the two phases in which data is discarded. HRV4Training users perform the second test, without a tilt table, since anyone can do it at home. The test duration is often shorter, as short as 1 minute. The second version of the measurement protocol is also what is typically provided in other commercial devices (see for example Polar's website for some more information on how they do it).
At this point we should be clear on how the test works. The next question is, what does it tell me? The principle behind orthostatic measurements is clearly explained at this link. Simplifying a bit, your HR during the standing phase should have more trouble staying low, if you are overtrained.
Interestingly, there is not that much research backing up this assumption. In my previous analysis I showed that HRV is able to distinguish between easy and intense training days, and is a valid tool to measure recovery, more than HR. However, if you look at this data showing the difference in HR the day after an easy and an intense training:
we can clearly see that there is a difference in HR, which is - as expected -, higher after intense training. So is the HR while standing going to be much higher and therefore the difference between standing and lying HR will be higher as well after intense training? Or is the HR increase after intense training during lying and standing comparable, and therefore the difference in HR between lying and standing is pretty much the same after easy and intense exercise? I think these considerations have no obvious answers, and probably different people have different physiological responses. However, by looking at the data we can try to understand what works best to determine training load and recovery.
Recently I read an interesting thesis where the author investigated the relation between different stressors and HRV. The goal was to understand what HRV features can better discriminate between physical and psychological stress (stressors were as extreme as running marathons or sky diving). One of the "light" stressors was an orthostatic measurement, performed the same way we are considering in this analysis (i.e. lying down, and then standing up without tilt table). However, the test was unable to discriminate between overtrained athletes and controls, something that instead clearly showed up in HRV recordings at rest. It is therefore even more worth investigating if orthostatic measurements are reliable to assess training load and recovery.
In a previous post, I validated the assumption that HRV data can be used to monitor recovery by looking at how training intensity was affecting HRV measurements on the following day. For this analysis, I will do something similar. First, I will select only users using orthostatic measurements, then, I will look at how both the lying and standing part of the orthostatic measurement are affected by training intensity. Since a major point from previous literature is also the reduction in the difference in HR between lying and standing after intense exercise (see Rusko), I will also look at how this data changes with respect to training intensity.
For this analysis I first filtered out all HRV4Training users that do not perform orthostatic measurements. This leaves me with a small percentage of users (about 5%). Then, I performed some additional filtering to make sure I have reliable data, after all these are measurements taken "in the wild", without any supervision. Therefore, I kept 1) users with more then 10 measurements, 2) HR values between 30 and 120, 3) rMSSD values between 10 and 180, 4) percentage of RR intervals discarded when using the Camera to acquire data below 15%, 5) measurements taken between 6 and 10 am.
I ended up with 2098 measurements, from 30 users, so about 70 measurements per users. Taken longitudinally, this means that the average user in this dataset used the app for more than 2 months. This data is already more than what we can find in most HRV studies, and therefore should be sufficient to get more clarity on orthostatic measurements.
Let's first have a look at HR and HRV (rMSSD) values during the two phases of the orthostatic measurement, for all users. Here I am plotting boxplots to show the distribution of the data:
The behavior is pretty much what we would expect (click to enlarge). For the HR data, we have consistently higher HR while standing, compared to lying. For the rMSSD data, we have consistently reduced rMSSD while standing, compared to lying.
Now let's move to the most interesting part of this analysis. How do HR and rMSSD during orthostatic measurements relate to training intensity?
To answer the question, I computed changes in HR and HRV for days following easy and intense trainings. Looking at days after the training days allows us to determine the impact of training intensity on HR and HRV. Additionally, since we are considering changes in HR or HRV on consecutive days (depending on training intensity), all measures are relative. Thus, since we are not looking at absolute HR or HRV values, we already get rid of the problem of having different baselines in different users, and only look at how physiology changes with respect to training intensity within a user. Training intensities were manually annotated by the users.
Heart rate during orthostatic measurements in relation to training intensity
Let's start by looking at HR changes for the different phases of the orthostatic measurements, as well as for the difference between standing and lying HR (i.e. the orthostatic HR).
What can we see in these plots? Similarly to what I've shown on a bigger dataset including all users, when we look at HR changes in days after easy and intense trainings, HR does change, but the change is not statistically significant. I am not really a big fan of statistical significance, and from the lying and standing plots (first two) we can see there is an increase in HR following intense trainings in comparison to easy trainings. However, this change is relatively small, and therefore it might be difficult to understand when recovery is needed, using only HR. Lying and standing provide pretty much the same results, showing that both measurements types are valid. However, when we look at the change in HR between lying and standing (third plot), we really see no difference between days following easy trainings and days following intense trainings.
Here are some numbers:
- after an intense training, HR is on average increased by 1.4 beats per minute (higher HR means more training load)
- after an intense training, HR is on average increased by 1.6 beats per minute (higher HR means more training load)
Thus, standing seems to make it easier to capture the difference between the two conditions. In general, the differences in HR on consecutive days are rather small, going up to 2% maximum, depending on training intensity.
What about changes in HRV? We've seen in the past that HRV seems to be more sensitive to training intensity, and therefore it's easier to monitor training load and recovery using HRV compared to HR.
Heart rate variability during orthostatic measurements in relation to training intensity
Similarly to what I've shown in the plots above, I computed the difference in HRV (rMSSD) in days following easy and intense trainings, our reference points. I've done the same also for the difference in HRV between the two conditions of the orthostatic test, as shown in the third plot.
Again, we can see consistent reductions in HRV after intense trainings compared to easy trainings (click to enlarge). This time, the difference in HRV reaches statistical significance. However, when we look at changes within participants between the standing and lying state, as shown in the third plot, we still have nothing. While the two single phases of the orthostatic test are both able to capture the effect of training intensity, when we look at the difference between the physiological values in the two conditions, values are all over the place and do not seem to be indicative of training load.
Here are some numbers:
- after an intense training, rMSSD is on average reduced by 4.8 ms (lower rMSSD means more training load)
- after an intense training, rMSSD is on average increased by 3.2 ms (lower rMSSD means more training load)
On the contrary to what I've just reported for HR, when looking at HRV (rMSSD) lying down seems to make it easier to capture the difference between the two conditions. In general, the differences in HRV on consecutive days are bigger than for HR, going up to 14% depending on training intensity. Therefore HRV is a better marker of training load and recovery, as I already pointed out in previous posts.
What next? Are orthostatic measurements useless or can we still benefit from the additional time spent, to get an even better understanding of training load compared to what we obtain already with single HRV measurements?
Taking it a step further
We've seen that the difference in either HR or HRV is not representative of training intensity, according to this dataset. However, both rest and standing measurements triggered physiological responses that allowed us to capture the difference between training intensities, as known from literature. Obviously, these two factors are related. Since both phases of the test can capture training load, taking the difference cancels out the effect of training.
At this point a natural follow up is to try to determine if the two measurements (lying and standing) can still be used together to discriminate between training intensities and therefore monitor recovery, helping us optimizing training. While the difference between standing and lying HR or HRV was pretty much the same after easy and intense trainings, we could come up with a new metric.
For example, we could compute the HR (or HRV) difference on a day following easy or intense training as the sum of the HR (or HRV) change while lying and standing with respect to the day before. Let's clarify this with an example. If your HR after intense exercise is 2 bpm higher than the day before while lying, and 3 bpm higher than the day before while standing, your overall difference for that day would be 5 bpm (instead as 1 bpm, as it is currently done when we take the difference between standing and lying). In this way we always take into account relative differences between days, instead of absolute values, and we "accumulate numbers representative of fatigue and training load", such as HR (HRV) changes in the day after training, in contrast to determining the difference between HR (HRV) values between lying and standing, since both lying and standing might be affected by training intensity, and therefore the difference might cancel out the information we want to capture.
Let's have a look at some plots:
In both cases there is a clear outlier, but we can see consistent differences in HR and HRV. Again, HR differences don't reach statistical significance, while HRV differences do. Changes in rMSSD combined between the two phases, i.e. reduction in HRV in days following training when measured while lying summed to reduction in HRV in days following training when measured while standing, show marked differences between easy and intense training days. Thus, monitoring relative changes seems to be a better idea than just looking at the difference in HR or HRV between the two phases of the orthostatic measurement within a person.
Let's have a look at some data for one user, to better understand changes in HR and HRV following training days of different intensities, and how this data can be representative of training load:
The plots above show a user's data (rMSSD and HR) during the lying phase of the orthostatic measurement. We can see from the first plot that HRV after intense training, i.e. the blue bar immediately following a green one, is consistently much lower than the day before. This means that HRV is able to capture training load and shows that the body needs recovery after intense exercise. We can also see how easy trainings are followed by higher HRV values (even though we have very few data points).
When looking at the HR plot, things are less clear. There is much less variation over time, as I've covered before changes in HR are about 2% max, while for HRV they are much bigger. Not all intense trainings are followed by higher HR the day after (remember the relation between HR, HRV and training intensity is inverse, so after intense training we expect lower HRV and higher HR).
Now let's look at the second phase of the orthostatic measurement, the standing phase:
Results are very similar to what we had before, no surprise. Also, HRV is much lower than while lying, while HR is much higher. Also here no surprise. However, for this specific participant, results seemed a bit more consistent during the lying phase. It could be that for a short measurement, the standing phase is still affected by the transition between lying down and standing, and by how much time it took to go through the transition.
Finally, we can have a look at the sum of the two, as I've proposed in this post as a useful way to measure training load, by capturing the difference in HR/HRV during both phases of the protocol:
How do things change when we sum up the two phases?
Let's look at some numbers, even though this is a single user and therefore things are not necessarily applicable to everyone. When looking at data while lying down, we can isolate 9 intense trainings that have also a recording on the following day. Out of these 9 trainings, on 8 following days we have a reduction in HRV, with one day showing pretty much the same value. For HR, we have that only 6 out of 9 trainings triggered a higher HR the following day.
When looking at data while standing, for HRV we have that 7 out of 9 intense trainings triggered lower HRV values on the following day, while only 5 out of 9 intense trainings triggered a higher HR on the following days.
Finally, if we look at the sum of the two, we have that all HRV values (9 out of 9) on the day following intense training are lower than the day before, and 6 out of 9 trainings triggered higher HR on the following day.
This was an interesting analysis with some unexpected results. Doing orthostatic measurements can bring some additional advantages, even though the single HRV measurements have already shown to be good enough to measure training load and recovery, as pointed out by this analysis as well.
However, the higher discriminative power between the easy and intense training conditions using orthostatic HRV measurements when taking the sum of the HRV difference for the two phases, could provide slightly more accurate guidance when optimizing training using these physiological measurements.
"Traditional" orthostatic measurements, where we try to determine training load using just the difference between lying and standing HR, do not seem to capture training load, since both measurements while lying down and standing are affected and therefore the difference cancels out the information we are trying to capture.
EDIT: just a small edit after a quick conversation with Alan Couzens on twitter, he points out (showing some amazing data) that orthostatic HR measurements might still be very useful to monitor longer term stressors, while for day to day guidance on training, the usual rMSSD-based HRV metrics are definitely better. Something to keep in mind, and definitely very interesting in the context of better understanding physical condition, beyond daily advice based on HRV measurement.
Register to the mailing list
and try the HRV4Training app!
1. Context & Time of the Day
3. Paced breathing
4. Orthostatic Test
5. Slides HRV overview
1a. Acute Changes in HRV
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
2b. 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
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. Zoom HRV vs Polar
7. Apple Watch and HRV
8. Scosche Rhythm24
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. HRV4T Coach advanced view
8. Acute HRV changes by sport
9. Remote tags in HRV4T Coach
10. VO2max Estimation
11. Acute stressors analysis
12. Training Polarization
13. Custom desirable range / SWC
14. Lactate Threshold Estimation
1. Intro to HRV
2. HRV normal values
3. HRV by sport
4. HRV, strength & power
5. AngelSensor & HRV
6. HRV 101: How to
7. Top 5 most read articles
8. HRV normalization by HR
9. How to use HRV, the basics