HRV4Training Pro: Resting Physiology
User guide index: https://marcoaltini.substack.com/p/hrv4training-pro-user-guide
The resting physiology page provides an overview of your HRV, heart rate, and coefficient of variation, together with daily and baseline changes and their respective normal ranges.
The individual parameters are then combined in HRV4Training’s trend detection, to determine if a recent trend is changing in a trivial way, or if the change is something to take more seriously, based on historical data.
Combining these physiological parameters, the platform will also estimate your current response, among one of the following: stable, coping well with training, maladaptation, or risk of accumulated fatigue. The trend detection in Pro will also assess the possibility of parasympathetic saturation, which I discuss here.
We’ve seen in the scientific literature that looking at multiple parameters together is a must in the context of trying to understand long-term trends. Here is an overview of what we have implemented in HRV4Training, together with a basic interpretation of their use:
HRV (ln rMSSD)
An increase is typically associated with coping well with training and improved fitness level. A reduction is not necessarily bad, it could be associated with parasympathetic saturation or tapering. Looking at heart rate can help figure out the different situations. Most importantly, HRV should always be considered in the context of a specific training phase. For example, an increase in HRV during a high-load phase is typical when good athletes are responding well to the stimulus and might be associated with other physiological mechanisms such as increased blood plasma volume. Such an increase in HRV during high-volume training can be considered a sign of functional overreaching, that’s an ideal response. A reduction in HRV outside of tapering and with stable or increasing resting heart rate is typically a sign of a poor physiological response to either acute or chronic stressors.
Resting heart rate
In general, an increase is associated with more fatigue if acute, or less fitness if chronic unless it is occurring during tapering. A reduction is most of the time associated with coping well with training and better cardiorespiratory fitness level, especially if we talk about trends analyzed over several weeks or months. A stable trend is ideal. Note that seasonal patterns are present (e.g. resting heart rate tends to be lower in summer), and therefore changes should always be analyzed with respect to your normal values, as we do in the HRV4Training app.
Coefficient of variation of HRV
A decrease associated with higher HRV and lower resting heart rate can be representative of coping well with training, while a reduction associated with lower HRV is probably representative of the risk of non-functional overreaching. An increase in the coefficient of variation might reflect some trouble in adapting to a new training block (or other stressors, such as travel or altitude) and if associated with reduced HRV might be a warning sign of inappropriate training load.
Normal range: one of the difficulties of analyzing trends is due to the choices we need to make in terms of the amount of data used for this analysis. For example, after a negative response, resulting in a reduction in HRV, we might have stable trends, but still far off from our normal range. This is why I included also the normal range in our multiparameter trends analysis, so that periods of long, abnormal responses, can be better quantified.
Trend detection
The algorithm we implemented reports one of the following conditions, based on the parameters listed above, and an analysis of how they are changing in the past 2 weeks, with respect to normal variability in our own historical data, in the previous 60 days:
Stable: values are fluctuating normally but without strong changes. Normally, this means that you can proceed as planned, but keep an eye on any acute drops.
Coping well with training: typically associated with unchanged or increased HRV and unchanged or decreased resting heart rate, together with a lower coefficient of variation, within your normal range. This means that it’s all good, and you should proceed according to your plans.
Maladaptation to training: associated with increased resting heart rate and coefficient of variation, reductions in HRV. This is a sign of a poor response to current stressors (training or other), and typically it would be a good idea to reduce training intensity or prioritize recovery in other ways.
Accumulated fatigue: decreased HRV and increased resting heart rate, with reduced coefficient of variation or HRV suppressed below your normal values. This is what is shown above for my own data, and is often associated with longer periods of poor health or poor responses that require slowing down and trying to prioritize recovery for several days or weeks.
Saturation: saturation is often associated with reduced HRV and resting heart rate, in particular for individuals with very low resting heart rates or elite athletes. It is important to analyze this trend in the context of a training program and training history. This is an experimental feature.
That’s all for the resting physiology page. I hope you’ll find it useful.
Thank you for your support.
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.
Twitter: @altini_marco
