We have released a new feature in HRV4Training Pro: Cardiac decoupling. You can find it under Insights / Aerobic endurance, together with our Aerobic Efficiency analysis.
Note that to use this feature you need to use HRV4Training linked to Strava, so that your workout summaries and laps can be analyzed.
What's cardiac decoupling?
Cardiac decoupling relates to your cardiac drift during an aerobic effort. What’s your cardiac drift? Basically, your heart rate increasing as a result of your body getting fatigued, during the second part of a workout.
To determine your cardiac decoupling, we compute the relation between output (pace or power) and input (heart rate) during the first and second half of a workout.
Intuitively, if heart rate increases at the same pace during the second part of a workout, or if your pace reduces in an attempt to keep your heart rate below a certain value, it means that your aerobic endurance for the distance is not well developed. Similarly, a ratio close to one or below 1.03–1.05 shows that your heart rate does not drift much during the second part of the workout, which is a sign of good aerobic endurance.
Here is 6 months of data, which include about 4–5 months of very good training in between two injuries:
As you can see there is a quite long period in which decoupling is suboptimal (gray), which means my heart rate was drifting quite a bit.
Then, things get better with consistent training and towards February cardiac drift is constant at 1, which means there is no difference in heart rate and pace in the second half of the workout (for the selected workouts, more on this later). Here is an example of an easy run during that period, you can see pace and heart rate being quite constant:
Finally, as I got injured again, which resulted in about 6 weeks without running before getting back at it at the beginning of April, my cardiac decoupling became again pretty terrible (see the yellow area in the figure above).
Here is an example of a workout in this period, in which I had to slow down a lot despite running just 12 km, to keep my heart rate from going really high:
Knowing both your aerobic efficiency and your cardiac decoupling can provide you with quite a good picture of your current aerobic endurance abilities as you prepare a certain event.
Here is another example, this time using Alessandra’s data. We can see the same few months of consistent training, with decoupling reducing over time until race day (March 19th). Here we have no injuries, but a bit of post-race tiredness that shows as increased decoupling before things get back to normal:
For cardiac decoupling, we do have ideal values, as we are not comparing to anyone else but simply computing the ratio between your first and second half of a workout, hence the closer to 1, the better.
Knowing your average pace (or power) and heart rate for a workout is sufficient to compute your aerobic efficiency. Running the same analysis isolating the first and second half of a workout can provide you with more insights on cardiac drift or what we have called here cardiac decoupling
Accounting for confounding factors
There are many factors that can affect the relationship between pace (or power) and heart rate.
A few examples are: running or cycling on trails or difficult terrains, (which reduces pace and makes your data not really representative of your fitness), very short workouts where heart rate does not reach a steady state, environmental factors such as hot days or training at altitude, etc. — the list goes on.
While many of these parameters are simply impossible to account for, what we can do is give you more control over what data is used to track changes in aerobic endurance. In particular, via the panel below you can filter workouts and environmental factors so that the resulting data is more representative of your aerobic endurance.
You can also select how much data you’d like to use for each data point, for example selecting light smoothing, only this week of data will be used, while using average smoothing, which I recommend, uses 3 weeks of data. The plots shown above use heavy smoothing, 6 weeks of data per data point.
For example, using the parameters selected above, and my recent training log which includes just a few runs post-injury, I get the following list of workouts:
To use this feature you need to use HRV4Training linked to Strava, so that your workout summaries and laps can be analyzed.
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This blog is curated by
Marco Altini, founder of HRV4Training
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