This is a short post in which I’d like to cover just one aspect of HRV monitoring and more specifically of guiding training based on physiological responses, which I see it’s something often misunderstood or in general not completely clear when approaching tools like HRV4Training or other similar apps. While HRV4Training provides many insights, some of them built around trying to better understand the big picture and avoid overtraining (see for example HRV Trends, VO2max Estimation , Training Load Analysis , etc.) - I see the main misconception is often on the day to day use of the app. Let’s revise the basics: HRV, in particular rMSSD or a transformation of rMSSD such as HRV4Training’s Recovery Points, are simply a way to capture parasympathetic activity, or in other words, level of physiological stress. As we apply stress to trigger certain adaptations, measuring our body’s response to such stressors, as well as to all other forms of stress we are affected from (e.g. simply life happening, work stress, family, etc.), is very helpful as it can provide objective feedback and help us making meaningful adjustments, the simpler adjustments is probably just being a little more honest with ourselves, and slowing down from time to time, especially when our body is already too stressed. The example I’ve just highlighted is something we all understand quite well, higher stress as shown by lower HRV highlights how it might be a good idea to take it easy and avoid excessive stress which might lead to overtraining or slower recoveries, hindering improvements in performance. Now the main point of this article: what do you do when it’s all good? Should you push it all the time because your HRV is within normal values, often shown in apps as a green light? Of course not. The fact that your body is in a (physiologically speaking) normal state, is what you should aim for. Normal is good. However, this does not mean that every time HRV looks good you should go hard. The point I’m trying to make, which I’ve discussed also in this podcast with Molly and Peter at the Consummate Athlete, as well as in this one with Mikael at the scientific triathlon) is that you first need to have a plan, then you can make adjustments based on how you respond to such plan, which is something HRV and physiological measurements can allow you to do, by providing feedback on your individual specific physiological response to your training plan. Normal values, or in other words a green light, should give you confidence that everything is going well and in general you are coping well with your current training and lifestyle. Yet, if your training plan says you are due for a rest day, take it. If you are due for a low intensity workout, do it. Small adjustments such as flipping an intense workout scheduled for tomorrow are another way to make better use of these measurements, however it is important to understand that HRV and physiological measurements are tools for awareness, which allow you to understand how you respond to a particular plan, not to replace your plan entirely. To sum it all up:
Where to go from here?As you gather more data, looking at long term trends is definitely when things get more interesting, and in particular looking at baseline changes over time, with respect to your normal values. You can learn more about the big picture, in this post. Another important aspect highlighted also in the long term trends analysis linked above, is the fact that HRV is not necessarily a metric to be optimized towards some specific value. While we might want certain metrics to improve over time, and others do change as a consequence of our training, for example think about resting heart rate decreasing as a result of the heart muscle improving, HRV does not necessarily behave in the same way. In my opinion, the best way to make use of HRV is to use it as a continuous feedback loop so that we are more aware of the overall level of stress on the body and can make day to day adjustments aiming at eventually optimizing recovery and improving performance. Stay in touchComments are closed.
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