Digging into DFA alpha 1
| Howdy! I have been on a deep dive into this relatively new metric/technique that offers some promise to fine tune your training zones to your own unique physiology. While this post is definitely a summary, it still gets into the weeds a little. Rest assured, though, there is some actionable information here! Enjoy. |
| Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. – Thomas Gronwald, Bruce Rogers and Olaf Hoos |
| What is DFA alpha 1? DFA alpha 1 is a new metric/technique to identify your aerobic threshold. Your aerobic threshold is the intensity where your physiology starts to show the first significant signs of a disruption of metabolic homeostasis. This occurs at a relative low intensity and is typically identified in the lab by measuring blood lactate concentration or by measuring breathing data via V02 testing. It also can be estimated by relying on percentages of other physiological or output metrics like FTP or Max HR. Finally, a low-tech estimator is the so-called “talk test.” Detrended Fluctuation Analysis is a mathematical method for determining the statistical self-affinity of a signal, in the case of DFA a1, the heart rate signal. Much like HRV for recovery and readiness monitoring, DFA a1 is a metric derived from the heart rate signal by examining the variations in between individual beats. But unlike HRV analysis, it is done during activity. Initial research has identified a value (.75) which appears to correlate well with the lactate threshold (LT1) and the ventilatory threshold (VT1) as indicators of your aerobic threshold (AeT). Why is the AeT important? The aerobic threshold is important because it is the upper limit of low intensity training. This is where endurance athletes spend the majority of time when training according to a BASE, POLARIZED, or PYRAMIDAL model of intensity distribution. Normally, we just rely on estimations of this point, typically 75% of FTP in the Coggan 7-Zone model (power). There are 2 problems with this approach: 1) it relies on statistical norms to determine the specific intensity threshold and is, therefore, not individualized, and 2) it doesn’t account for day-to-day internal variability or internal responses to training stress during a particular workout. Why is DFA alpha 1 important? Most athletes would benefit from identifying and utilizing their own individual AeT. The problem is that existing methods involve expensive equipment or laboratory tests. There is also some difficulty in effectively translating lab results to your daily training sessions. DFA alpha 1 is interesting because it can be measured in real-time with a $10 app on your iPhone. This makes it easy to do your own “lab test” on the trainer at any time. And perhaps even more valuable, continuously measure and monitor a low intensity training session or effort block. Putting it to use It’s still early days, but this technique holds promise. I am doing my own testing and will incorporate my experience into training plans and coaching advice going forward. |
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