Use Zwift running workouts to increase your running pace with a data-driven, personalized and predictive Zwift running training plan from AI Endurance.
You can now execute your AI Endurance workouts as Zwift running workouts by following these simple steps:
In case you are updating your training plan make sure to delete all AI Endurance .zwo files from your old plan in the workout folder prior to uploading your new workouts. Don't delete the file workouts.files as it is Zwift's way of keeping track which workouts were deleted.
For more information, see how to use custom workouts in Zwift.
That's it, now you can execute your AI Endurance runs as a Zwift running training plan.
See also our Zwift custom cycling workouts.
You can also get a taste of some our workouts under
AI Endurance is based on the observation that an optimal training routine can be very different for each individual. That's why one-size-fits all training plans often don't yield the expected results.
With AI Endurance you get truly personalized, data-driven training based on your accumulated historic GPS and heart rate data. Our machine learning algorithm is like a 'digital twin' that represents how you respond to different training routines. This allows us to
For your optimized, personalized training plan we take into account
You can always make adjustments to your training plan when real life gets in the way.
Sign up today and get your own personalized training plan to reach your goal race pace!
Power meters are costly and we often can't afford one on every bike we own. AI Endurance calculates cycling power from activities without a power meter using heart rate, cadence and DFA alpha 1. The results are generally more accurate than speed based estimates such as Strava's estimated power. All you need is a heart rate monitor and ideally a cadence sensor on your bike and AI Endurance will estimate your power for every ride.
We get it, virtual races are not the same as actual races in terms of staying motivated. That's why AI Endurance is introducing a new maintenance running schedule to keep you in shape during the pandemic.
by Stefano Andriolo. Building on previous work, we refine a method to accurately determine the relationship between DFA alpha 1 and power. This method can be used to track fitness and thresholds of an athlete. We find in some cases ramp detection tends to overestimate thresholds, a finding mirrored in recent physiological papers. On the other hand, thresholds based on clustering of DFA alpha 1 values tend to agree well with this new method. We propose a hybrid lab and everyday workout experiment to further study the relationship.
by Markus Rummel. DDFA (Dynamical Detrended Fluctuation Analysis) is a new method to analyze the changes in your HRV data during exercise. It is an evolution of the DFA analysis based on the research in [1, 2] used by AI Endurance.