Published Dec 3, 2021 · Updated Dec 6, 2021
If you do not want to use Zwift or other virtual platforms, you can simply execute your AI Endurance cycling workouts by letting your Garmin control your smart trainer. For example, let your Garmin Edge 530 or Forerunner 945 control your Wahoo Kickr trainer. All smart trainers supporting the ANT+ FE-C protocol, including Tacx, are supported.
If you do not care too much for the entertainment that virtual cycling environments such as Zwift offer and simply want to get your indoor workouts done in a productive way, this is for you. And you get to save the Zwift subscription fee as well.
Here's how you do it:
Here's a video of how to set this up for the Garmin Edge 520:
AI Endurance is a training platform that optimizes and predicts your cycling performance. You tell us how much time you have to train and we find the optimal training composition based on your training data.
To get more information on how to control your smart trainer with your Garmin device please see:
Export your AI Endurance workouts to your Garmin Connect today and connect your Garmin device with your smart trainer. This is all you need to execute your personalized training plan and grow your FTP.
If you do not want to use Zwift or other virtual platforms, you can simply execute your AI Endurance cycling workouts by letting your Garmin control your smart trainer. For example, let your Garmin Edge 530 or Forerunner 945 control your Wahoo Kickr trainer. All smart trainers supporting the ANT+ FE-C protocol, including Tacx, are supported.
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.
We compare polarized training, threshold training and AI optimized endurance training. AI optimized training yields the best results, followed by polarized training with threshold training in third. The results are inline with current exercise physiology research. If the training composition is not optimized to the individual athlete, substantially smaller gains are to be expected.
In this post, we give a short introduction to the running training zones and cycling training zones we use to structure your training. We use 5 training zones defined by pace for running activities and by power for cycling activities. AI Endurance calculates these zones for you individually based on your past training data.
