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.
by Grant Paling. In the first of three blog posts, Grant shares his experience of qualifying for Great Britain's Age Group team in the upcoming European Triathlon Championships.
Use Zwift running workouts to increase your running pace with a data-driven, personalized and predictive Zwift running training plan from AI Endurance.
Get your AI Endurance best training plan into TrainingPeaks. From there, you can execute your TrainingPeaks workouts in Zwift and many other apps. Connect your AI Endurance account once and any changes will automatically be synced with TrainingPeaks.
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.
