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.
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.
Daily readiness to train is affected by many factors including sleep, illness and training load. Heart rate variability (HRV) readiness to train metrics typically rely on measurements taken immediately upon waking in the morning. We introduce an HRV readiness to train and a durability metric based on DFA alpha 1 (a1) measurements taken during exercise. These new metrics provide additional insights and do not require you to measure HRV upon waking.
Get your AI Endurance best training plan into TrainingPeaks. From there, you can execute your TrainingPeaks workouts in Zwift, Apple Watch, Wahoo, Polar, Suunto and many other apps. Connect your AI Endurance account once and any changes will automatically be synced with TrainingPeaks.
DFA alpha 1 is a heart rate variability (HRV) metric that allows tracking of the aerobic and anaerobic threshold. We explain the breakthrough potential of this new metric and how you can track your DFA alpha 1 thresholds with the AI Endurance app, Garmin and Zwift.
DFA (detrended fluctuation analysis) alpha 1 is an HRV (heart rate variability) based aerobic and anaerobic threshold estimation method. It only requires a heart rate monitor that tracks HRV data. It has the potential to track your thresholds automatically without dedicated test workouts.
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.
There are different options on the market for optimized AI training plans that are based on applying machine learning to your individual data. In this post, we compare the different options and their features.
Use Zwift custom workouts to grow your FTP with a data-driven, personalized Zwift custom training plan from AI Endurance.
Use Zwift running workouts to increase your running pace with a data-driven, personalized and predictive Zwift running training plan from AI Endurance.
While we are getting our app ready for the App Store you can install AI Endurance at full functionality on your iOS device with only a few clicks.
Execute your AI Endurance personalized training plan directly from your Garmin watch or bike computer. No more writing down workouts or remembering interval sets. Get step-by-step instructions as Garmin custom workouts and a Garmin Connect training plan with only a few clicks.
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.
Stay on top of your goals and support our local businesses and charities at the same time. A virtual cycling challenge that comes as close to a race as possible now that social distancing is crucial in slowing down the spread of COVID-19.
Stay on top of your goals and support our local businesses at the same time. A virtual running challenge that comes as close to a race as possible now that social distancing is crucial in slowing down the spread of COVID-19.
We recap the results of following AI Endurance’s cycling training plan that saw our FTP grow according to AI Endurance’s predictions, following the instructions on how to improve FTP.
In this post, we discuss staying motivated executing your cycling training plan when you’re not training for an event. Also we give an update on our training and give a status report on how AI Endurance’s performance predictions are stacking up against reality.
In this post, we explain how to use AI Endurance’s cycling training plan that we generated for Paris to Ancaster, Canada’s biggest gravel racing event. The plan includes detailed workout instructions. For indoor cycling, we show how to use AI Endurance with Trainerroad and Zwift.
Paris to Ancaster is the biggest gravel grinder bike race in Canada. It’s in 8 weeks and I need to get in shape. AI Endurance can predict race performance and create a training plan which is optimized to my training responses. It predicts that I can increase my FTP by 14% to 293 Watts on race day with just 3.5 hours of training a week.
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.
AI Endurance has a built-in race pace predictor for your running and cycling performance. In this post, we discuss how you can use it to predict your pace for your next running race or your goal power for your next cycling event.
Sometimes it’s hard to stay motivated during the cold months with the next race still so far away. We’ll give you a few winter training tips on how to stay motivated and stay fit until it gets warmer outside.
AI has great potential to help us as endurance athletes improve our training. In this post we will discuss how AI endurance training works.