The anaerobic threshold is an important marker commonly used in cycling to identify training zones and monitor training progress. However, monitoring of the anaerobic threshold is not performed on a regular basis due to the high costs, invasive blood sampling and time-intensive test protocols. Mathematical modelling might form a suitable alternative for regular monitoring of performance. Furthermore, modelling allows for identifying the effect of certain influential variables on the performance, resulting in performance prediction. They might enable more practical applications, especially in combination with wearable technology. In cycling, the heart rate, power and cadence are already continuously measured and monitored during training and competition, making them particularly suitable for integration in a modelling technique. This study attempts to estimate the anaerobic threshold with linear time-invariant and linear time-varying models based on the heart rate, power.
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