real-time Monitoring of the Aerobe and Anaerobe phase during Training (MAAT)

This doctoral programme will be performed in cooperation with Belgian Cycling Factory on the basis of a Baekeland mandate. Based on a patent created by M3-Biores (International Publication Number WO2013/120151 A1), the MAAT project will refine and expand the algorithm to predict the physical condition of cyclists by measuring the heart rate and power output. In doing so, the tipping point between the aerobe and anaerobe training phase is determined. The algorithm has already been tested in lab conditions, but needs to be adapted to the field and to different target groups of varying skill levels. Moreover, the algorithm will be expanded with a machine learning-based model to integrate the effects of environmental temperature, humidity and to a lesser extent the aerodynamic position and hydration status. The facilities of Belgian Cycling Factory such as the wind tunnel and climate chamber are extremely well suited for this. BCF's extensive expertise and prominent place in the cycling ecosystem allows testing every iterative step of the research project on both professional cyclists with the Lotto-Soudal team, as well as amateur cyclists with the Ridley Family. The collaboration with professor Van Breda from the University of Antwerp also ensures the exploration of the use of the model for revalidation purposes. A second machine learning-based model will be created based on the collected data to predict the optimal training schedules for different types of cyclists. User expectations will be collected alongside to provide support in the front-end development of a Minimal Viable Product.