The goal of the project is to formalise the 'eye of the master' through technological innovation, thus making the judgement of performance more transparent and less subjective. 

Currently, the level and performance of the rider and horse are often judged subjectively. The end goal is to explore whether it is possible to develop a digital measurement system that can be used to provide direct feedback, as well as personalised guidance to riders. In this project, we focus specifically on what can be achieved using sensor data of phones attached to the rider and horse. 

Work is done in cooperation with JADS - Jheronimus Academy of Data Science and our goal for this was twofold:

  • To be able to recognize the different gaits from the sensor data. This entails building a classification model which is capable of classifying the different gaits of the horse (such as walk, trot, and canter). 
  • To be able to classify the performance based on the Skala der Ausbildung. The Skala der Ausbildung is a scale of training which classifies the performance of the horse according to six different elements which improve over time. These elements are rhythm, suppleness/relaxation, contact, straightness, impulsion and collection. After discussions with EquInnoLab and some initial findings, we have decided to scope down the second goal and focus on rhythm and straightness specifically.