Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning
The research demonstrates that machine learning models, trained on data from IMU sensors, can classify horse gaits with up to 97% accuracy. This approach offers a more objective and automated alternative to traditional visual gait assessment, facilitating deeper biomechanical analysis and potential applications in genetic research and breeding.