“…To evaluate sensor data, especially in a sparse measurement setup, machine learning techniques are necessary [ 20 , 21 ]. In recent years, IMU and machine learning techniques, including artificial neural networks (ANN), have been successfully applied in both classification and prediction tasks in biomechanical settings [ 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Traditional machine learning algorithms such as Random Forest, Support Vector Machine, etc., require time-intensive feature engineering and manual feature extraction.…”