Machine learning-based classification model corresponding to the paper 'Machine learning to improve orientation estimation in sports situations challenging for inertial sensor use'
Machine learning model as used in 'Machine learning to improve orientation estimation in sports situations challenging for inertial sensor use'. The model to run the Extended Madgwick filter is based on a random forest algorithm and can be used as explained in Figure 3 in the paper. Explanation for use:The model can be loaded and executed in Python using the following code- RFmodel = pickle.load(open([filename_RFmodel], 'rb'))- y = RFmodel.predict_proba(X)[:,1]- if y > 0.5 EFcorrect = 1 else EFcorrect = 0 X are (normalized) input variablesy are probabilities for EFcorrect (see paper)
Machine Learning to Improve Orientation Estimation in Sports Situations Challenging for Inertial Sensor Use