%0 Computer Program
%A van Dijk, Marit
%D 2021
%T Machine learning-based classification model corresponding to the paper 'Machine learning to improve orientation estimation in sports situations challenging for inertial sensor use'
%U https://data.4tu.nl/articles/software/Machine_learning-based_classification_model_corresponding_to_the_paper_Machine_learning_to_improve_orientation_estimation_in_sports_situations_challenging_for_inertial_sensor_use_/14883927/1
%R 10.4121/14883927.v1
%K Madgwick filter
%K Inertial Measurement Unit
%K orientation estimation
%K kinematics
%K machine learning
%K sports
%X 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.<div><br></div><div>Explanation for use:</div><div>The model can be loaded and executed in Python using the following code</div><div>- RFmodel = pickle.load(open([filename_RFmodel], 'rb'))</div><div>- y = RFmodel.predict_proba(X)[:,1]<div>- if y > 0.5</div><div>     EFcorrect = 1</div><div> else</div><div>     EFcorrect = 0</div><div> </div><div>X are (normalized) input variables</div><div>y are probabilities for EFcorrect (see paper)<br></div></div>
%I 4TU.ResearchData