Machine learning-based classification model corresponding to the paper 'Machine learning to improve orientation estimation in sports situations challenging for inertial sensor use'

DOI:10.4121/14883927.v1
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DOI: 10.4121/14883927
Datacite citation style:
van Dijk, Marit (2021): Machine learning-based classification model corresponding to the paper 'Machine learning to improve orientation estimation in sports situations challenging for inertial sensor use'. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/14883927.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

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)

History

  • 2021-07-13 first online, published, posted

Publisher

4TU.ResearchData

Funding

  • ZonMw project number: 546003002

Organizations

TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, department of BioMechanical Engineering
Vrije Universiteit Amsterdam
The Hague University of Applied Sciences

DATA

Files (1)