Development of Machine Learning Algorithms for the Determination of the Centre of Mass
Abstract
:1. Introduction
2. Materials and Methods
2.1. Wii Balance Board
2.2. Video Acquisition
2.3. OpenPose
2.4. Assessment of the Centre of Mass
3. Results
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
List of Abbreviations
CoM | Centre of Mass |
CoG | Centre of Mass on the Ground |
CoP | Centre of Pressure |
OP | OpenPose |
BB | Nintendo™ Wii Balance Board™ |
CNN | Convolution Neural Networks |
MoCap | Motion Capture |
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D’Andrea, D.; Cucinotta, F.; Farroni, F.; Risitano, G.; Santonocito, D.; Scappaticci, L. Development of Machine Learning Algorithms for the Determination of the Centre of Mass. Symmetry 2021, 13, 401. https://doi.org/10.3390/sym13030401
D’Andrea D, Cucinotta F, Farroni F, Risitano G, Santonocito D, Scappaticci L. Development of Machine Learning Algorithms for the Determination of the Centre of Mass. Symmetry. 2021; 13(3):401. https://doi.org/10.3390/sym13030401
Chicago/Turabian StyleD’Andrea, Danilo, Filippo Cucinotta, Flavio Farroni, Giacomo Risitano, Dario Santonocito, and Lorenzo Scappaticci. 2021. "Development of Machine Learning Algorithms for the Determination of the Centre of Mass" Symmetry 13, no. 3: 401. https://doi.org/10.3390/sym13030401