Prediction of gait trajectories based on the Long Short Term Memory neural networks.
The forecasting of lower limb trajectories can improve the operation of assistive devices and minimise the risk of tripping and balance loss. The aim of this work was to examine four Long Short Term Memory (LSTM) neural network architectures (Vanilla, Stacked, Bidirectional and Autoencoders) in pred...
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Autores principales: | Abdelrahman Zaroug, Alessandro Garofolini, Daniel T H Lai, Kurt Mudie, Rezaul Begg |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/a5de0cf3941c41b585df56e04a3f2f87 |
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