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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Detalles Bibliográficos
Autores principales: Zaroug, Abdelrahman, Garofolini, Alessandro, Lai, Daniel T. H., Mudie, Kurt, Begg, Rezaul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341582/
https://www.ncbi.nlm.nih.gov/pubmed/34351994
http://dx.doi.org/10.1371/journal.pone.0255597

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341582/
https://www.ncbi.nlm.nih.gov/pubmed/34351994
http://dx.doi.org/10.1371/journal.pone.0255597

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