Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Lower Limb Kinematics Trajectory Prediction Using Long Short-Term Memory Neural Networks
por: Zaroug, Abdelrahman, et al.
Publicado: (2020) -
Prediction and detection of freezing of gait in Parkinson’s disease from plantar pressure data using long short-term memory neural-networks
por: Shalin, Gaurav, et al.
Publicado: (2021) -
Splice Junction Identification using Long Short-Term Memory Neural Networks
por: Regan, Kevin, et al.
Publicado: (2021) -
Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks
por: Zazo, Ruben, et al.
Publicado: (2016) -
Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding
por: Yu, Zhibin, et al.
Publicado: (2017)