Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications

Gait speed is an important biomechanical determinant of gait patterns, with joint kinematics being influenced by it. This study aims to explore the effectiveness of fully connected neural networks (FCNNs), with a potential application for exoskeleton control, in predicting gait trajectories at varyi...

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Detalles Bibliográficos
Autores principales: Kolaghassi, Rania, Marcelli, Gianluca, Sirlantzis, Konstantinos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301853/
https://www.ncbi.nlm.nih.gov/pubmed/37420852
http://dx.doi.org/10.3390/s23125687

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301853/
https://www.ncbi.nlm.nih.gov/pubmed/37420852
http://dx.doi.org/10.3390/s23125687

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