The Use of Synthetic IMU Signals in the Training of Deep Learning Models Significantly Improves the Accuracy of Joint Kinematic Predictions

Gait analysis based on inertial sensors has become an effective method of quantifying movement mechanics, such as joint kinematics and kinetics. Machine learning techniques are used to reliably predict joint mechanics directly from streams of IMU signals for various activities. These data-driven mod...

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Detalles Bibliográficos
Autores principales: Sharifi Renani, Mohsen, Eustace, Abigail M., Myers, Casey A., Clary, Chadd W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434290/
https://www.ncbi.nlm.nih.gov/pubmed/34502766
http://dx.doi.org/10.3390/s21175876

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434290/
https://www.ncbi.nlm.nih.gov/pubmed/34502766
http://dx.doi.org/10.3390/s21175876

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