Predicting continuous ground reaction forces from accelerometers during uphill and downhill running: a recurrent neural network solution

BACKGROUND: Ground reaction forces (GRFs) are important for understanding human movement, but their measurement is generally limited to a laboratory environment. Previous studies have used neural networks to predict GRF waveforms during running from wearable device data, but these predictions are li...

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Detalles Bibliográficos
Autores principales: Alcantara, Ryan S., Edwards, W. Brent, Millet, Guillaume Y., Grabowski, Alena M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Data Mining and Machine Learning
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740512/
https://www.ncbi.nlm.nih.gov/pubmed/35036107
http://dx.doi.org/10.7717/peerj.12752

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740512/
https://www.ncbi.nlm.nih.gov/pubmed/35036107
http://dx.doi.org/10.7717/peerj.12752

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