Gaussian Process Autoregression for Joint Angle Prediction Based on sEMG Signals

There is uncertainty in the neuromusculoskeletal system, and deterministic models cannot describe this significant presence of uncertainty, affecting the accuracy of model predictions. In this paper, a knee joint angle prediction model based on surface electromyography (sEMG) signals is proposed. To...

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Detalles Bibliográficos
Autores principales: Liang, Jie, Shi, Zhengyi, Zhu, Feifei, Chen, Wenxin, Chen, Xin, Li, Yurong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Public Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175857/
https://www.ncbi.nlm.nih.gov/pubmed/34095080
http://dx.doi.org/10.3389/fpubh.2021.685596

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175857/
https://www.ncbi.nlm.nih.gov/pubmed/34095080
http://dx.doi.org/10.3389/fpubh.2021.685596

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