Feasibility of Training a Random Forest Model With Incomplete User-Specific Data for Devising a Control Strategy for Active Biomimetic Ankle

Feasibility of Training a Random Forest Model With Incomplete User-Specific Data for Devising a Control Strategy for Active Biomimetic Ankle

Intelligent control strategies for active biomimetic prostheses could exploit the inter-joint coordination of limbs in human gait in order to mimic the functioning of a biological joint. A machine learning regression model could be employed to learn an input-output relationship between the coordinat...

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Bibliographic Details
Main Authors: Sharmita Dey, Takashi Yoshida, Arndt F. Schilling
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-08-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
human gait
prediction
prosthetic control
intelligent biomimetics
random forest
Online Access:https://www.frontiersin.org/article/10.3389/fbioe.2020.00855/full

Internet

https://www.frontiersin.org/article/10.3389/fbioe.2020.00855/full

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