Predictive framework of human locomotion based on neuromuscular primitives and modeling

Massimo Sartori; José González-Vargas; Strahinja Došen; Jose L Pons; Dario Farina

doi:10.1007/978-3-319-46669-9_46

Predictive framework of human locomotion based on neuromuscular primitives and modeling

Massimo Sartori^*, José González-Vargas, Strahinja Došen, Jose L Pons, Dario Farina

^*Corresponding author for this work

Physical Medicine and Rehabilitation

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Synthesizing human movement in computational neuro-mechanical models is a complex problem. In this study, we describe a predictive framework that combines computational models of neural, sensory and mechanical processes. Our proposed formulation facilitates the transition towards the design of a new class of bio-mimetic assistive devices that do not rely on explicit representations of task-specific motor control models.

Original language	English (US)
Title of host publication	Biosystems and Biorobotics
Publisher	Springer International Publishing
Pages	265-269
Number of pages	5
DOIs	https://doi.org/10.1007/978-3-319-46669-9_46
State	Published - 2017

Publication series

Name	Biosystems and Biorobotics
Volume	15
ISSN (Print)	2195-3562
ISSN (Electronic)	2195-3570

ASJC Scopus subject areas

Biomedical Engineering
Mechanical Engineering
Artificial Intelligence

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10.1007/978-3-319-46669-9_46

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abstract = "Synthesizing human movement in computational neuro-mechanical models is a complex problem. In this study, we describe a predictive framework that combines computational models of neural, sensory and mechanical processes. Our proposed formulation facilitates the transition towards the design of a new class of bio-mimetic assistive devices that do not rely on explicit representations of task-specific motor control models.",

author = "Massimo Sartori and Jos{\'e} Gonz{\'a}lez-Vargas and Strahinja Do{\v s}en and Pons, {Jose L} and Dario Farina",

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AU - Sartori, Massimo

AU - González-Vargas, José

AU - Došen, Strahinja

AU - Pons, Jose L

AU - Farina, Dario

N1 - Funding Information: Acknowledgments This work was in part supported by the ERC Advanced Grant DEMOVE [267888]. Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - Synthesizing human movement in computational neuro-mechanical models is a complex problem. In this study, we describe a predictive framework that combines computational models of neural, sensory and mechanical processes. Our proposed formulation facilitates the transition towards the design of a new class of bio-mimetic assistive devices that do not rely on explicit representations of task-specific motor control models.

AB - Synthesizing human movement in computational neuro-mechanical models is a complex problem. In this study, we describe a predictive framework that combines computational models of neural, sensory and mechanical processes. Our proposed formulation facilitates the transition towards the design of a new class of bio-mimetic assistive devices that do not rely on explicit representations of task-specific motor control models.

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BT - Biosystems and Biorobotics

PB - Springer International Publishing

ER -

Predictive framework of human locomotion based on neuromuscular primitives and modeling

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