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Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques

The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimat...

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Detalles Bibliográficos
Autores principales: Latella, Claudia, Traversaro, Silvio, Ferigo, Diego, Tirupachuri, Yeshasvi, Rapetti, Lorenzo, Andrade Chavez, Francisco Javier, Nori, Francesco, Pucci, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631387/
https://www.ncbi.nlm.nih.gov/pubmed/31234414
http://dx.doi.org/10.3390/s19122794
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author Latella, Claudia
Traversaro, Silvio
Ferigo, Diego
Tirupachuri, Yeshasvi
Rapetti, Lorenzo
Andrade Chavez, Francisco Javier
Nori, Francesco
Pucci, Daniele
author_facet Latella, Claudia
Traversaro, Silvio
Ferigo, Diego
Tirupachuri, Yeshasvi
Rapetti, Lorenzo
Andrade Chavez, Francisco Javier
Nori, Francesco
Pucci, Daniele
author_sort Latella, Claudia
collection PubMed
description The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation problem. The presented approach is validated by presenting experimental results of a health subject equipped with a wearable motion tracking system and a pair of shoes sensorized with force/torque sensors while performing different motion tasks, e.g., walking on a treadmill. The results show that joint torque estimates obtained by using floating-base and fixed-base approaches match satisfactorily, thus validating the present approach.
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spelling pubmed-66313872019-08-19 Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques Latella, Claudia Traversaro, Silvio Ferigo, Diego Tirupachuri, Yeshasvi Rapetti, Lorenzo Andrade Chavez, Francisco Javier Nori, Francesco Pucci, Daniele Sensors (Basel) Article The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation problem. The presented approach is validated by presenting experimental results of a health subject equipped with a wearable motion tracking system and a pair of shoes sensorized with force/torque sensors while performing different motion tasks, e.g., walking on a treadmill. The results show that joint torque estimates obtained by using floating-base and fixed-base approaches match satisfactorily, thus validating the present approach. MDPI 2019-06-21 /pmc/articles/PMC6631387/ /pubmed/31234414 http://dx.doi.org/10.3390/s19122794 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Latella, Claudia
Traversaro, Silvio
Ferigo, Diego
Tirupachuri, Yeshasvi
Rapetti, Lorenzo
Andrade Chavez, Francisco Javier
Nori, Francesco
Pucci, Daniele
Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title_full Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title_fullStr Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title_full_unstemmed Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title_short Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques
title_sort simultaneous floating-base estimation of human kinematics and joint torques
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631387/
https://www.ncbi.nlm.nih.gov/pubmed/31234414
http://dx.doi.org/10.3390/s19122794
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