A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons

Guillaume Durandau; Herman van der Kooij; Massimo Sartori

doi:10.1007/978-3-030-01887-0_62

A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons

Guillaume Durandau, Herman van der Kooij, Massimo Sartori^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

Abstract

Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we created a muscle-driven controller based on electromyography (EMG)-driven musculoskeletal modeling that we interfaced with the robotic bi-lateral Achilles ankle exoskeleton previously developed in our group. Preliminary results on one healthy individual show the possibility of continuously decoding EMG-dependent muscle force and resulting ankle joint moment patterns in real-time across a range of diverse motor tasks. We demonstrate that this information can be used to establish a human-exoskeleton interface with high-resolution at the level of single muscle mechanics.

Original language	English
Title of host publication	Wearable Robotics
Subtitle of host publication	challenges and trends
Editors	Maria Chiara Carrozza, Silvestro Micera, José L. Pons
Publisher	Springer
Pages	325-328
Number of pages	4
ISBN (Electronic)	978-3-030-01887-0
ISBN (Print)	978-3-030-01886-3
DOIs	https://doi.org/10.1007/978-3-030-01887-0_62
Publication status	Published - 1 Jan 2019

Publication series

Name	Biosystems and Biorobotics
Volume	22
ISSN (Print)	2195-3562
ISSN (Electronic)	2195-3570

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-030-01887-0_62

Cite this

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abstract = "Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we created a muscle-driven controller based on electromyography (EMG)-driven musculoskeletal modeling that we interfaced with the robotic bi-lateral Achilles ankle exoskeleton previously developed in our group. Preliminary results on one healthy individual show the possibility of continuously decoding EMG-dependent muscle force and resulting ankle joint moment patterns in real-time across a range of diverse motor tasks. We demonstrate that this information can be used to establish a human-exoskeleton interface with high-resolution at the level of single muscle mechanics.",

author = "Guillaume Durandau and {van der Kooij}, Herman and Massimo Sartori",

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A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons. / Durandau, Guillaume; van der Kooij, Herman ; Sartori, Massimo.
Wearable Robotics: challenges and trends. ed. / Maria Chiara Carrozza; Silvestro Micera; José L. Pons. Springer, 2019. p. 325-328 (Biosystems and Biorobotics; Vol. 22).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

TY - CHAP

T1 - A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons

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AU - Sartori, Massimo

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N2 - Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we created a muscle-driven controller based on electromyography (EMG)-driven musculoskeletal modeling that we interfaced with the robotic bi-lateral Achilles ankle exoskeleton previously developed in our group. Preliminary results on one healthy individual show the possibility of continuously decoding EMG-dependent muscle force and resulting ankle joint moment patterns in real-time across a range of diverse motor tasks. We demonstrate that this information can be used to establish a human-exoskeleton interface with high-resolution at the level of single muscle mechanics.

AB - Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we created a muscle-driven controller based on electromyography (EMG)-driven musculoskeletal modeling that we interfaced with the robotic bi-lateral Achilles ankle exoskeleton previously developed in our group. Preliminary results on one healthy individual show the possibility of continuously decoding EMG-dependent muscle force and resulting ankle joint moment patterns in real-time across a range of diverse motor tasks. We demonstrate that this information can be used to establish a human-exoskeleton interface with high-resolution at the level of single muscle mechanics.

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T3 - Biosystems and Biorobotics

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A2 - Carrozza, Maria Chiara

A2 - Micera, Silvestro

A2 - Pons, José L.

PB - Springer

ER -

A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons

Abstract

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UN SDGs

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