An Assistive Soft Wrist Exosuit for Flexion Movements With an Ergonomic Reinforced Glove.

admittance control assistive robot cable-driven exosuit electromyography ergonomics flexible exoskeleton soft wrist exosuit wearable robotics

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2020
Historique:
received: 17 08 2020
accepted: 02 11 2020
entrez: 4 2 2021
pubmed: 5 2 2021
medline: 5 2 2021
Statut: epublish

Résumé

Soft exosuits are a promising solution for the assistance and augmentation of human motor abilities in the industrial field, where the use of more symbiotic wearable robots can avoid excessive worker fatigue and improve the quality of the work. One of the challenges in the design of soft exosuits is the choice of the right amount of softness to balance load transfer, ergonomics, and weight. This article presents a cable-driven based soft wrist exosuit for flexion assistance with the use of an ergonomic reinforced glove. The flexible and highly compliant three-dimensional (3D)-printed plastic structure that is sewn on the glove allows an optimal force transfer from the remotely located motor to the wrist articulation and to preserve a high level of comfort for the user during assistance. The device is shown to reduce fatigue and the muscular effort required for holding and lifting loads in healthy subjects for weights up to 3 kg.

Identifiants

pubmed: 33537345
doi: 10.3389/frobt.2020.595862
pmc: PMC7848217
doi:

Types de publication

Journal Article

Langues

eng

Pagination

595862

Informations de copyright

Copyright © 2021 Chiaradia, Tiseni, Xiloyannis, Solazzi, Masia and Frisoli.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Domenico Chiaradia (D)

Percro Laboratory, Tecip Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.

Luca Tiseni (L)

Percro Laboratory, Tecip Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.

Michele Xiloyannis (M)

Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, Switzerland and the Spinal Cord Injury Center, University Hospital Balgrist, Zurich, Switzerland.

Massimiliano Solazzi (M)

Percro Laboratory, Tecip Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.

Lorenzo Masia (L)

Institut für Technische Informatik (ZITI), Heidelberg University, Heidelberg, Germany.

Antonio Frisoli (A)

Percro Laboratory, Tecip Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.

Classifications MeSH