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Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design

Designing the physical coupling between the human body and the wearable robot is a challenging endeavor. The typical approach of tightening the wearable robot against the body, and softening the interface materials does not work well. It makes the task of simultaneously improving comfort, and anchor...

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Autores principales: John Varghese, Rohit, Mukherjee, Gaurav, Deshpande, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895480/
https://www.ncbi.nlm.nih.gov/pubmed/35250527
http://dx.doi.org/10.3389/fnbot.2021.727534
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author John Varghese, Rohit
Mukherjee, Gaurav
Deshpande, Ashish
author_facet John Varghese, Rohit
Mukherjee, Gaurav
Deshpande, Ashish
author_sort John Varghese, Rohit
collection PubMed
description Designing the physical coupling between the human body and the wearable robot is a challenging endeavor. The typical approach of tightening the wearable robot against the body, and softening the interface materials does not work well. It makes the task of simultaneously improving comfort, and anchoring the robot to the body at the physical human robot interaction interface (PHRII), difficult. Characterizing this behavior experimentally with sensors at the interface is challenging due to the soft-soft interactions between the PHRII materials and the human tissue. Therefore, modeling the interaction between the wearable robot and the hand is a necessary step to improve design. In this paper, we introduce a methodology to systematically improve the design of the PHRII by combining experimentally measured characteristics of the biological tissue with a novel dynamic modeling tool. Using a novel and scalable simulation framework, HuRoSim, we quantified the interaction between the human hand and an exoskeleton. In the first of our experiments, we use HuRoSim to predict complex interactions between the hand and the coupled exoskeleton. In our second experiment, we then demonstrate how HuRoSim can be coupled with experimental measurements of the stiffness of the dorsal surface of the hand to optimize the design of the PHRII. This approach of data-driven modeling of the interaction between the body and a wearable robot, such as a hand exoskeleton, can be generalized to other forms of wearable devices as well, demonstrating a scalable and systematic method for improving the design of the PHRII for future devices coupled to the body.
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spelling pubmed-88954802022-03-05 Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design John Varghese, Rohit Mukherjee, Gaurav Deshpande, Ashish Front Neurorobot Neuroscience Designing the physical coupling between the human body and the wearable robot is a challenging endeavor. The typical approach of tightening the wearable robot against the body, and softening the interface materials does not work well. It makes the task of simultaneously improving comfort, and anchoring the robot to the body at the physical human robot interaction interface (PHRII), difficult. Characterizing this behavior experimentally with sensors at the interface is challenging due to the soft-soft interactions between the PHRII materials and the human tissue. Therefore, modeling the interaction between the wearable robot and the hand is a necessary step to improve design. In this paper, we introduce a methodology to systematically improve the design of the PHRII by combining experimentally measured characteristics of the biological tissue with a novel dynamic modeling tool. Using a novel and scalable simulation framework, HuRoSim, we quantified the interaction between the human hand and an exoskeleton. In the first of our experiments, we use HuRoSim to predict complex interactions between the hand and the coupled exoskeleton. In our second experiment, we then demonstrate how HuRoSim can be coupled with experimental measurements of the stiffness of the dorsal surface of the hand to optimize the design of the PHRII. This approach of data-driven modeling of the interaction between the body and a wearable robot, such as a hand exoskeleton, can be generalized to other forms of wearable devices as well, demonstrating a scalable and systematic method for improving the design of the PHRII for future devices coupled to the body. Frontiers Media S.A. 2022-02-18 /pmc/articles/PMC8895480/ /pubmed/35250527 http://dx.doi.org/10.3389/fnbot.2021.727534 Text en Copyright © 2022 John Varghese, Mukherjee and Deshpande. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
John Varghese, Rohit
Mukherjee, Gaurav
Deshpande, Ashish
Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title_full Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title_fullStr Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title_full_unstemmed Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title_short Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design
title_sort designing physical human-robot interaction interfaces: a scalable method for simulation based design
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895480/
https://www.ncbi.nlm.nih.gov/pubmed/35250527
http://dx.doi.org/10.3389/fnbot.2021.727534
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