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Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics

This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial visio...

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Detalles Bibliográficos
Autores principales: Perez, Elisa, López, Natalia, Orosco, Eugenio, Soria, Carlos, Mut, Vicente, Freire-Bastos, Teodiano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888755/
https://www.ncbi.nlm.nih.gov/pubmed/24453877
http://dx.doi.org/10.1155/2013/589636
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author Perez, Elisa
López, Natalia
Orosco, Eugenio
Soria, Carlos
Mut, Vicente
Freire-Bastos, Teodiano
author_facet Perez, Elisa
López, Natalia
Orosco, Eugenio
Soria, Carlos
Mut, Vicente
Freire-Bastos, Teodiano
author_sort Perez, Elisa
collection PubMed
description This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair.
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spelling pubmed-38887552014-01-22 Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics Perez, Elisa López, Natalia Orosco, Eugenio Soria, Carlos Mut, Vicente Freire-Bastos, Teodiano ScientificWorldJournal Research Article This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair. Hindawi Publishing Corporation 2013-12-26 /pmc/articles/PMC3888755/ /pubmed/24453877 http://dx.doi.org/10.1155/2013/589636 Text en Copyright © 2013 Elisa Perez et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Perez, Elisa
López, Natalia
Orosco, Eugenio
Soria, Carlos
Mut, Vicente
Freire-Bastos, Teodiano
Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title_full Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title_fullStr Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title_full_unstemmed Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title_short Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
title_sort robust human machine interface based on head movements applied to assistive robotics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888755/
https://www.ncbi.nlm.nih.gov/pubmed/24453877
http://dx.doi.org/10.1155/2013/589636
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