Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface

"The process through which children learn about the world and develop perceptual, cognitive and motor skills relies heavily on object exploration in their physical world. New types of assistive technology that enable children with impairments to interact with their environment have emerged in r...

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Autores Principales: Sakamaki I., Del Campo C.E.P., Wiebe S.A., Tavakoli M., Adams K.
Formato: Objeto de conferencia (Conference Object)
Lenguaje:Inglés (English)
Publicado: Institute of Electrical and Electronics Engineers Inc. 2017
Materias:
Acceso en línea:https://repository.urosario.edu.co/handle/10336/24029
https://doi.org/10.1109/SMC.2017.8122954
id ir-10336-24029
recordtype dspace
spelling ir-10336-240292020-06-03T22:15:16Z Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface Sakamaki I. Del Campo C.E.P. Wiebe S.A. Tavakoli M. Adams K. Biomedical signal processing Cybernetics Electroencephalography Electrophysiology Interfaces (computer) Machine design Robots Assistive technology Children with disabilities Classification accuracy Event related desynchronization Mobile robot control Movement intentions Robot controls Technical expertise Brain computer interface Assistive Technology Brain Computer Interfaces (BCI) Event Related Desynchronization (ERD) Robot Control "The process through which children learn about the world and develop perceptual, cognitive and motor skills relies heavily on object exploration in their physical world. New types of assistive technology that enable children with impairments to interact with their environment have emerged in recent years, and they could be beneficial for children's cognitive and perceptual skills development. Many studies have reported on brain computer interface (BCI) research. However, a conventional electroencephalography (EEG) system is generally bulky and expensive. It also requires special equipment and technical expertise to operate successfully. In this study, a compact low-cost EEG system was used to detect signals related to movement intention and control a mobile robot control. EEG signals of three non-disabled adults were acquired by the BCI system and the movement intention was classified during physical movement and motor imagery. The average classification accuracies achieved during testing were 56.4% for the motor imagery and 72.7% for the physical movement. The results show moderate classification accuracy for the motor imagery; however, the classification accuracy for the physical movement was high for all the subjects. Even though further improvement of the system is still needed, the experimental results demonstrated the feasibility of a BCI-based robotic system that is affordable and accessible for many people including children with disabilities. © 2017 IEEE." 2017 2020-05-26T00:07:45Z info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion https://repository.urosario.edu.co/handle/10336/24029 https://doi.org/10.1109/SMC.2017.8122954 eng info:eu-repo/semantics/openAccess application/pdf Institute of Electrical and Electronics Engineers Inc. instname:Universidad del Rosario reponame:Repositorio Institucional EdocUR
institution EdocUR - Universidad del Rosario
collection DSpace
language Inglés (English)
topic Biomedical signal processing
Cybernetics
Electroencephalography
Electrophysiology
Interfaces (computer)
Machine design
Robots
Assistive technology
Children with disabilities
Classification accuracy
Event related desynchronization
Mobile robot control
Movement intentions
Robot controls
Technical expertise
Brain computer interface
Assistive Technology
Brain Computer Interfaces (BCI)
Event Related Desynchronization (ERD)
Robot Control
spellingShingle Biomedical signal processing
Cybernetics
Electroencephalography
Electrophysiology
Interfaces (computer)
Machine design
Robots
Assistive technology
Children with disabilities
Classification accuracy
Event related desynchronization
Mobile robot control
Movement intentions
Robot controls
Technical expertise
Brain computer interface
Assistive Technology
Brain Computer Interfaces (BCI)
Event Related Desynchronization (ERD)
Robot Control
Sakamaki I.
Del Campo C.E.P.
Wiebe S.A.
Tavakoli M.
Adams K.
Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
description "The process through which children learn about the world and develop perceptual, cognitive and motor skills relies heavily on object exploration in their physical world. New types of assistive technology that enable children with impairments to interact with their environment have emerged in recent years, and they could be beneficial for children's cognitive and perceptual skills development. Many studies have reported on brain computer interface (BCI) research. However, a conventional electroencephalography (EEG) system is generally bulky and expensive. It also requires special equipment and technical expertise to operate successfully. In this study, a compact low-cost EEG system was used to detect signals related to movement intention and control a mobile robot control. EEG signals of three non-disabled adults were acquired by the BCI system and the movement intention was classified during physical movement and motor imagery. The average classification accuracies achieved during testing were 56.4% for the motor imagery and 72.7% for the physical movement. The results show moderate classification accuracy for the motor imagery; however, the classification accuracy for the physical movement was high for all the subjects. Even though further improvement of the system is still needed, the experimental results demonstrated the feasibility of a BCI-based robotic system that is affordable and accessible for many people including children with disabilities. © 2017 IEEE."
format Objeto de conferencia (Conference Object)
author Sakamaki I.
Del Campo C.E.P.
Wiebe S.A.
Tavakoli M.
Adams K.
author_facet Sakamaki I.
Del Campo C.E.P.
Wiebe S.A.
Tavakoli M.
Adams K.
author_sort Sakamaki I.
title Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
title_short Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
title_full Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
title_fullStr Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
title_full_unstemmed Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
title_sort assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://repository.urosario.edu.co/handle/10336/24029
https://doi.org/10.1109/SMC.2017.8122954
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score 11,387785