A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along...

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Autores principales:	Bongjae Choi, Sungho Jo
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/eccfb43fa1a744eb8a024c9bac51f23b
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id	oai:doaj.org-article:eccfb43fa1a744eb8a024c9bac51f23b
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spelling	oai:doaj.org-article:eccfb43fa1a744eb8a024c9bac51f23b2021-11-18T08:56:51ZA low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.1932-620310.1371/journal.pone.0074583https://doaj.org/article/eccfb43fa1a744eb8a024c9bac51f23b2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24023953/?tool=EBIhttps://doaj.org/toc/1932-6203This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system.Bongjae ChoiSungho JoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 9, p e74583 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bongjae Choi Sungho Jo A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
description	This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system.
format	article
author	Bongjae Choi Sungho Jo
author_facet	Bongjae Choi Sungho Jo
author_sort	Bongjae Choi
title	A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
title_short	A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
title_full	A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
title_fullStr	A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
title_full_unstemmed	A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
title_sort	low-cost eeg system-based hybrid brain-computer interface for humanoid robot navigation and recognition.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/eccfb43fa1a744eb8a024c9bac51f23b
work_keys_str_mv	AT bongjaechoi alowcosteegsystembasedhybridbraincomputerinterfaceforhumanoidrobotnavigationandrecognition AT sunghojo alowcosteegsystembasedhybridbraincomputerinterfaceforhumanoidrobotnavigationandrecognition AT bongjaechoi lowcosteegsystembasedhybridbraincomputerinterfaceforhumanoidrobotnavigationandrecognition AT sunghojo lowcosteegsystembasedhybridbraincomputerinterfaceforhumanoidrobotnavigationandrecognition
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A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

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