EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies

Recently, a novel method created on thought based brain signal and it has been technologically advanced rapidly. The Brain control system is a rapidly emerging multidisciplinary study area which has perceived remarkable achievement over the past few years. In this paper, we review the background, f...

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Main Authors:	Murali Krishnan, Muralindran Mariappan
Format:	Article
Published:	2015
Subjects:	TJ Mechanical engineering and machinery
Online Access:	https://eprints.ums.edu.my/id/eprint/15230/ http://www.isaet.org/images/extraimages/P515033.pdf
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Institution:	Universiti Malaysia Sabah

id	my.ums.eprints.15230
record_format	eprints
spelling	my.ums.eprints.152302024-03-11T04:31:34Z https://eprints.ums.edu.my/id/eprint/15230/ EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies Murali Krishnan, Muralindran Mariappan, TJ Mechanical engineering and machinery Recently, a novel method created on thought based brain signal and it has been technologically advanced rapidly. The Brain control system is a rapidly emerging multidisciplinary study area which has perceived remarkable achievement over the past few years. In this paper, we review the background, feature extraction and classification algorithms used to design the Electroencephalography (EEG) based Brain-Machine Interface (BMI) to control the mobile robots. 2015 Article NonPeerReviewed Murali Krishnan, and Muralindran Mariappan, (2015) EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies. International Journal of Computer Science and Electronics Engineering (IJCSEE), 3 (2). pp. 159-165. ISSN 2320-4028 http://www.isaet.org/images/extraimages/P515033.pdf
institution	Universiti Malaysia Sabah
building	UMS Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Sabah
content_source	UMS Institutional Repository
url_provider	http://eprints.ums.edu.my/
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Murali Krishnan, Muralindran Mariappan, EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
description	Recently, a novel method created on thought based brain signal and it has been technologically advanced rapidly. The Brain control system is a rapidly emerging multidisciplinary study area which has perceived remarkable achievement over the past few years. In this paper, we review the background, feature extraction and classification algorithms used to design the Electroencephalography (EEG) based Brain-Machine Interface (BMI) to control the mobile robots.
format	Article
author	Murali Krishnan, Muralindran Mariappan,
author_facet	Murali Krishnan, Muralindran Mariappan,
author_sort	Murali Krishnan,
title	EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
title_short	EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
title_full	EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
title_fullStr	EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
title_full_unstemmed	EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies
title_sort	eeg-based brain-machine interface (bmi) for controlling mobile robots: the trend of prior studies
publishDate	2015
url	https://eprints.ums.edu.my/id/eprint/15230/ http://www.isaet.org/images/extraimages/P515033.pdf
_version_	1794553641416261632

EEG-based brain-machine interface (BMI) for controlling mobile robots: the trend of prior studies

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