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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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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
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score 13.160551

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