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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 rev...

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Main Authors: Murali Krishnan, Muralindran Mariappan
Format: Article
Language:English
Published: Volume 3, Issue 2 2015
Subjects:
TL Motor vehicles. Aeronautics. Astronautics
Online Access:https://eprints.ums.edu.my/id/eprint/21642/1/EEG-Based%20Brain-Machine%20Interface%20%28BMI%29.pdf
https://eprints.ums.edu.my/id/eprint/21642/
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id my.ums.eprints.21642
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spelling my.ums.eprints.216422019-03-15T07:23:14Z https://eprints.ums.edu.my/id/eprint/21642/ EEG-Based Brain-Machine Interface (BMI) for Controlling Mobile Robots: The Trend of Prior Studies Murali Krishnan Muralindran Mariappan TL Motor vehicles. Aeronautics. Astronautics 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. Volume 3, Issue 2 2015 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/21642/1/EEG-Based%20Brain-Machine%20Interface%20%28BMI%29.pdf 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). ISSN 2320–4028
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/
language English
topic TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TL Motor vehicles. Aeronautics. Astronautics
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
publisher Volume 3, Issue 2
publishDate 2015
url https://eprints.ums.edu.my/id/eprint/21642/1/EEG-Based%20Brain-Machine%20Interface%20%28BMI%29.pdf
https://eprints.ums.edu.my/id/eprint/21642/
_version_ 1760229869449379840
score 13.209306

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