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Single trial motor imagery classification for a four state brain machine interface

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Main Authors: Hema, Chengalvarayan Radhakrishnamurthy, Paulraj, Murugesapandian, Sazali, Yaacob, Abdul Hamid, Adom, Ramachandran, Nagarajan
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineering (IEEE) 2009
Subjects:
Biomedical electrodes
Medical control systems
Electroencephalography
Handicapped aids
Brain Machine Interfaces (BMI)
Digital communication system
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7350
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spelling my.unimap-73502010-11-24T02:56:26Z Single trial motor imagery classification for a four state brain machine interface Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesapandian Sazali, Yaacob Abdul Hamid, Adom Ramachandran, Nagarajan Biomedical electrodes Medical control systems Electroencephalography Handicapped aids Brain Machine Interfaces (BMI) Digital communication system Link to publisher's homepage at http://ieeexplore.ieee.org Motor imagery is the mental simulation of a motor act which can be used to design brain machine interfaces [BMI]. A BMI is a digital communication system, which connects the human brain directly to an external device bypassing the peripheral nervous system and muscular system. Thus a BMI opens up possibilities for a new communication channel for people with neuromuscular disorders. The ability of an individual to control his EEG through imaginary motor tasks enables him to control devices. This paper presents a novel method for single trial motor imagery classification for a four state BMI to control a powered wheelchair. Recurrent Neural classifiers are used for classification of EEG signals during motor imagery for forward, stop, left and right hand movements. EEG is recorded using noninvasive scalp electrodes placed over the motor cortex. The performance of the proposed algorithm has an average classification efficiency of 96.15%. The proposed method can be used to translate the motor imagery signals into control signal using a four state BMI to control the directional movement of a powered wheelchair. 2009-11-19T13:38:11Z 2009-11-19T13:38:11Z 2009-03-06 Article p.39-41 978-1-4244-4151-8 http://ieeexplore.ieee.org/xpls/abs_all.jsp?=&arnumber=5069184 http://hdl.handle.net/123456789/7350 en Proceedings of the 5th International Colloquium on Signal Processing & Its Applications (CSPA 2009) Institute of Electrical and Electronics Engineering (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Biomedical electrodes
Medical control systems
Electroencephalography
Handicapped aids
Brain Machine Interfaces (BMI)
Digital communication system
spellingShingle Biomedical electrodes
Medical control systems
Electroencephalography
Handicapped aids
Brain Machine Interfaces (BMI)
Digital communication system
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
Single trial motor imagery classification for a four state brain machine interface
description Link to publisher's homepage at http://ieeexplore.ieee.org
format Article
author Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
author_facet Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
author_sort Hema, Chengalvarayan Radhakrishnamurthy
title Single trial motor imagery classification for a four state brain machine interface
title_short Single trial motor imagery classification for a four state brain machine interface
title_full Single trial motor imagery classification for a four state brain machine interface
title_fullStr Single trial motor imagery classification for a four state brain machine interface
title_full_unstemmed Single trial motor imagery classification for a four state brain machine interface
title_sort single trial motor imagery classification for a four state brain machine interface
publisher Institute of Electrical and Electronics Engineering (IEEE)
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7350
_version_ 1643788785882759168
score 13.214268

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