Cover Image

Neuro-Fuzzy based motor imagery classification for a four class brain machine interface

Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.

Saved in:
Bibliographic Details
Main Authors: Hema, Chengalvarayan Radhakrishnamurthy, Paulraj, Murugesapandian, Sazali, Yaacob, Abdul Hamid, Adom, Ramachandran, Nagarajan
Other Authors: hema@unimap.edu.my
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis 2009
Subjects:
Brain Machine Interfaces
EEG motor imagery
EEG band power
Neuro-fuzzy classifiers
Brain-computer interfaces
Computational neuroscience
Bioengineering
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7339
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-7339
record_format dspace
spelling my.unimap-73392010-01-21T01:56:27Z Neuro-Fuzzy based motor imagery classification for a four class brain machine interface Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesapandian Sazali, Yaacob Abdul Hamid, Adom Ramachandran, Nagarajan hema@unimap.edu.my Brain Machine Interfaces EEG motor imagery EEG band power Neuro-fuzzy classifiers Brain-computer interfaces Computational neuroscience Bioengineering Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. Brain Machine Interface (BMI) provides a digital link between the brain and a device such as a computer, robot or wheelchair. This paper presents a BMI design using Neuro-Fuzzy classifiers for controlling a wheelchair using EEG signals. EEG signals during motor imagery (MI) of left and right hand movements are recorded noninvasively at the sensorimotor cortex. Four mental task signals are analyzed and classified to design a four class BMI. The proposed classifier has an average classification performance of 97%. 2009-11-18T07:33:11Z 2009-11-18T07:33:11Z 2009-10-11 Working Paper p.5B1 1 - 5B1 5 http://hdl.handle.net/123456789/7339 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) Universiti Malaysia Perlis
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 Brain Machine Interfaces
EEG motor imagery
EEG band power
Neuro-fuzzy classifiers
Brain-computer interfaces
Computational neuroscience
Bioengineering
spellingShingle Brain Machine Interfaces
EEG motor imagery
EEG band power
Neuro-fuzzy classifiers
Brain-computer interfaces
Computational neuroscience
Bioengineering
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
description Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
author2 hema@unimap.edu.my
author_facet hema@unimap.edu.my
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
format Working Paper
author Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Ramachandran, Nagarajan
author_sort Hema, Chengalvarayan Radhakrishnamurthy
title Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
title_short Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
title_full Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
title_fullStr Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
title_full_unstemmed Neuro-Fuzzy based motor imagery classification for a four class brain machine interface
title_sort neuro-fuzzy based motor imagery classification for a four class brain machine interface
publisher Universiti Malaysia Perlis
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7339
_version_ 1643788782535704576
score 13.222552

Similar Items