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Classification of EEG colour imagination tasks based BMI using energy and entropy features

International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.

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Bibliographic Details
Main Authors: Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Abdul Hamid, Adom, Assoc. Prof. Dr., Hema, Chengalvarayan Radhakrishnamurthy, Purushothaman, Divakar
Other Authors: paul@unimap.edu.my
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Brain machine interface
Colour imagination tasks
Neural network
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/20496
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spelling my.unimap-204962012-07-19T13:47:34Z Classification of EEG colour imagination tasks based BMI using energy and entropy features Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Hema, Chengalvarayan Radhakrishnamurthy Purushothaman, Divakar paul@unimap.edu.my abdhamid@unimap.edu.my Brain machine interface Colour imagination tasks Neural network International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. Electroencephalogram (EEG) signals are the electrophysiological measures of brain function and it is used to develop a brain machine interface. Brain machine interface (BMI) system is used to provide a communication and control technology for the mentally able people having neuromuscular disorders. In this paper, a simple BMI system based on EEG signal emanated while imagining of different colours has been proposed. The proposed BMI uses the color imagination tasks (CIT) and aims to provide a communication link using brain activated control signal; the required task operation can be then performed and the needs of the physically retarded community can be accomplished. Two feature extraction method are used for analysis namely energy and entropy. The extracted features are then associated to different control signals and a probabilistic neural network model (PNN) has been developed. The effectiveness of the two features are compared using PNN classification accuracy. 2012-07-19T13:47:32Z 2012-07-19T13:47:32Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20496 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
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 interface
Colour imagination tasks
Neural network
spellingShingle Brain machine interface
Colour imagination tasks
Neural network
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Hema, Chengalvarayan Radhakrishnamurthy
Purushothaman, Divakar
Classification of EEG colour imagination tasks based BMI using energy and entropy features
description International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.
author2 paul@unimap.edu.my
author_facet paul@unimap.edu.my
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Hema, Chengalvarayan Radhakrishnamurthy
Purushothaman, Divakar
format Working Paper
author Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Hema, Chengalvarayan Radhakrishnamurthy
Purushothaman, Divakar
author_sort Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
title Classification of EEG colour imagination tasks based BMI using energy and entropy features
title_short Classification of EEG colour imagination tasks based BMI using energy and entropy features
title_full Classification of EEG colour imagination tasks based BMI using energy and entropy features
title_fullStr Classification of EEG colour imagination tasks based BMI using energy and entropy features
title_full_unstemmed Classification of EEG colour imagination tasks based BMI using energy and entropy features
title_sort classification of eeg colour imagination tasks based bmi using energy and entropy features
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/20496
_version_ 1643793090212790272
score 13.222552

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