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Functional link PSO neural network based classification of EEG mental task signals

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Main Authors: Hema, Chengalvarayan Radhakrishnamurthy, Paulraj, Murugesapandian, Sazali, Yaacob, Abdul Hamid, Adom, Nagarajan, Ramachandran
Other Authors: hema@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineering (IEEE) 2009
Subjects:
Electroencephalography
EEG mental
Signal classification
Brain-computer interfaces
Medical signal processing
Principal component analysis
Neural nets
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7383
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spelling my.unimap-73832009-12-09T07:32:44Z Functional link PSO neural network based classification of EEG mental task signals Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesapandian Sazali, Yaacob Abdul Hamid, Adom Nagarajan, Ramachandran hema@unimap.edu.my Electroencephalography EEG mental Signal classification Brain-computer interfaces Medical signal processing Principal component analysis Neural nets Link to publisher's homepage at http://ieeexplore.ieee.org Classification of EEG mental task signals is a technique in the design of Brain machine interface [BMI]. A BMI can provide a digital channel for communication in the absence of the biological channels and are used to rehabilitate patients with neurodegenerative diseases, a condition in which all motor movements are impaired including speech leaving the patients totally locked-in. BMI are designed using the electrical activity of the brain detected by scalp EEG electrodes. In this paper five different mental tasks from two subjects were studied, combinations of two tasks are used in the classification process. A novel functional link neural network trained by a PSO algorithm is proposed for classification of the EEG signals. Principal component analysis features are used in the training and testing of the neural network. The average classification accuracies were observed to vary from 80.25% to 93% for the 10 different task combinations for each of the subjects. The proposed network has an average training time of 0.16 sec. The results obtained validate the performance of the proposed algorithm for mental task classification. 2009-12-09T07:32:44Z 2009-12-09T07:32:44Z 2008-08-26 Working Paper vol.3, p.1-6 978-1-4244-2327-9 http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4631976 http://hdl.handle.net/123456789/7383 en Proceedings of the International Symposium on Information Technology (ITSim 08) 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 Electroencephalography
EEG mental
Signal classification
Brain-computer interfaces
Medical signal processing
Principal component analysis
Neural nets
spellingShingle Electroencephalography
EEG mental
Signal classification
Brain-computer interfaces
Medical signal processing
Principal component analysis
Neural nets
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Nagarajan, Ramachandran
Functional link PSO neural network based classification of EEG mental task signals
description Link to publisher's homepage at http://ieeexplore.ieee.org
author2 hema@unimap.edu.my
author_facet hema@unimap.edu.my
Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Nagarajan, Ramachandran
format Working Paper
author Hema, Chengalvarayan Radhakrishnamurthy
Paulraj, Murugesapandian
Sazali, Yaacob
Abdul Hamid, Adom
Nagarajan, Ramachandran
author_sort Hema, Chengalvarayan Radhakrishnamurthy
title Functional link PSO neural network based classification of EEG mental task signals
title_short Functional link PSO neural network based classification of EEG mental task signals
title_full Functional link PSO neural network based classification of EEG mental task signals
title_fullStr Functional link PSO neural network based classification of EEG mental task signals
title_full_unstemmed Functional link PSO neural network based classification of EEG mental task signals
title_sort functional link pso neural network based classification of eeg mental task signals
publisher Institute of Electrical and Electronics Engineering (IEEE)
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7383
_version_ 1643788788249395200
score 13.214268

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