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Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal

One of the popular features extraction methods for recognizing motor imagery EEG signal is Common Spatial Pattern (CSP). CSP is an algorithm that maximize the variance of one class and minimize the variance of other class simultaneously to discriminate two classes of multichannel EEG signals for cla...

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Main Authors: Hilman, Fauzi, Mohd Ibrahim, Shapiai, Noor Akhmad, Setiawan, Jafreezal, Jaafar, Mahfuzah, Mustafa
Format: Conference or Workshop Item
Language:English
Published: IEEE 2017
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/23210/1/Channel%20selection%20for%20common%20spatial%20pattern%20Based%20on%20energy%20calculation%20of%20motor%20imagery%20EEG%20signal.pdf
http://umpir.ump.edu.my/id/eprint/23210/
https://doi.org/10.1109/ICCEREC.2017.8226692
https://doi.org/10.1016/j.ijrefrig.2018.02.006
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spelling my.ump.umpir.232102019-05-16T06:17:04Z http://umpir.ump.edu.my/id/eprint/23210/ Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal Hilman, Fauzi Mohd Ibrahim, Shapiai Noor Akhmad, Setiawan Jafreezal, Jaafar Mahfuzah, Mustafa TK Electrical engineering. Electronics Nuclear engineering One of the popular features extraction methods for recognizing motor imagery EEG signal is Common Spatial Pattern (CSP). CSP is an algorithm that maximize the variance of one class and minimize the variance of other class simultaneously to discriminate two classes of multichannel EEG signals for classification purpose. However, CSP assumes that the signals on all EEG channels are functionally interconnected even though only spurious relationship due to artefact or noise. This study will conduct several investigations on the classification performance by imposing channels selection based on calculated energy on brain excitation calculation. The improvement strategy calculates the energy in each channel and the selection will be based on the energy level. In order to validate the performance of the proposed technique, three motor imagery data sets are employed including RIKEN, BCI Competition III Data set IVa, and BCI Competition IV Data set I. In general, all these datasets are tested on the existing CSP and its variants with and without the proposed channel selection strategy. The existing techniques such as CSP, R-CSP (regularized CSP), and A-CSP (analytic CSP) are included in this study. The results show that the selected channels with higher energy can improve the CSP, R-CSP and A-CSP classification performance. Also, smaller size of selected channels in the area of motor cortex offers better performance with almost 75% channel reduction and 8% increase in accuracy. IEEE 2017 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23210/1/Channel%20selection%20for%20common%20spatial%20pattern%20Based%20on%20energy%20calculation%20of%20motor%20imagery%20EEG%20signal.pdf Hilman, Fauzi and Mohd Ibrahim, Shapiai and Noor Akhmad, Setiawan and Jafreezal, Jaafar and Mahfuzah, Mustafa (2017) Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal. In: 3rd International Conference on Control, Electronics, Renewable Energy, and Communications (ICCREC 2017), 26-28 September 2017 , Yogyakarta, Indonesia. pp. 33-39., 2017. ISBN 978-1-5386-1667-3 https://doi.org/10.1109/ICCEREC.2017.8226692 https://doi.org/10.1016/j.ijrefrig.2018.02.006
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Hilman, Fauzi
Mohd Ibrahim, Shapiai
Noor Akhmad, Setiawan
Jafreezal, Jaafar
Mahfuzah, Mustafa
Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
description One of the popular features extraction methods for recognizing motor imagery EEG signal is Common Spatial Pattern (CSP). CSP is an algorithm that maximize the variance of one class and minimize the variance of other class simultaneously to discriminate two classes of multichannel EEG signals for classification purpose. However, CSP assumes that the signals on all EEG channels are functionally interconnected even though only spurious relationship due to artefact or noise. This study will conduct several investigations on the classification performance by imposing channels selection based on calculated energy on brain excitation calculation. The improvement strategy calculates the energy in each channel and the selection will be based on the energy level. In order to validate the performance of the proposed technique, three motor imagery data sets are employed including RIKEN, BCI Competition III Data set IVa, and BCI Competition IV Data set I. In general, all these datasets are tested on the existing CSP and its variants with and without the proposed channel selection strategy. The existing techniques such as CSP, R-CSP (regularized CSP), and A-CSP (analytic CSP) are included in this study. The results show that the selected channels with higher energy can improve the CSP, R-CSP and A-CSP classification performance. Also, smaller size of selected channels in the area of motor cortex offers better performance with almost 75% channel reduction and 8% increase in accuracy.
format Conference or Workshop Item
author Hilman, Fauzi
Mohd Ibrahim, Shapiai
Noor Akhmad, Setiawan
Jafreezal, Jaafar
Mahfuzah, Mustafa
author_facet Hilman, Fauzi
Mohd Ibrahim, Shapiai
Noor Akhmad, Setiawan
Jafreezal, Jaafar
Mahfuzah, Mustafa
author_sort Hilman, Fauzi
title Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
title_short Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
title_full Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
title_fullStr Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
title_full_unstemmed Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
title_sort channel selection for common spatial pattern based on energy calculation of motor imagery eeg signal
publisher IEEE
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/23210/1/Channel%20selection%20for%20common%20spatial%20pattern%20Based%20on%20energy%20calculation%20of%20motor%20imagery%20EEG%20signal.pdf
http://umpir.ump.edu.my/id/eprint/23210/
https://doi.org/10.1109/ICCEREC.2017.8226692
https://doi.org/10.1016/j.ijrefrig.2018.02.006
_version_ 1643669546455793664
score 13.211869

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