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/ http://umpir.ump.edu.my/id/eprint/23210/ http://umpir.ump.edu.my/id/eprint/23210/ 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

id	ump-23210
recordtype	eprints
spelling	ump-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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
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/ http://umpir.ump.edu.my/id/eprint/23210/ http://umpir.ump.edu.my/id/eprint/23210/ 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
first_indexed	2023-09-18T22:34:41Z
last_indexed	2023-09-18T22:34:41Z
_version_	1777416516227039232

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

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