Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals
Introduction: In most BCI articles which aim to separate movement imaginations, µ and &beta frequency bands have been used. In this paper, the effect of presence and absence of &gamma band on performance improvement is discussed since movement imaginations affect &gamma frequency band as...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Iran University of Medical Sciences
2013-02-01
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| Series: | Basic and Clinical Neuroscience |
| Subjects: | |
| Online Access: | http://bcn.iums.ac.ir/browse.php?a_code=A-10-1-146&slc_lang=en&sid=1 |
| _version_ | 1797283063952048128 |
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| author | Mina Mirnaziri Masoomeh Rahimi Sepidehsadat Alavikakhaki Reza Ebrahimpour |
| author_facet | Mina Mirnaziri Masoomeh Rahimi Sepidehsadat Alavikakhaki Reza Ebrahimpour |
| author_sort | Mina Mirnaziri |
| collection | DOAJ |
| description | Introduction: In most BCI articles which aim to separate movement imaginations, µ and &beta frequency bands have been used. In this paper, the effect of presence and absence of &gamma band on performance improvement is discussed since movement imaginations affect &gamma frequency band as well.
Methods: In this study we used data set 2a from BCI Competition IV. In this data set, 9 healthy subjects have performed left hand, right hand, foot and tongue movement imaginations. Time and frequency intervals are computed for each subject and then are classi.ed using Common Spatial Pattern (CSP) as a feature extractor. Finally, data is classi.ed by LDA1, RBF2 MLP3, SVM4and KNN 5 methods. In all experiments, accuracy rate of classi.cation is computed using 4 fold validation method.
Results: It is seen that most of the time, combination of &mu,&beta and &gamma bands would have better performance than just using combination of &mu and &beta bands or &gamma band alone. In general, the improvement rate of the average classi.cation accuracy is computed 2.91%.
Discussion: In this study, it is shown that using combination of µ, &beta and &gamma frequency bands provides more information than only using combination of µ and &beta in movement imagination separations. |
| first_indexed | 2024-03-07T17:25:39Z |
| format | Article |
| id | doaj.art-dd6b5221ae0945d083063ca6adb6c359 |
| institution | Directory Open Access Journal |
| issn | 2008-126X 2228-7442 |
| language | English |
| last_indexed | 2024-03-07T17:25:39Z |
| publishDate | 2013-02-01 |
| publisher | Iran University of Medical Sciences |
| record_format | Article |
| series | Basic and Clinical Neuroscience |
| spelling | doaj.art-dd6b5221ae0945d083063ca6adb6c3592024-03-02T19:16:39ZengIran University of Medical SciencesBasic and Clinical Neuroscience2008-126X2228-74422013-02-01417687Using Combination of μ,β and γ Bands in Classi.cation of EEG SignalsMina Mirnaziri0Masoomeh Rahimi1Sepidehsadat Alavikakhaki2Reza Ebrahimpour3 Brain and Intelligent Systems Research Laboratory (BISLab), Department of Electrical and Computer Engineering, ShahidRajaee Teacher Training University, Tehran, Iran. Brain and Intelligent Systems Research Laboratory (BISLab), Department of Electrical and Computer Engineering, ShahidRajaee Teacher Training University, Tehran, Iran. Department of Computer Science, School of Mathematics, Statistics and Computer Science, University of Tehran, Iran. Brain and Intelligent Systems Research Laboratory (BISLab), Department of Electrical and Computer Engineering, ShahidRajaee Teacher Training University, Tehran, Iran. Introduction: In most BCI articles which aim to separate movement imaginations, µ and &beta frequency bands have been used. In this paper, the effect of presence and absence of &gamma band on performance improvement is discussed since movement imaginations affect &gamma frequency band as well. Methods: In this study we used data set 2a from BCI Competition IV. In this data set, 9 healthy subjects have performed left hand, right hand, foot and tongue movement imaginations. Time and frequency intervals are computed for each subject and then are classi.ed using Common Spatial Pattern (CSP) as a feature extractor. Finally, data is classi.ed by LDA1, RBF2 MLP3, SVM4and KNN 5 methods. In all experiments, accuracy rate of classi.cation is computed using 4 fold validation method. Results: It is seen that most of the time, combination of &mu,&beta and &gamma bands would have better performance than just using combination of &mu and &beta bands or &gamma band alone. In general, the improvement rate of the average classi.cation accuracy is computed 2.91%. Discussion: In this study, it is shown that using combination of µ, &beta and &gamma frequency bands provides more information than only using combination of µ and &beta in movement imagination separations.http://bcn.iums.ac.ir/browse.php?a_code=A-10-1-146&slc_lang=en&sid=1Brain – Computer Interface (BCI)Electroencephalogram (EEG)Common Spatial Pattern (CSP)Multi – Layer Perceptron (MLP)Linear Discriminant Analysis (LDA)Radial Basis Function (RBF). |
| spellingShingle | Mina Mirnaziri Masoomeh Rahimi Sepidehsadat Alavikakhaki Reza Ebrahimpour Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals Basic and Clinical Neuroscience Brain – Computer Interface (BCI) Electroencephalogram (EEG) Common Spatial Pattern (CSP) Multi – Layer Perceptron (MLP) Linear Discriminant Analysis (LDA) Radial Basis Function (RBF). |
| title | Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals |
| title_full | Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals |
| title_fullStr | Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals |
| title_full_unstemmed | Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals |
| title_short | Using Combination of μ,β and γ Bands in Classi.cation of EEG Signals |
| title_sort | using combination of μ β and γ bands in classi cation of eeg signals |
| topic | Brain – Computer Interface (BCI) Electroencephalogram (EEG) Common Spatial Pattern (CSP) Multi – Layer Perceptron (MLP) Linear Discriminant Analysis (LDA) Radial Basis Function (RBF). |
| url | http://bcn.iums.ac.ir/browse.php?a_code=A-10-1-146&slc_lang=en&sid=1 |
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