Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces
Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific cha...
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| Published in | Cognitive computation Vol. 8; no. 3; pp. 505 - 518 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.06.2016
Springer Nature B.V Springer |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1866-9956 1866-9964 |
| DOI | 10.1007/s12559-015-9379-z |
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| Abstract | Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific channel selection method based on a criterion called
F
score to realize the parameterization of both time segment and channel positions. The
F
score is a novel simplified measure derived from Fisher’s discriminant analysis for evaluating the discriminative power of a group of features. The experimental results on a standard dataset (BCI competition III dataset IVa) show that our method can efficiently reduce the number of channels (from 118 channels to 9 in average) without a decrease in mean classification accuracy. Compared to two state-of-the-art methods in channel selection, our method leads to comparable or even better classification results with less selected channels. |
|---|---|
| AbstractList | Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific channel selection method based on a criterion called F score to realize the parameterization of both time segment and channel positions. The F score is a novel simplified measure derived from Fisher’s discriminant analysis for evaluating the discriminative power of a group of features. The experimental results on a standard dataset (BCI competition III dataset IVa) show that our method can efficiently reduce the number of channels (from 118 channels to 9 in average) without a decrease in mean classification accuracy. Compared to two state-of-the-art methods in channel selection, our method leads to comparable or even better classification results with less selected channels. Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific channel selection method based on a criterion called F score to realize the parameterization of both time segment and channel positions. The F score is a novel simplified measure derived from Fisher's discrimi-nant analysis for evaluating the discriminative power of a group of features. The experimental results on a standard dataset (BCI competition III dataset IVa) show that our method can efficiently reduce the number of channels (from 118 channels to 9 in average) without a decrease in mean classification accuracy. Compared to two state-of-the-art methods in channel selection, our method leads to comparable or even better classification results with less selected channels. Keeping a minimal number of channels is essential for designing a portable brain–computer interface system for daily usage. Most existing methods choose key channels based on spatial information without optimization of time segment for classification. This paper proposes a novel subject-specific channel selection method based on a criterion called F score to realize the parameterization of both time segment and channel positions. The F score is a novel simplified measure derived from Fisher’s discriminant analysis for evaluating the discriminative power of a group of features. The experimental results on a standard dataset (BCI competition III dataset IVa) show that our method can efficiently reduce the number of channels (from 118 channels to 9 in average) without a decrease in mean classification accuracy. Compared to two state-of-the-art methods in channel selection, our method leads to comparable or even better classification results with less selected channels. |
| Author | Bloch, Isabelle Chevallier, Sylvain Yang, Yuan Wiart, Joe |
| Author_xml | – sequence: 1 givenname: Yuan surname: Yang fullname: Yang, Yuan email: Y.Yang-2@tudelft.nl organization: LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, Whist Lab, Department of BioMechanical Engineering, Delft University of Technology – sequence: 2 givenname: Isabelle surname: Bloch fullname: Bloch, Isabelle organization: LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, Whist Lab – sequence: 3 givenname: Sylvain surname: Chevallier fullname: Chevallier, Sylvain organization: LISV - IUT de Vélizy, Université de Versailles St-Quentin – sequence: 4 givenname: Joe surname: Wiart fullname: Wiart, Joe organization: LTCI, CNRS, Télécom ParisTech, Université Paris-Saclay, Whist Lab, Orange Labs R&D |
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| Cites_doi | 10.1371/journal.pone.0120432 10.1109/MC.2008.409 10.1007/s12559-013-9239-7 10.1109/TBME.2004.827827 10.1002/ima.20285 10.1109/TNSRE.2006.875557 10.1186/s12938-015-0087-4 10.1016/j.neunet.2009.07.020 10.1007/s12559-014-9264-1 10.1016/j.neuroimage.2005.12.003 10.1016/S1388-2457(02)00057-3 10.1109/TBME.2009.2032162 10.1109/MSP.2008.4408441 10.1016/S0013-4694(97)00022-2 10.1109/MC.2008.407 10.1016/S0079-6123(06)59014-4 10.1016/j.neucom.2013.05.005 10.1109/TNSRE.2006.875642 10.1007/s00521-010-0481-6 10.1016/S0079-6123(06)59006-5 10.1109/34.574797 10.1186/1687-6180-2014-38 10.1586/17434440.4.4.463 10.1088/1741-2560/4/2/R01 10.1186/s13634-015-0251-9 10.1155/2015/703768 10.1109/ICASSP.2008.4517635 10.1109/ICASSP.2013.6637856 10.1109/NER.2011.5910558 10.1007/978-3-642-41184-7_57 10.1109/EMBC.2012.6346532 10.1109/IEMBS.2005.1615701 |
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| Keywords | Fisher’s discriminant analysis Brain–computer interfaces Channel reduction EEG Time information channel reduction Fisher's discriminant analysis time information |
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| References | Blankertz, Tomioka, Lemm, Kawanabe, Müller (CR7) 2008; 25 Li, Koike (CR17) 2011; 20 Shan, Xu, Zhu, He (CR27) 2015; 14 CR15 CR37 CR36 Vidaurre, Kramer, Blankertz, Schlögl (CR28) 2009; 22 CR35 Blankertz, Dornhege, Krauledat, Müller, Kunzmann, Losch, Curio (CR5) 2006; 14 CR33 CR32 CR30 Gouy-Pailler, Congedo, Brunner, Jutten, Pfurtscheller (CR9) 2010; 57 Pfurtscheller, Brunner, Schlögl, Lopes da Silva (CR25) 2006; 31 Duan, Zhong, Miao, Yang, Ma, Zhang (CR8) 2014; 6 Neuper, Wörtz, Pfurtscheller (CR24) 2006; 159 He, Hu, Li, Li (CR12) 2013; 121 Jasper (CR14) 1958; 10 Müller, Krauledat, Dornhege, Curio, Blankertz (CR21) 2004; 49 Naeem, Brunner, Pfurtscheller (CR22) 2009; 1–8 Alotaiby, El-Samie, Alshebeili, Ahmad (CR2) 2015; 2015 Ansuini, Cavallo, Koul, Jacono, Yang, Becchio (CR3) 2015; 10 CR4 Graimann, Pfurtscheller (CR11) 2006; 159 CR29 Yang, Chevallier, Wiart, Bloch (CR34) 2014; 2014 Lal, Schröder, Hinterberger, Weston, Bogdan, Birbaumer, Schölkopf (CR16) 2004; 51 Allison, Wolpaw, Wolpaw (CR1) 2007; 4 Blankertz, Müller, Krusienski, Schalk, Wolpaw, Schlögl, Pfurtscheller, Millán, Schroder, Birbaumer (CR6) 2006; 14 Wolpaw, Birbaumer, McFarland, Pfurtscheller, Vaughan (CR31) 2002; 113 Schlögl, Brunner (CR26) 2008; 41 Jain, Zongker (CR13) 1997; 19 McFarland, Wolpaw (CR19) 2008; 41 Lotte, Congedo, Lécuyer, Lamarche, Arnaldi (CR18) 2007; 4 Gouy-Pailler, Sebag, Larue, Souloumiac (CR10) 2011; 21 McFarland, McCane, David, Wolpaw (CR20) 1997; 103 Naji, Firoozabadi, Azadfallah (CR23) 2014; 6 Dennis J McFarland (9379_CR20) 1997; 103 9379_CR30 Y Li (9379_CR17) 2011; 20 C Ansuini (9379_CR3) 2015; 10 9379_CR4 C Neuper (9379_CR24) 2006; 159 B Graimann (9379_CR11) 2006; 159 A Jain (9379_CR13) 1997; 19 M Naji (9379_CR23) 2014; 6 KR Müller (9379_CR21) 2004; 49 B Blankertz (9379_CR6) 2006; 14 TN Lal (9379_CR16) 2004; 51 HH Jasper (9379_CR14) 1958; 10 C Gouy-Pailler (9379_CR9) 2010; 57 9379_CR15 9379_CR37 DJ McFarland (9379_CR19) 2008; 41 9379_CR35 F Lotte (9379_CR18) 2007; 4 9379_CR36 9379_CR33 G Pfurtscheller (9379_CR25) 2006; 31 9379_CR32 L He (9379_CR12) 2013; 121 C Gouy-Pailler (9379_CR10) 2011; 21 A Schlögl (9379_CR26) 2008; 41 C Vidaurre (9379_CR28) 2009; 22 B Blankertz (9379_CR7) 2008; 25 L Duan (9379_CR8) 2014; 6 B Blankertz (9379_CR5) 2006; 14 Y Yang (9379_CR34) 2014; 2014 H Shan (9379_CR27) 2015; 14 BZ Allison (9379_CR1) 2007; 4 9379_CR29 JR Wolpaw (9379_CR31) 2002; 113 M Naeem (9379_CR22) 2009; 1–8 T Alotaiby (9379_CR2) 2015; 2015 |
| References_xml | – volume: 10 start-page: e0120432 issue: 3 year: 2015 ident: CR3 article-title: Predicting object size from hand kinematics: a temporal perspective publication-title: PLoS One doi: 10.1371/journal.pone.0120432 – volume: 41 start-page: 52 issue: 10 year: 2008 end-page: 56 ident: CR19 article-title: Brain–computer interface operation of robotic and prosthetic devices publication-title: Computer doi: 10.1109/MC.2008.409 – volume: 6 start-page: 241 issue: 2 year: 2014 end-page: 252 ident: CR23 article-title: Classification of music-induced emotions based on information fusion of forehead biosignals and electrocardiogram publication-title: Cogn Comput doi: 10.1007/s12559-013-9239-7 – volume: 51 start-page: 1003 issue: 6 year: 2004 end-page: 1010 ident: CR16 article-title: Support vector channel selection in BCI publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2004.827827 – ident: CR4 – volume: 21 start-page: 148 issue: 2 year: 2011 end-page: 157 ident: CR10 article-title: Single trial variability in brain-computer interfaces based on motor imagery: learning in the presence of labeling noise publication-title: Int J Imaging Syst Technol doi: 10.1002/ima.20285 – ident: CR37 – volume: 14 start-page: 147 issue: 2 year: 2006 end-page: 152 ident: CR5 article-title: The Berlin brain–computer interface: EEG-based communication without subject training publication-title: IEEE Trans Neural Syst Rehabil Eng doi: 10.1109/TNSRE.2006.875557 – volume: 14 start-page: 93 issue: 1 year: 2015 ident: CR27 article-title: A novel channel selection method for optimal classification in different motor imagery BCI paradigms publication-title: Biomed Eng Online doi: 10.1186/s12938-015-0087-4 – volume: 22 start-page: 1313 issue: 9 year: 2009 end-page: 1319 ident: CR28 article-title: Time domain parameters as a feature for EEG-based brain–computer interfaces publication-title: Neural Netw doi: 10.1016/j.neunet.2009.07.020 – ident: CR30 – volume: 6 start-page: 477 issue: 3 year: 2014 end-page: 483 ident: CR8 article-title: A voting optimized strategy based on ELM for improving classification of motor imagery BCI data publication-title: Cogn Comput doi: 10.1007/s12559-014-9264-1 – volume: 31 start-page: 153 issue: 1 year: 2006 end-page: 159 ident: CR25 article-title: Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks publication-title: NeuroImage doi: 10.1016/j.neuroimage.2005.12.003 – volume: 113 start-page: 767 issue: 6 year: 2002 end-page: 791 ident: CR31 article-title: Brain–computer interfaces for communication and control publication-title: Clin Neurophysiol doi: 10.1016/S1388-2457(02)00057-3 – ident: CR33 – volume: 57 start-page: 469 issue: 2 year: 2010 end-page: 478 ident: CR9 article-title: Nonstationary brain source separation for multiclass motor imagery publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2009.2032162 – volume: 10 start-page: 371 issue: 2 year: 1958 end-page: 375 ident: CR14 article-title: The ten-twenty electrode system of the International Federation publication-title: Electroencephalogr Clin Neurophysiol – volume: 25 start-page: 41 issue: 1 year: 2008 end-page: 56 ident: CR7 article-title: Optimizing spatial filters for robust EEG single-trial analysis publication-title: IEEE Signal Process Mag doi: 10.1109/MSP.2008.4408441 – ident: CR35 – ident: CR29 – volume: 103 start-page: 386 issue: 3 year: 1997 end-page: 394 ident: CR20 article-title: Spatial filter selection for EEG-based communication publication-title: Electroencephalogr Clin Neurophysiol doi: 10.1016/S0013-4694(97)00022-2 – volume: 49 start-page: 11 issue: 1 year: 2004 end-page: 22 ident: CR21 article-title: Machine learning techniques for brain-computer interfaces publication-title: Biomed Eng Biomed Tech – volume: 41 start-page: 44 issue: 10 year: 2008 end-page: 50 ident: CR26 article-title: BioSig: a free and open source software library for BCI research publication-title: Computer doi: 10.1109/MC.2008.407 – volume: 159 start-page: 211 year: 2006 end-page: 222 ident: CR24 article-title: ERD/ERS patterns reflecting sensorimotor activation and deactivation publication-title: Progr Brain Res doi: 10.1016/S0079-6123(06)59014-4 – volume: 121 start-page: 423 year: 2013 end-page: 433 ident: CR12 article-title: Channel selection by Rayleigh coefficient maximization based genetic algorithm for classifying single-trial motor imagery EEG publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.05.005 – volume: 14 start-page: 153 issue: 2 year: 2006 end-page: 159 ident: CR6 article-title: The BCI competition III: validating alternative approaches to actual BCI problems publication-title: IEEE Trans Neural Syst Rehabil Eng doi: 10.1109/TNSRE.2006.875642 – volume: 20 start-page: 1187 issue: 8 year: 2011 end-page: 1192 ident: CR17 article-title: A real-time BCI with a small number of channels based on CSP publication-title: Neural Comput Appl doi: 10.1007/s00521-010-0481-6 – volume: 159 start-page: 79 year: 2006 end-page: 97 ident: CR11 article-title: Quantification and visualization of event-related changes in oscillatory brain activity in the time-frequency domain publication-title: Progr Brain Res doi: 10.1016/S0079-6123(06)59006-5 – volume: 19 start-page: 153 issue: 2 year: 1997 end-page: 158 ident: CR13 article-title: Feature selection: evaluation, application, and small sample performance publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.574797 – ident: CR15 – volume: 2014 start-page: 38 issue: 1 year: 2014 ident: CR34 article-title: Time-frequency optimization for discrimination between imagination of right and left hand movements based on two bipolar electroencephalography channels publication-title: EURASIP J Adv Signal Process doi: 10.1186/1687-6180-2014-38 – volume: 4 start-page: 463 issue: 4 year: 2007 end-page: 474 ident: CR1 article-title: Brain–computer interface systems: progress and prospects publication-title: Expert Rev Med Dev doi: 10.1586/17434440.4.4.463 – ident: CR32 – ident: CR36 – volume: 4 start-page: R1 year: 2007 end-page: R14 ident: CR18 article-title: A review of classification algorithms for EEG-based brain-computer interfaces publication-title: J Neural Eng doi: 10.1088/1741-2560/4/2/R01 – volume: 2015 start-page: 1 issue: 1 year: 2015 end-page: 21 ident: CR2 article-title: A review of channel selection algorithms for EEG signal processing publication-title: EURASIP J Adv Signal Process doi: 10.1186/s13634-015-0251-9 – volume: 1–8 start-page: 2009 year: 2009 ident: CR22 article-title: Dimensionality reduction and channel selection of motor imagery electroencephalographic data publication-title: Comput Intell Neurosci – ident: 9379_CR29 doi: 10.1155/2015/703768 – ident: 9379_CR37 doi: 10.1109/ICASSP.2008.4517635 – volume: 4 start-page: R1 year: 2007 ident: 9379_CR18 publication-title: J Neural Eng doi: 10.1088/1741-2560/4/2/R01 – ident: 9379_CR35 doi: 10.1109/ICASSP.2013.6637856 – volume: 22 start-page: 1313 issue: 9 year: 2009 ident: 9379_CR28 publication-title: Neural Netw doi: 10.1016/j.neunet.2009.07.020 – volume: 20 start-page: 1187 issue: 8 year: 2011 ident: 9379_CR17 publication-title: Neural Comput Appl doi: 10.1007/s00521-010-0481-6 – volume: 2014 start-page: 38 issue: 1 year: 2014 ident: 9379_CR34 publication-title: EURASIP J Adv Signal Process doi: 10.1186/1687-6180-2014-38 – volume: 6 start-page: 477 issue: 3 year: 2014 ident: 9379_CR8 publication-title: Cogn Comput doi: 10.1007/s12559-014-9264-1 – volume: 113 start-page: 767 issue: 6 year: 2002 ident: 9379_CR31 publication-title: Clin Neurophysiol doi: 10.1016/S1388-2457(02)00057-3 – ident: 9379_CR4 doi: 10.1109/NER.2011.5910558 – volume: 2015 start-page: 1 issue: 1 year: 2015 ident: 9379_CR2 publication-title: EURASIP J Adv Signal Process doi: 10.1186/s13634-015-0251-9 – volume: 6 start-page: 241 issue: 2 year: 2014 ident: 9379_CR23 publication-title: Cogn Comput doi: 10.1007/s12559-013-9239-7 – volume: 41 start-page: 52 issue: 10 year: 2008 ident: 9379_CR19 publication-title: Computer doi: 10.1109/MC.2008.409 – volume: 25 start-page: 41 issue: 1 year: 2008 ident: 9379_CR7 publication-title: IEEE Signal Process Mag doi: 10.1109/MSP.2008.4408441 – ident: 9379_CR15 doi: 10.1007/978-3-642-41184-7_57 – volume: 51 start-page: 1003 issue: 6 year: 2004 ident: 9379_CR16 publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2004.827827 – volume: 57 start-page: 469 issue: 2 year: 2010 ident: 9379_CR9 publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2009.2032162 – volume: 159 start-page: 211 year: 2006 ident: 9379_CR24 publication-title: Progr Brain Res doi: 10.1016/S0079-6123(06)59014-4 – volume: 121 start-page: 423 year: 2013 ident: 9379_CR12 publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.05.005 – volume: 49 start-page: 11 issue: 1 year: 2004 ident: 9379_CR21 publication-title: Biomed Eng Biomed Tech – volume: 4 start-page: 463 issue: 4 year: 2007 ident: 9379_CR1 publication-title: Expert Rev Med Dev doi: 10.1586/17434440.4.4.463 – volume: 14 start-page: 147 issue: 2 year: 2006 ident: 9379_CR5 publication-title: IEEE Trans Neural Syst Rehabil Eng doi: 10.1109/TNSRE.2006.875557 – volume: 31 start-page: 153 issue: 1 year: 2006 ident: 9379_CR25 publication-title: NeuroImage doi: 10.1016/j.neuroimage.2005.12.003 – volume: 14 start-page: 153 issue: 2 year: 2006 ident: 9379_CR6 publication-title: IEEE Trans Neural Syst Rehabil Eng doi: 10.1109/TNSRE.2006.875642 – ident: 9379_CR33 doi: 10.1109/EMBC.2012.6346532 – volume: 21 start-page: 148 issue: 2 year: 2011 ident: 9379_CR10 publication-title: Int J Imaging Syst Technol doi: 10.1002/ima.20285 – ident: 9379_CR36 – volume: 1–8 start-page: 2009 year: 2009 ident: 9379_CR22 publication-title: Comput Intell Neurosci – ident: 9379_CR32 – volume: 159 start-page: 79 year: 2006 ident: 9379_CR11 publication-title: Progr Brain Res doi: 10.1016/S0079-6123(06)59006-5 – volume: 41 start-page: 44 issue: 10 year: 2008 ident: 9379_CR26 publication-title: Computer doi: 10.1109/MC.2008.407 – ident: 9379_CR30 doi: 10.1109/IEMBS.2005.1615701 – volume: 19 start-page: 153 issue: 2 year: 1997 ident: 9379_CR13 publication-title: IEEE Trans Pattern Anal Mach Intell doi: 10.1109/34.574797 – volume: 10 start-page: e0120432 issue: 3 year: 2015 ident: 9379_CR3 publication-title: PLoS One doi: 10.1371/journal.pone.0120432 – volume: 10 start-page: 371 issue: 2 year: 1958 ident: 9379_CR14 publication-title: Electroencephalogr Clin Neurophysiol – volume: 14 start-page: 93 issue: 1 year: 2015 ident: 9379_CR27 publication-title: Biomed Eng Online doi: 10.1186/s12938-015-0087-4 – volume: 103 start-page: 386 issue: 3 year: 1997 ident: 9379_CR20 publication-title: Electroencephalogr Clin Neurophysiol doi: 10.1016/S0013-4694(97)00022-2 |
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| SubjectTerms | Algorithms Artificial Intelligence Biomedical and Life Sciences Biomedicine Brain research Channels Classification Cognitive science Computation by Abstract Devices Computational Biology/Bioinformatics Computer Science Datasets Discriminant analysis Electrodes Electroencephalography Human-computer interface Machine Learning Methods Neuroscience Neurosciences Parameterization Segments Signal and Image Processing Signal processing Spatial data |
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| Title | Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces |
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